id	sid	tid	token	lemma	pos
afs-90955	1	1	agricultural	agricultural	ADJ
afs-90955	1	2	and	and	CCONJ
afs-90955	1	3	food	food	NOUN
afs-90955	1	4	science	science	PROPN
afs-90955	1	5	i.	i.	PROPN
afs-90955	1	6	strandén	strandén	PROPN
afs-90955	1	7	&	&	CCONJ
afs-90955	1	8	e.a	e.a	PROPN
afs-90955	1	9	.	.	PROPN
afs-90955	1	10	mäntysaari	mäntysaari	PROPN
afs-90955	1	11	(	(	PUNCT
afs-90955	1	12	2020	2020	NUM
afs-90955	1	13	)	)	PUNCT
afs-90955	1	14	29	29	NUM
afs-90955	1	15	:	:	PUNCT
afs-90955	1	16	166–176	166–176	NUM
afs-90955	1	17	166	166	NUM
afs-90955	1	18	bpop	bpop	NOUN
afs-90955	1	19	:	:	PUNCT
afs-90955	1	20	an	an	DET
afs-90955	1	21	efficient	efficient	ADJ
afs-90955	1	22	program	program	NOUN
afs-90955	1	23	for	for	ADP
afs-90955	1	24	estimating	estimate	VERB
afs-90955	1	25	base	base	ADJ
afs-90955	1	26	population	population	NOUN
afs-90955	1	27	allele	allele	NOUN
afs-90955	1	28	frequencies	frequency	NOUN
afs-90955	1	29	in	in	ADP
afs-90955	1	30	single	single	ADJ
afs-90955	1	31	and	and	CCONJ
afs-90955	1	32	multiple	multiple	ADJ
afs-90955	1	33	group	group	NOUN
afs-90955	1	34	structured	structure	VERB
afs-90955	1	35	populations	population	NOUN
afs-90955	1	36	ismo	ismo	NOUN
afs-90955	1	37	strandén	strandén	NOUN
afs-90955	1	38	and	and	CCONJ
afs-90955	1	39	esa	esa	PROPN
afs-90955	1	40	a.	a.	PROPN
afs-90955	1	41	mäntysaari	mäntysaari	PROPN
afs-90955	1	42	natural	natural	ADJ
afs-90955	1	43	resources	resources	PROPN
afs-90955	1	44	institute	institute	PROPN
afs-90955	1	45	finland	finland	PROPN
afs-90955	1	46	(	(	PUNCT
afs-90955	1	47	luke	luke	PROPN
afs-90955	1	48	)	)	PUNCT
afs-90955	1	49	,	,	PUNCT
afs-90955	1	50	jokioinen	jokioinen	PROPN
afs-90955	1	51	,	,	PUNCT
afs-90955	1	52	finland	finland	PROPN
afs-90955	1	53	e	e	NOUN
afs-90955	1	54	-	-	NOUN
afs-90955	1	55	mail	mail	NOUN
afs-90955	1	56	:	:	PUNCT
afs-90955	1	57	ismo.stranden@luke.fi	ismo.stranden@luke.fi	ADJ
afs-90955	1	58	base	base	NOUN
afs-90955	1	59	population	population	NOUN
afs-90955	1	60	allele	allele	NOUN
afs-90955	1	61	frequencies	frequency	NOUN
afs-90955	1	62	(	(	PUNCT
afs-90955	1	63	af	af	NOUN
afs-90955	1	64	)	)	PUNCT
afs-90955	1	65	should	should	AUX
afs-90955	1	66	be	be	AUX
afs-90955	1	67	used	use	VERB
afs-90955	1	68	in	in	ADP
afs-90955	1	69	genomic	genomic	ADJ
afs-90955	1	70	evaluations	evaluation	NOUN
afs-90955	1	71	.	.	PUNCT
afs-90955	2	1	a	a	DET
afs-90955	2	2	program	program	NOUN
afs-90955	2	3	named	name	VERB
afs-90955	2	4	bpop	bpop	NOUN
afs-90955	2	5	was	be	AUX
afs-90955	2	6	implemented	implement	VERB
afs-90955	2	7	to	to	PART
afs-90955	2	8	estimate	estimate	VERB
afs-90955	2	9	base	base	NOUN
afs-90955	2	10	population	population	NOUN
afs-90955	2	11	af	af	AUX
afs-90955	2	12	using	use	VERB
afs-90955	2	13	a	a	DET
afs-90955	2	14	generalized	generalized	ADJ
afs-90955	2	15	least	least	ADJ
afs-90955	2	16	squares	square	NOUN
afs-90955	2	17	(	(	PUNCT
afs-90955	2	18	gls	gls	NOUN
afs-90955	2	19	)	)	PUNCT
afs-90955	2	20	method	method	NOUN
afs-90955	2	21	when	when	SCONJ
afs-90955	2	22	the	the	DET
afs-90955	2	23	base	base	ADJ
afs-90955	2	24	population	population	NOUN
afs-90955	2	25	individuals	individual	NOUN
afs-90955	2	26	can	can	AUX
afs-90955	2	27	be	be	AUX
afs-90955	2	28	assigned	assign	VERB
afs-90955	2	29	to	to	ADP
afs-90955	2	30	groups	group	NOUN
afs-90955	2	31	.	.	PUNCT
afs-90955	3	1	the	the	DET
afs-90955	3	2	required	require	VERB
afs-90955	3	3	dense	dense	ADJ
afs-90955	3	4	matrix	matrix	NOUN
afs-90955	3	5	products	product	NOUN
afs-90955	3	6	involving	involve	VERB
afs-90955	3	7	(	(	PUNCT
afs-90955	3	8	a22	a22	PROPN
afs-90955	3	9	)	)	PUNCT
afs-90955	3	10	-1v	-1v	NOUN
afs-90955	3	11	were	be	AUX
afs-90955	3	12	implemented	implement	VERB
afs-90955	3	13	efficiently	efficiently	ADV
afs-90955	3	14	using	use	VERB
afs-90955	3	15	sparse	sparse	ADJ
afs-90955	3	16	submatrices	submatrice	NOUN
afs-90955	3	17	of	of	ADP
afs-90955	3	18	a-1	a-1	PROPN
afs-90955	3	19	,	,	PUNCT
afs-90955	3	20	where	where	SCONJ
afs-90955	3	21	a	a	PRON
afs-90955	3	22	and	and	CCONJ
afs-90955	3	23	a22	a22	PROPN
afs-90955	3	24	are	be	AUX
afs-90955	3	25	pedigree	pedigree	ADJ
afs-90955	3	26	relationship	relationship	NOUN
afs-90955	3	27	matrices	matrix	NOUN
afs-90955	3	28	for	for	ADP
afs-90955	3	29	all	all	PRON
afs-90955	3	30	and	and	CCONJ
afs-90955	3	31	genotyped	genotyped	ADJ
afs-90955	3	32	animals	animal	NOUN
afs-90955	3	33	,	,	PUNCT
afs-90955	3	34	respectively	respectively	ADV
afs-90955	3	35	.	.	PUNCT
afs-90955	4	1	three	three	NUM
afs-90955	4	2	approaches	approach	NOUN
afs-90955	4	3	were	be	AUX
afs-90955	4	4	implemented	implement	VERB
afs-90955	4	5	:	:	PUNCT
afs-90955	4	6	iteration	iteration	NOUN
afs-90955	4	7	on	on	ADP
afs-90955	4	8	pedigree	pedigree	ADJ
afs-90955	4	9	(	(	PUNCT
afs-90955	4	10	iop	iop	PROPN
afs-90955	4	11	)	)	PUNCT
afs-90955	4	12	,	,	PUNCT
afs-90955	4	13	iteration	iteration	NOUN
afs-90955	4	14	in	in	ADP
afs-90955	4	15	memory	memory	NOUN
afs-90955	4	16	(	(	PUNCT
afs-90955	4	17	i	i	NOUN
afs-90955	4	18	m	m	PROPN
afs-90955	4	19	)	)	PUNCT
afs-90955	4	20	,	,	PUNCT
afs-90955	4	21	and	and	CCONJ
afs-90955	4	22	direct	direct	ADJ
afs-90955	4	23	inversion	inversion	NOUN
afs-90955	4	24	by	by	ADP
afs-90955	4	25	sparsity	sparsity	NOUN
afs-90955	4	26	preserving	preserve	VERB
afs-90955	4	27	cholesky	cholesky	ADJ
afs-90955	4	28	decomposition	decomposition	NOUN
afs-90955	4	29	(	(	PUNCT
afs-90955	4	30	chm	chm	NOUN
afs-90955	4	31	)	)	PUNCT
afs-90955	4	32	.	.	PUNCT
afs-90955	5	1	the	the	DET
afs-90955	5	2	test	test	NOUN
afs-90955	5	3	data	datum	NOUN
afs-90955	5	4	had	have	VERB
afs-90955	5	5	1.5	1.5	NUM
afs-90955	5	6	million	million	NUM
afs-90955	5	7	animals	animal	NOUN
afs-90955	5	8	genotyped	genotype	VERB
afs-90955	5	9	using	use	VERB
afs-90955	5	10	50240	50240	NUM
afs-90955	5	11	markers	marker	NOUN
afs-90955	5	12	.	.	PUNCT
afs-90955	6	1	total	total	ADJ
afs-90955	6	2	computing	computing	NOUN
afs-90955	6	3	time	time	NOUN
afs-90955	6	4	(	(	PUNCT
afs-90955	6	5	the	the	DET
afs-90955	6	6	product	product	NOUN
afs-90955	6	7	(	(	PUNCT
afs-90955	6	8	a22	a22	PROPN
afs-90955	6	9	)	)	PUNCT
afs-90955	6	10	-11	-11	PUNCT
afs-90955	6	11	)	)	PUNCT
afs-90955	6	12	was	be	AUX
afs-90955	6	13	53	53	NUM
afs-90955	6	14	min	min	NOUN
afs-90955	6	15	(	(	PUNCT
afs-90955	6	16	1.2	1.2	NUM
afs-90955	6	17	min	min	NOUN
afs-90955	6	18	)	)	PUNCT
afs-90955	6	19	by	by	ADP
afs-90955	6	20	iop	iop	PROPN
afs-90955	6	21	,	,	PUNCT
afs-90955	6	22	51	51	NUM
afs-90955	6	23	min	min	NOUN
afs-90955	6	24	(	(	PUNCT
afs-90955	6	25	0.3	0.3	NUM
afs-90955	6	26	min	min	NOUN
afs-90955	6	27	)	)	PUNCT
afs-90955	6	28	by	by	ADP
afs-90955	6	29	i	i	PRON
afs-90955	6	30	m	m	PROPN
afs-90955	6	31	,	,	PUNCT
afs-90955	6	32	and	and	CCONJ
afs-90955	6	33	56	56	NUM
afs-90955	6	34	min	min	NOUN
afs-90955	6	35	(	(	PUNCT
afs-90955	6	36	4.6	4.6	NUM
afs-90955	6	37	min	min	NOUN
afs-90955	6	38	)	)	PUNCT
afs-90955	6	39	by	by	ADP
afs-90955	6	40	chm	chm	PROPN
afs-90955	6	41	.	.	PUNCT
afs-90955	6	42	peak	peak	PROPN
afs-90955	6	43	computer	computer	NOUN
afs-90955	6	44	core	core	NOUN
afs-90955	6	45	memory	memory	NOUN
afs-90955	6	46	use	use	NOUN
afs-90955	6	47	was	be	AUX
afs-90955	6	48	0.67	0.67	NUM
afs-90955	6	49	gb	gb	ADP
afs-90955	6	50	by	by	ADP
afs-90955	6	51	iop	iop	PROPN
afs-90955	6	52	,	,	PUNCT
afs-90955	6	53	0.80	0.80	NUM
afs-90955	6	54	gb	gb	VERB
afs-90955	6	55	by	by	ADP
afs-90955	6	56	i	i	PROPN
afs-90955	6	57	m	m	PROPN
afs-90955	6	58	,	,	PUNCT
afs-90955	6	59	and	and	CCONJ
afs-90955	6	60	7.53	7.53	NUM
afs-90955	6	61	gb	gb	NOUN
afs-90955	6	62	by	by	ADP
afs-90955	6	63	chm	chm	NOUN
afs-90955	6	64	.	.	PUNCT
afs-90955	7	1	thus	thus	ADV
afs-90955	7	2	,	,	PUNCT
afs-90955	7	3	the	the	DET
afs-90955	7	4	iop	iop	NOUN
afs-90955	7	5	and	and	CCONJ
afs-90955	7	6	i	i	PRON
afs-90955	7	7	m	m	VERB
afs-90955	7	8	approaches	approach	NOUN
afs-90955	7	9	can	can	AUX
afs-90955	7	10	be	be	AUX
afs-90955	7	11	recommended	recommend	VERB
afs-90955	7	12	for	for	ADP
afs-90955	7	13	large	large	ADJ
afs-90955	7	14	data	datum	NOUN
afs-90955	7	15	sets	set	NOUN
afs-90955	7	16	because	because	SCONJ
afs-90955	7	17	of	of	ADP
afs-90955	7	18	their	their	PRON
afs-90955	7	19	low	low	ADJ
afs-90955	7	20	memory	memory	NOUN
afs-90955	7	21	use	use	NOUN
afs-90955	7	22	and	and	CCONJ
afs-90955	7	23	computing	computing	NOUN
afs-90955	7	24	time	time	NOUN
afs-90955	7	25	.	.	PUNCT
afs-90955	8	1	key	key	ADJ
afs-90955	8	2	words	word	NOUN
afs-90955	8	3	:	:	PUNCT
afs-90955	8	4	allele	allele	NOUN
afs-90955	8	5	frequency	frequency	NOUN
afs-90955	8	6	,	,	PUNCT
afs-90955	8	7	computer	computer	NOUN
afs-90955	8	8	software	software	NOUN
afs-90955	8	9	,	,	PUNCT
afs-90955	8	10	genomic	genomic	NOUN
afs-90955	8	11	evaluation	evaluation	NOUN
afs-90955	8	12	,	,	PUNCT
afs-90955	8	13	relationship	relationship	NOUN
afs-90955	8	14	matrix	matrix	NOUN
afs-90955	8	15	introduction	introduction	NOUN
afs-90955	8	16	base	base	NOUN
afs-90955	8	17	population	population	NOUN
afs-90955	8	18	allele	allele	NOUN
afs-90955	8	19	frequencies	frequency	NOUN
afs-90955	8	20	(	(	PUNCT
afs-90955	8	21	af	af	NOUN
afs-90955	8	22	)	)	PUNCT
afs-90955	8	23	are	be	AUX
afs-90955	8	24	recommended	recommend	VERB
afs-90955	8	25	to	to	PART
afs-90955	8	26	be	be	AUX
afs-90955	8	27	used	use	VERB
afs-90955	8	28	in	in	ADP
afs-90955	8	29	computation	computation	NOUN
afs-90955	8	30	of	of	ADP
afs-90955	8	31	the	the	DET
afs-90955	8	32	genomic	genomic	NOUN
afs-90955	8	33	relationship	relationship	NOUN
afs-90955	8	34	matrix	matrix	NOUN
afs-90955	8	35	used	use	VERB
afs-90955	8	36	in	in	ADP
afs-90955	8	37	the	the	DET
afs-90955	8	38	genomic	genomic	NOUN
afs-90955	8	39	evaluation	evaluation	NOUN
afs-90955	8	40	(	(	PUNCT
afs-90955	8	41	vanraden	vanraden	NOUN
afs-90955	8	42	2008	2008	NUM
afs-90955	8	43	)	)	PUNCT
afs-90955	8	44	and	and	CCONJ
afs-90955	8	45	estimation	estimation	NOUN
afs-90955	8	46	of	of	ADP
afs-90955	8	47	the	the	DET
afs-90955	8	48	genomic	genomic	ADJ
afs-90955	8	49	compliant	compliant	ADJ
afs-90955	8	50	relationship	relationship	NOUN
afs-90955	8	51	matrix	matrix	NOUN
afs-90955	8	52	among	among	ADP
afs-90955	8	53	metafounders	metafounder	NOUN
afs-90955	8	54	(	(	PUNCT
afs-90955	8	55	garcia	garcia	PROPN
afs-90955	8	56	-	-	PUNCT
afs-90955	8	57	baccino	baccino	PROPN
afs-90955	8	58	et	et	PROPN
afs-90955	8	59	al	al	PROPN
afs-90955	8	60	.	.	PROPN
afs-90955	8	61	2017	2017	NUM
afs-90955	8	62	)	)	PUNCT
afs-90955	8	63	.	.	PUNCT
afs-90955	9	1	for	for	ADP
afs-90955	9	2	example	example	NOUN
afs-90955	9	3	,	,	PUNCT
afs-90955	9	4	the	the	DET
afs-90955	9	5	single	single	ADJ
afs-90955	9	6	-	-	PUNCT
afs-90955	9	7	step	step	NOUN
afs-90955	9	8	gblup	gblup	NOUN
afs-90955	9	9	method	method	NOUN
afs-90955	9	10	assumes	assume	VERB
afs-90955	9	11	that	that	SCONJ
afs-90955	9	12	the	the	DET
afs-90955	9	13	pedigree	pedigree	ADJ
afs-90955	9	14	and	and	CCONJ
afs-90955	9	15	genomic	genomic	NOUN
afs-90955	9	16	based	base	VERB
afs-90955	9	17	relationship	relationship	NOUN
afs-90955	9	18	matrices	matrix	NOUN
afs-90955	9	19	have	have	VERB
afs-90955	9	20	the	the	DET
afs-90955	9	21	same	same	ADJ
afs-90955	9	22	scale	scale	NOUN
afs-90955	9	23	and	and	CCONJ
afs-90955	9	24	base	base	NOUN
afs-90955	9	25	population	population	NOUN
afs-90955	9	26	definition	definition	NOUN
afs-90955	9	27	(	(	PUNCT
afs-90955	9	28	christensen	christensen	PROPN
afs-90955	9	29	et	et	PROPN
afs-90955	9	30	al	al	PROPN
afs-90955	9	31	.	.	PROPN
afs-90955	9	32	2012	2012	NUM
afs-90955	9	33	,	,	PUNCT
afs-90955	9	34	mäntysaari	mäntysaari	PROPN
afs-90955	9	35	et	et	PROPN
afs-90955	9	36	al	al	PROPN
afs-90955	9	37	.	.	PROPN
afs-90955	9	38	2020	2020	NUM
afs-90955	9	39	)	)	PUNCT
afs-90955	9	40	which	which	PRON
afs-90955	9	41	may	may	AUX
afs-90955	9	42	be	be	AUX
afs-90955	9	43	achieved	achieve	VERB
afs-90955	9	44	by	by	ADP
afs-90955	9	45	using	use	VERB
afs-90955	9	46	base	base	ADJ
afs-90955	9	47	population	population	NOUN
afs-90955	9	48	af	af	PROPN
afs-90955	9	49	.	.	PUNCT
afs-90955	10	1	garcia	garcia	PROPN
afs-90955	10	2	baccino	baccino	PROPN
afs-90955	10	3	et	et	PROPN
afs-90955	10	4	al	al	PROPN
afs-90955	10	5	.	.	PROPN
afs-90955	11	1	(	(	PUNCT
afs-90955	11	2	2017	2017	NUM
afs-90955	11	3	)	)	PUNCT
afs-90955	11	4	reviewed	review	VERB
afs-90955	11	5	methods	method	NOUN
afs-90955	11	6	for	for	ADP
afs-90955	11	7	the	the	DET
afs-90955	11	8	estimation	estimation	NOUN
afs-90955	11	9	of	of	ADP
afs-90955	11	10	base	base	ADJ
afs-90955	11	11	population	population	NOUN
afs-90955	11	12	af	af	VERB
afs-90955	11	13	when	when	SCONJ
afs-90955	11	14	the	the	DET
afs-90955	11	15	pedigree	pedigree	NOUN
afs-90955	11	16	of	of	ADP
afs-90955	11	17	genotyped	genotype	VERB
afs-90955	11	18	animals	animal	NOUN
afs-90955	11	19	is	be	AUX
afs-90955	11	20	known	know	VERB
afs-90955	11	21	for	for	ADP
afs-90955	11	22	single	single	ADJ
afs-90955	11	23	and	and	CCONJ
afs-90955	11	24	multiple	multiple	ADJ
afs-90955	11	25	group	group	NOUN
afs-90955	11	26	populations	population	NOUN
afs-90955	11	27	.	.	PUNCT
afs-90955	12	1	in	in	ADP
afs-90955	12	2	two	two	NUM
afs-90955	12	3	of	of	ADP
afs-90955	12	4	the	the	DET
afs-90955	12	5	presented	present	VERB
afs-90955	12	6	three	three	NUM
afs-90955	12	7	methods	method	NOUN
afs-90955	12	8	,	,	PUNCT
afs-90955	12	9	i.e.	i.e.	X
afs-90955	12	10	,	,	PUNCT
afs-90955	12	11	generalized	generalized	ADJ
afs-90955	12	12	least	least	ADJ
afs-90955	12	13	squares	square	NOUN
afs-90955	12	14	(	(	PUNCT
afs-90955	12	15	gls	gls	PROPN
afs-90955	12	16	)	)	PUNCT
afs-90955	12	17	and	and	CCONJ
afs-90955	12	18	maximum	maximum	ADJ
afs-90955	12	19	likelihood	likelihood	NOUN
afs-90955	12	20	(	(	PUNCT
afs-90955	12	21	ml	ml	NOUN
afs-90955	12	22	)	)	PUNCT
afs-90955	12	23	,	,	PUNCT
afs-90955	12	24	computationally	computationally	ADV
afs-90955	12	25	the	the	DET
afs-90955	12	26	most	most	ADV
afs-90955	12	27	challenging	challenging	ADJ
afs-90955	12	28	step	step	NOUN
afs-90955	12	29	is	be	AUX
afs-90955	12	30	the	the	DET
afs-90955	12	31	product	product	NOUN
afs-90955	12	32	v	v	NOUN
afs-90955	12	33	=	=	SYM
afs-90955	12	34	(	(	PUNCT
afs-90955	12	35	a22	a22	PROPN
afs-90955	12	36	)	)	PUNCT
afs-90955	12	37	-1s	-1s	PROPN
afs-90955	12	38	where	where	SCONJ
afs-90955	12	39	vector	vector	NOUN
afs-90955	12	40	s	s	NOUN
afs-90955	12	41	is	be	AUX
afs-90955	12	42	a	a	DET
afs-90955	12	43	function	function	NOUN
afs-90955	12	44	of	of	ADP
afs-90955	12	45	marker	marker	NOUN
afs-90955	12	46	genotypes	genotype	NOUN
afs-90955	12	47	and	and	CCONJ
afs-90955	12	48	a22	a22	PROPN
afs-90955	12	49	is	be	AUX
afs-90955	12	50	the	the	DET
afs-90955	12	51	pedigree	pedigree	NOUN
afs-90955	12	52	based	base	VERB
afs-90955	12	53	relationship	relationship	NOUN
afs-90955	12	54	matrix	matrix	NOUN
afs-90955	12	55	between	between	ADP
afs-90955	12	56	the	the	DET
afs-90955	12	57	genotyped	genotype	VERB
afs-90955	12	58	animals	animal	NOUN
afs-90955	12	59	.	.	PUNCT
afs-90955	13	1	when	when	SCONJ
afs-90955	13	2	the	the	DET
afs-90955	13	3	number	number	NOUN
afs-90955	13	4	of	of	ADP
afs-90955	13	5	genotyped	genotype	VERB
afs-90955	13	6	animals	animal	NOUN
afs-90955	13	7	is	be	AUX
afs-90955	13	8	large	large	ADJ
afs-90955	13	9	,	,	PUNCT
afs-90955	13	10	the	the	DET
afs-90955	13	11	need	need	NOUN
afs-90955	13	12	to	to	PART
afs-90955	13	13	invert	invert	VERB
afs-90955	13	14	a	a	DET
afs-90955	13	15	large	large	ADJ
afs-90955	13	16	a22	a22	NOUN
afs-90955	13	17	may	may	AUX
afs-90955	13	18	make	make	VERB
afs-90955	13	19	the	the	DET
afs-90955	13	20	method	method	NOUN
afs-90955	13	21	computationally	computationally	ADV
afs-90955	13	22	unfeasible	unfeasible	ADJ
afs-90955	13	23	because	because	SCONJ
afs-90955	13	24	this	this	DET
afs-90955	13	25	matrix	matrix	NOUN
afs-90955	13	26	is	be	AUX
afs-90955	13	27	often	often	ADV
afs-90955	13	28	dense	dense	ADJ
afs-90955	13	29	.	.	PUNCT
afs-90955	14	1	an	an	DET
afs-90955	14	2	alternative	alternative	NOUN
afs-90955	14	3	to	to	ADP
afs-90955	14	4	the	the	DET
afs-90955	14	5	brute	brute	ADJ
afs-90955	14	6	force	force	NOUN
afs-90955	14	7	inversion	inversion	NOUN
afs-90955	14	8	of	of	ADP
afs-90955	14	9	a	a	DET
afs-90955	14	10	large	large	ADJ
afs-90955	14	11	a22	a22	NOUN
afs-90955	14	12	matrix	matrix	NOUN
afs-90955	14	13	is	be	AUX
afs-90955	14	14	to	to	PART
afs-90955	14	15	solve	solve	VERB
afs-90955	14	16	the	the	DET
afs-90955	14	17	vector	vector	NOUN
afs-90955	14	18	v	v	NOUN
afs-90955	14	19	in	in	ADP
afs-90955	14	20	linear	linear	ADJ
afs-90955	14	21	system	system	NOUN
afs-90955	14	22	of	of	ADP
afs-90955	14	23	equations	equation	NOUN
afs-90955	14	24	a22v	a22v	X
afs-90955	15	1	=	=	SYM
afs-90955	15	2	s	s	NOUN
afs-90955	15	3	,	,	PUNCT
afs-90955	15	4	e.g.	e.g.	ADV
afs-90955	15	5	,	,	PUNCT
afs-90955	15	6	by	by	ADP
afs-90955	15	7	an	an	DET
afs-90955	15	8	iterative	iterative	NOUN
afs-90955	15	9	method	method	NOUN
afs-90955	15	10	such	such	ADJ
afs-90955	15	11	as	as	ADP
afs-90955	15	12	preconditioned	precondition	VERB
afs-90955	15	13	conjugate	conjugate	ADJ
afs-90955	15	14	gradient	gradient	NOUN
afs-90955	15	15	(	(	PUNCT
afs-90955	15	16	pcg	pcg	PROPN
afs-90955	15	17	)	)	PUNCT
afs-90955	15	18	iteration	iteration	NOUN
afs-90955	15	19	.	.	PUNCT
afs-90955	16	1	however	however	ADV
afs-90955	16	2	,	,	PUNCT
afs-90955	16	3	when	when	SCONJ
afs-90955	16	4	the	the	DET
afs-90955	16	5	number	number	NOUN
afs-90955	16	6	of	of	ADP
afs-90955	16	7	genotyped	genotype	VERB
afs-90955	16	8	animals	animal	NOUN
afs-90955	16	9	is	be	AUX
afs-90955	16	10	large	large	ADJ
afs-90955	16	11	,	,	PUNCT
afs-90955	16	12	storing	store	VERB
afs-90955	16	13	and	and	CCONJ
afs-90955	16	14	using	use	VERB
afs-90955	16	15	the	the	DET
afs-90955	16	16	dense	dense	ADJ
afs-90955	16	17	a22	a22	NOUN
afs-90955	16	18	matrix	matrix	NOUN
afs-90955	16	19	will	will	AUX
afs-90955	16	20	slow	slow	VERB
afs-90955	16	21	down	down	ADP
afs-90955	16	22	the	the	DET
afs-90955	16	23	computations	computation	NOUN
afs-90955	16	24	considerably	considerably	ADV
afs-90955	16	25	.	.	PUNCT
afs-90955	17	1	thus	thus	ADV
afs-90955	17	2	,	,	PUNCT
afs-90955	17	3	solving	solve	VERB
afs-90955	17	4	by	by	ADP
afs-90955	17	5	an	an	DET
afs-90955	17	6	iterative	iterative	NOUN
afs-90955	17	7	method	method	NOUN
afs-90955	17	8	may	may	AUX
afs-90955	17	9	take	take	VERB
afs-90955	17	10	too	too	ADV
afs-90955	17	11	long	long	ADV
afs-90955	17	12	.	.	PUNCT
afs-90955	18	1	strandén	strandén	PROPN
afs-90955	18	2	et	et	PROPN
afs-90955	18	3	al	al	PROPN
afs-90955	18	4	.	.	PROPN
afs-90955	19	1	(	(	PUNCT
afs-90955	19	2	2017	2017	NUM
afs-90955	19	3	)	)	PUNCT
afs-90955	19	4	presented	present	VERB
afs-90955	19	5	an	an	DET
afs-90955	19	6	alternative	alternative	ADJ
afs-90955	19	7	computational	computational	ADJ
afs-90955	19	8	approach	approach	NOUN
afs-90955	19	9	for	for	ADP
afs-90955	19	10	the	the	DET
afs-90955	19	11	gls	gls	NOUN
afs-90955	19	12	method	method	NOUN
afs-90955	19	13	(	(	PUNCT
afs-90955	19	14	mcpeek	mcpeek	NOUN
afs-90955	19	15	et	et	PROPN
afs-90955	19	16	al	al	PROPN
afs-90955	19	17	.	.	PROPN
afs-90955	19	18	2006	2006	NUM
afs-90955	19	19	)	)	PUNCT
afs-90955	19	20	where	where	SCONJ
afs-90955	19	21	explicit	explicit	ADJ
afs-90955	19	22	calculation	calculation	NOUN
afs-90955	19	23	of	of	ADP
afs-90955	19	24	(	(	PUNCT
afs-90955	19	25	a22	a22	PROPN
afs-90955	19	26	)	)	PUNCT
afs-90955	19	27	-1	-1	PUNCT
afs-90955	19	28	is	be	AUX
afs-90955	19	29	avoided	avoid	VERB
afs-90955	19	30	.	.	PUNCT
afs-90955	20	1	they	they	PRON
afs-90955	20	2	used	use	VERB
afs-90955	20	3	equality	equality	NOUN
afs-90955	20	4	(	(	PUNCT
afs-90955	20	5	a22	a22	PROPN
afs-90955	20	6	)	)	PUNCT
afs-90955	20	7	-1s	-1s	PROPN
afs-90955	20	8	=	=	SYM
afs-90955	20	9	(	(	PUNCT
afs-90955	20	10	a22	a22	PROPN
afs-90955	20	11	–	–	PUNCT
afs-90955	20	12	a21(a11)-1a12)s	a21(a11)-1a12)s	PROPN
afs-90955	20	13	where	where	SCONJ
afs-90955	20	14	aij	aij	PROPN
afs-90955	20	15	,	,	PUNCT
afs-90955	20	16	i	i	PRON
afs-90955	20	17	,	,	PUNCT
afs-90955	20	18	j	j	PROPN
afs-90955	20	19	=	=	SYM
afs-90955	20	20	1,2,are	1,2,are	NUM
afs-90955	20	21	submatrices	submatrice	NOUN
afs-90955	20	22	of	of	ADP
afs-90955	20	23	a-1	a-1	PROPN
afs-90955	20	24	which	which	PRON
afs-90955	20	25	are	be	AUX
afs-90955	20	26	often	often	ADV
afs-90955	20	27	sparse	sparse	ADJ
afs-90955	20	28	,	,	PUNCT
afs-90955	20	29	and	and	CCONJ
afs-90955	20	30	numbers	number	NOUN
afs-90955	20	31	1	1	NUM
afs-90955	20	32	and	and	CCONJ
afs-90955	20	33	2	2	NUM
afs-90955	20	34	refer	refer	VERB
afs-90955	20	35	to	to	ADP
afs-90955	20	36	the	the	DET
afs-90955	20	37	non	non	ADJ
afs-90955	20	38	-	-	ADJ
afs-90955	20	39	genotyped	genotype	VERB
afs-90955	20	40	and	and	CCONJ
afs-90955	20	41	the	the	DET
afs-90955	20	42	genotyped	genotype	VERB
afs-90955	20	43	animals	animal	NOUN
afs-90955	20	44	,	,	PUNCT
afs-90955	20	45	respectively	respectively	ADV
afs-90955	20	46	.	.	PUNCT
afs-90955	21	1	product	product	NOUN
afs-90955	21	2	aijs	aijs	PROPN
afs-90955	21	3	can	can	AUX
afs-90955	21	4	be	be	AUX
afs-90955	21	5	calculated	calculate	VERB
afs-90955	21	6	either	either	CCONJ
afs-90955	21	7	using	use	VERB
afs-90955	21	8	pedigree	pedigree	ADJ
afs-90955	21	9	information	information	NOUN
afs-90955	21	10	without	without	ADP
afs-90955	21	11	making	make	VERB
afs-90955	21	12	matrix	matrix	NOUN
afs-90955	21	13	aij	aij	PROPN
afs-90955	21	14	(	(	PUNCT
afs-90955	21	15	henderson	henderson	PROPN
afs-90955	21	16	1976	1976	NUM
afs-90955	21	17	,	,	PUNCT
afs-90955	21	18	quaas	quaas	NOUN
afs-90955	21	19	1976	1976	NUM
afs-90955	21	20	)	)	PUNCT
afs-90955	21	21	or	or	CCONJ
afs-90955	21	22	after	after	SCONJ
afs-90955	21	23	aij	aij	PROPN
afs-90955	21	24	has	have	AUX
afs-90955	21	25	been	be	AUX
afs-90955	21	26	computed	compute	VERB
afs-90955	21	27	using	use	VERB
afs-90955	21	28	pedigree	pedigree	ADJ
afs-90955	21	29	information	information	NOUN
afs-90955	21	30	.	.	PUNCT
afs-90955	22	1	computationally	computationally	ADV
afs-90955	22	2	the	the	DET
afs-90955	22	3	most	most	ADV
afs-90955	22	4	challenging	challenging	ADJ
afs-90955	22	5	task	task	NOUN
afs-90955	22	6	is	be	AUX
afs-90955	22	7	the	the	DET
afs-90955	22	8	product	product	NOUN
afs-90955	22	9	(	(	PUNCT
afs-90955	22	10	a11)-1x	a11)-1x	NOUN
afs-90955	22	11	where	where	SCONJ
afs-90955	22	12	x	x	SYM
afs-90955	22	13	=	=	PUNCT
afs-90955	22	14	a12s	a12	NOUN
afs-90955	22	15	.	.	PUNCT
afs-90955	23	1	this	this	DET
afs-90955	23	2	product	product	NOUN
afs-90955	23	3	requires	require	VERB
afs-90955	23	4	using	use	VERB
afs-90955	23	5	either	either	CCONJ
afs-90955	23	6	an	an	DET
afs-90955	23	7	iterative	iterative	NOUN
afs-90955	23	8	or	or	CCONJ
afs-90955	23	9	a	a	DET
afs-90955	23	10	sparse	sparse	ADJ
afs-90955	23	11	matrix	matrix	NOUN
afs-90955	23	12	solver	solver	NOUN
afs-90955	23	13	(	(	PUNCT
afs-90955	23	14	strandén	strandén	PROPN
afs-90955	23	15	et	et	PROPN
afs-90955	23	16	al	al	PROPN
afs-90955	23	17	.	.	PROPN
afs-90955	23	18	2017	2017	NUM
afs-90955	23	19	)	)	PUNCT
afs-90955	23	20	.	.	PUNCT
afs-90955	24	1	aldridge	aldridge	PROPN
afs-90955	24	2	et	et	PROPN
afs-90955	24	3	al	al	PROPN
afs-90955	24	4	.	.	PROPN
afs-90955	25	1	(	(	PUNCT
afs-90955	25	2	2018	2018	NUM
afs-90955	25	3	)	)	PUNCT
afs-90955	25	4	compared	compare	VERB
afs-90955	25	5	two	two	NUM
afs-90955	25	6	approaches	approach	NOUN
afs-90955	25	7	to	to	PART
afs-90955	25	8	compute	compute	VERB
afs-90955	25	9	the	the	DET
afs-90955	25	10	gls	gls	NOUN
afs-90955	25	11	method	method	NOUN
afs-90955	25	12	estimates	estimate	NOUN
afs-90955	25	13	.	.	PUNCT
afs-90955	26	1	one	one	NUM
afs-90955	26	2	method	method	NOUN
afs-90955	26	3	used	use	VERB
afs-90955	26	4	the	the	DET
afs-90955	26	5	direct	direct	ADJ
afs-90955	26	6	inversion	inversion	NOUN
afs-90955	26	7	of	of	ADP
afs-90955	26	8	the	the	DET
afs-90955	26	9	a22	a22	PROPN
afs-90955	26	10	matrix	matrix	NOUN
afs-90955	26	11	approach	approach	NOUN
afs-90955	26	12	and	and	CCONJ
afs-90955	26	13	another	another	PRON
afs-90955	26	14	used	use	VERB
afs-90955	26	15	the	the	DET
afs-90955	26	16	sparse	sparse	ADJ
afs-90955	26	17	matrix	matrix	NOUN
afs-90955	26	18	solver	solver	NOUN
afs-90955	26	19	approach	approach	NOUN
afs-90955	26	20	as	as	ADP
afs-90955	26	21	in	in	ADP
afs-90955	26	22	strandén	strandén	PROPN
afs-90955	26	23	et	et	PROPN
afs-90955	26	24	al	al	PROPN
afs-90955	26	25	.	.	PROPN
afs-90955	27	1	(	(	PUNCT
afs-90955	27	2	2017	2017	NUM
afs-90955	27	3	)	)	PUNCT
afs-90955	27	4	.	.	PUNCT
afs-90955	28	1	aldridge	aldridge	PROPN
afs-90955	28	2	et	et	PROPN
afs-90955	28	3	al	al	PROPN
afs-90955	28	4	.	.	PROPN
afs-90955	29	1	(	(	PUNCT
afs-90955	29	2	2018	2018	NUM
afs-90955	29	3	)	)	PUNCT
afs-90955	29	4	estimated	estimate	VERB
afs-90955	29	5	base	base	NOUN
afs-90955	29	6	population	population	NOUN
afs-90955	29	7	af	af	VERB
afs-90955	29	8	for	for	ADP
afs-90955	29	9	1670	1670	NUM
afs-90955	29	10	markers	marker	NOUN
afs-90955	29	11	using	use	VERB
afs-90955	29	12	genotypes	genotype	NOUN
afs-90955	29	13	from	from	ADP
afs-90955	29	14	100	100	NUM
afs-90955	29	15	078	078	NUM
afs-90955	29	16	animals	animal	NOUN
afs-90955	29	17	.	.	PUNCT
afs-90955	30	1	according	accord	VERB
afs-90955	30	2	to	to	ADP
afs-90955	30	3	their	their	PRON
afs-90955	30	4	results	result	NOUN
afs-90955	30	5	,	,	PUNCT
afs-90955	30	6	the	the	DET
afs-90955	30	7	direct	direct	ADJ
afs-90955	30	8	a22	a22	NOUN
afs-90955	30	9	matrix	matrix	NOUN
afs-90955	30	10	inversion	inversion	NOUN
afs-90955	30	11	approach	approach	NOUN
afs-90955	30	12	took	take	VERB
afs-90955	30	13	more	more	ADJ
afs-90955	30	14	than	than	ADP
afs-90955	30	15	1	1	NUM
afs-90955	30	16	day	day	NOUN
afs-90955	30	17	but	but	CCONJ
afs-90955	30	18	the	the	DET
afs-90955	30	19	algorithm	algorithm	NOUN
afs-90955	30	20	using	use	VERB
afs-90955	30	21	sparse	sparse	ADJ
afs-90955	30	22	matrices	matrix	NOUN
afs-90955	30	23	took	take	VERB
afs-90955	30	24	about	about	ADV
afs-90955	30	25	49	49	NUM
afs-90955	30	26	seconds	second	NOUN
afs-90955	30	27	.	.	PUNCT
afs-90955	31	1	the	the	DET
afs-90955	31	2	direct	direct	ADJ
afs-90955	31	3	inversion	inversion	NOUN
afs-90955	31	4	approach	approach	NOUN
afs-90955	31	5	needed	need	VERB
afs-90955	31	6	118.5	118.5	NUM
afs-90955	31	7	gb	gb	NOUN
afs-90955	31	8	of	of	ADP
afs-90955	31	9	memory	memory	NOUN
afs-90955	31	10	,	,	PUNCT
afs-90955	31	11	but	but	CCONJ
afs-90955	31	12	the	the	DET
afs-90955	31	13	sparse	sparse	ADJ
afs-90955	31	14	matrix	matrix	NOUN
afs-90955	31	15	approach	approach	NOUN
afs-90955	31	16	needed	need	VERB
afs-90955	31	17	only	only	ADV
afs-90955	31	18	1.3	1.3	NUM
afs-90955	31	19	gb	gb	NOUN
afs-90955	31	20	of	of	ADP
afs-90955	31	21	memory	memory	NOUN
afs-90955	31	22	.	.	PUNCT
afs-90955	32	1	manuscript	manuscript	NOUN
afs-90955	32	2	received	receive	VERB
afs-90955	32	3	march	march	PROPN
afs-90955	32	4	2020	2020	NUM
afs-90955	32	5	agricultural	agricultural	ADJ
afs-90955	32	6	and	and	CCONJ
afs-90955	32	7	food	food	NOUN
afs-90955	32	8	science	science	PROPN
afs-90955	32	9	i.	i.	PROPN
afs-90955	32	10	strandén	strandén	PROPN
afs-90955	32	11	&	&	CCONJ
afs-90955	32	12	e.a	e.a	PROPN
afs-90955	32	13	.	.	PROPN
afs-90955	32	14	mäntysaari	mäntysaari	PROPN
afs-90955	32	15	(	(	PUNCT
afs-90955	32	16	2020	2020	NUM
afs-90955	32	17	)	)	PUNCT
afs-90955	32	18	29	29	NUM
afs-90955	32	19	:	:	PUNCT
afs-90955	32	20	166–176	166–176	NUM
afs-90955	32	21	167	167	NUM
afs-90955	32	22	strandén	strandén	PROPN
afs-90955	32	23	et	et	PROPN
afs-90955	32	24	al	al	PROPN
afs-90955	32	25	.	.	PROPN
afs-90955	33	1	(	(	PUNCT
afs-90955	33	2	2017	2017	NUM
afs-90955	33	3	)	)	PUNCT
afs-90955	33	4	used	use	VERB
afs-90955	33	5	the	the	DET
afs-90955	33	6	sparse	sparse	ADJ
afs-90955	33	7	matrix	matrix	NOUN
afs-90955	33	8	approach	approach	NOUN
afs-90955	33	9	in	in	ADP
afs-90955	33	10	the	the	DET
afs-90955	33	11	iterative	iterative	NOUN
afs-90955	33	12	pcg	pcg	PROPN
afs-90955	33	13	method	method	NOUN
afs-90955	33	14	to	to	PART
afs-90955	33	15	solve	solve	VERB
afs-90955	33	16	single	single	ADJ
afs-90955	33	17	-	-	PUNCT
afs-90955	33	18	step	step	NOUN
afs-90955	33	19	gblup	gblup	NOUN
afs-90955	33	20	(	(	PUNCT
afs-90955	33	21	aguilar	aguilar	PROPN
afs-90955	33	22	et	et	PROPN
afs-90955	33	23	al	al	PROPN
afs-90955	33	24	.	.	PROPN
afs-90955	33	25	2010	2010	NUM
afs-90955	33	26	,	,	PUNCT
afs-90955	33	27	christensen	christensen	PROPN
afs-90955	33	28	and	and	CCONJ
afs-90955	33	29	lund	lund	PROPN
afs-90955	33	30	2010	2010	NUM
afs-90955	33	31	)	)	PUNCT
afs-90955	33	32	where	where	SCONJ
afs-90955	33	33	the	the	DET
afs-90955	33	34	product	product	NOUN
afs-90955	33	35	(	(	PUNCT
afs-90955	33	36	a22	a22	PROPN
afs-90955	33	37	)	)	PUNCT
afs-90955	33	38	-1d	-1d	PROPN
afs-90955	33	39	was	be	AUX
afs-90955	33	40	calculated	calculate	VERB
afs-90955	33	41	in	in	ADP
afs-90955	33	42	every	every	DET
afs-90955	33	43	iteration	iteration	NOUN
afs-90955	33	44	of	of	ADP
afs-90955	33	45	the	the	DET
afs-90955	33	46	pcg	pcg	PROPN
afs-90955	33	47	algorithm	algorithm	NOUN
afs-90955	33	48	.	.	PUNCT
afs-90955	34	1	they	they	PRON
afs-90955	34	2	presented	present	VERB
afs-90955	34	3	and	and	CCONJ
afs-90955	34	4	tested	test	VERB
afs-90955	34	5	three	three	NUM
afs-90955	34	6	approaches	approach	NOUN
afs-90955	34	7	and	and	CCONJ
afs-90955	34	8	found	find	VERB
afs-90955	34	9	the	the	DET
afs-90955	34	10	sparse	sparse	ADJ
afs-90955	34	11	matrix	matrix	NOUN
afs-90955	34	12	solver	solver	NOUN
afs-90955	34	13	approach	approach	NOUN
afs-90955	34	14	to	to	PART
afs-90955	34	15	be	be	AUX
afs-90955	34	16	the	the	DET
afs-90955	34	17	fastest	fast	ADJ
afs-90955	34	18	(	(	PUNCT
afs-90955	34	19	strandén	strandén	PROPN
afs-90955	34	20	et	et	PROPN
afs-90955	34	21	al	al	PROPN
afs-90955	34	22	.	.	PROPN
afs-90955	34	23	2017	2017	NUM
afs-90955	34	24	)	)	PUNCT
afs-90955	34	25	.	.	PUNCT
afs-90955	35	1	in	in	ADP
afs-90955	35	2	single	single	ADJ
afs-90955	35	3	-	-	PUNCT
afs-90955	35	4	step	step	NOUN
afs-90955	35	5	gblup	gblup	NOUN
afs-90955	35	6	,	,	PUNCT
afs-90955	35	7	the	the	DET
afs-90955	35	8	product	product	NOUN
afs-90955	35	9	(	(	PUNCT
afs-90955	35	10	a22	a22	PROPN
afs-90955	35	11	)	)	PUNCT
afs-90955	35	12	-1d	-1d	PROPN
afs-90955	35	13	needs	need	VERB
afs-90955	35	14	to	to	PART
afs-90955	35	15	be	be	AUX
afs-90955	35	16	computed	compute	VERB
afs-90955	35	17	every	every	DET
afs-90955	35	18	iteration	iteration	NOUN
afs-90955	35	19	using	use	VERB
afs-90955	35	20	a	a	DET
afs-90955	35	21	different	different	ADJ
afs-90955	35	22	d	d	NOUN
afs-90955	35	23	vector	vector	NOUN
afs-90955	35	24	.	.	PUNCT
afs-90955	36	1	note	note	VERB
afs-90955	36	2	that	that	SCONJ
afs-90955	36	3	the	the	DET
afs-90955	36	4	product	product	NOUN
afs-90955	36	5	(	(	PUNCT
afs-90955	36	6	a22	a22	PROPN
afs-90955	36	7	)	)	PUNCT
afs-90955	36	8	-1d	-1d	PROPN
afs-90955	36	9	above	above	ADV
afs-90955	36	10	is	be	AUX
afs-90955	36	11	due	due	ADJ
afs-90955	36	12	to	to	ADP
afs-90955	36	13	the	the	DET
afs-90955	36	14	mixed	mixed	ADJ
afs-90955	36	15	model	model	NOUN
afs-90955	36	16	equations	equation	NOUN
afs-90955	36	17	of	of	ADP
afs-90955	36	18	ssgblup	ssgblup	NOUN
afs-90955	36	19	,	,	PUNCT
afs-90955	36	20	and	and	CCONJ
afs-90955	36	21	not	not	PART
afs-90955	36	22	due	due	ADP
afs-90955	36	23	to	to	ADP
afs-90955	36	24	pcg	pcg	PROPN
afs-90955	36	25	iterations	iteration	NOUN
afs-90955	36	26	used	use	VERB
afs-90955	36	27	in	in	ADP
afs-90955	36	28	the	the	DET
afs-90955	36	29	gls	gls	NOUN
afs-90955	36	30	method	method	NOUN
afs-90955	36	31	for	for	ADP
afs-90955	36	32	the	the	DET
afs-90955	36	33	base	base	ADJ
afs-90955	36	34	population	population	NOUN
afs-90955	36	35	af	af	PROPN
afs-90955	36	36	estimation	estimation	NOUN
afs-90955	36	37	in	in	ADP
afs-90955	36	38	the	the	DET
afs-90955	36	39	current	current	ADJ
afs-90955	36	40	study	study	NOUN
afs-90955	36	41	.	.	PUNCT
afs-90955	37	1	in	in	ADP
afs-90955	37	2	the	the	DET
afs-90955	37	3	gls	gls	NOUN
afs-90955	37	4	method	method	NOUN
afs-90955	37	5	,	,	PUNCT
afs-90955	37	6	however	however	ADV
afs-90955	37	7	,	,	PUNCT
afs-90955	37	8	the	the	DET
afs-90955	37	9	product	product	NOUN
afs-90955	37	10	v	v	NOUN
afs-90955	37	11	=	=	SYM
afs-90955	37	12	(	(	PUNCT
afs-90955	37	13	a22	a22	PROPN
afs-90955	37	14	)	)	PUNCT
afs-90955	37	15	-1s	-1s	PROPN
afs-90955	37	16	needs	need	VERB
afs-90955	37	17	to	to	PART
afs-90955	37	18	be	be	AUX
afs-90955	37	19	computed	compute	VERB
afs-90955	37	20	only	only	ADV
afs-90955	37	21	once	once	ADV
afs-90955	37	22	and	and	CCONJ
afs-90955	37	23	the	the	DET
afs-90955	37	24	same	same	ADJ
afs-90955	37	25	v	v	NOUN
afs-90955	37	26	vector	vector	NOUN
afs-90955	37	27	is	be	AUX
afs-90955	37	28	used	use	VERB
afs-90955	37	29	in	in	ADP
afs-90955	37	30	every	every	DET
afs-90955	37	31	af	af	NOUN
afs-90955	37	32	calculation	calculation	NOUN
afs-90955	37	33	.	.	PUNCT
afs-90955	38	1	thus	thus	ADV
afs-90955	38	2	,	,	PUNCT
afs-90955	38	3	when	when	SCONJ
afs-90955	38	4	the	the	DET
afs-90955	38	5	number	number	NOUN
afs-90955	38	6	of	of	ADP
afs-90955	38	7	af	af	PROPN
afs-90955	38	8	to	to	PART
afs-90955	38	9	be	be	AUX
afs-90955	38	10	estimated	estimate	VERB
afs-90955	38	11	increases	increase	NOUN
afs-90955	38	12	,	,	PUNCT
afs-90955	38	13	time	time	NOUN
afs-90955	38	14	to	to	PART
afs-90955	38	15	compute	compute	VERB
afs-90955	38	16	v	v	NOUN
afs-90955	38	17	=	=	SYM
afs-90955	38	18	(	(	PUNCT
afs-90955	38	19	a22	a22	PROPN
afs-90955	38	20	)	)	PUNCT
afs-90955	38	21	-1s	-1s	PROPN
afs-90955	38	22	can	can	AUX
afs-90955	38	23	become	become	VERB
afs-90955	38	24	less	less	ADV
afs-90955	38	25	significant	significant	ADJ
afs-90955	38	26	.	.	PUNCT
afs-90955	39	1	because	because	SCONJ
afs-90955	39	2	the	the	DET
afs-90955	39	3	two	two	NUM
afs-90955	39	4	other	other	ADJ
afs-90955	39	5	approaches	approach	NOUN
afs-90955	39	6	,	,	PUNCT
afs-90955	39	7	named	name	VERB
afs-90955	39	8	iop	iop	NOUN
afs-90955	39	9	and	and	CCONJ
afs-90955	39	10	i	i	PRON
afs-90955	39	11	m	m	VERB
afs-90955	39	12	(	(	PUNCT
afs-90955	39	13	see	see	VERB
afs-90955	39	14	“	"	PUNCT
afs-90955	39	15	solving	solve	VERB
afs-90955	39	16	approaches	approach	NOUN
afs-90955	39	17	in	in	ADP
afs-90955	39	18	bpop	bpop	NOUN
afs-90955	39	19	”	"	PUNCT
afs-90955	39	20	in	in	ADP
afs-90955	39	21	material	material	NOUN
afs-90955	39	22	and	and	CCONJ
afs-90955	39	23	methods	method	NOUN
afs-90955	39	24	)	)	PUNCT
afs-90955	39	25	in	in	ADP
afs-90955	39	26	strandén	strandén	PROPN
afs-90955	39	27	et	et	PROPN
afs-90955	39	28	al	al	PROPN
afs-90955	39	29	.	.	PROPN
afs-90955	40	1	(	(	PUNCT
afs-90955	40	2	2017	2017	NUM
afs-90955	40	3	)	)	PUNCT
afs-90955	40	4	were	be	AUX
afs-90955	40	5	computationally	computationally	ADV
afs-90955	40	6	simpler	simple	ADJ
afs-90955	40	7	than	than	ADP
afs-90955	40	8	the	the	DET
afs-90955	40	9	sparse	sparse	ADJ
afs-90955	40	10	matrix	matrix	NOUN
afs-90955	40	11	solver	solver	NOUN
afs-90955	40	12	approach	approach	NOUN
afs-90955	40	13	called	call	VERB
afs-90955	40	14	chm	chm	NOUN
afs-90955	40	15	,	,	PUNCT
afs-90955	40	16	and	and	CCONJ
afs-90955	40	17	needed	need	VERB
afs-90955	40	18	less	less	ADJ
afs-90955	40	19	computing	computing	NOUN
afs-90955	40	20	memory	memory	NOUN
afs-90955	40	21	,	,	PUNCT
afs-90955	40	22	the	the	DET
afs-90955	40	23	simpler	simple	ADJ
afs-90955	40	24	approaches	approach	NOUN
afs-90955	40	25	may	may	AUX
afs-90955	40	26	be	be	AUX
afs-90955	40	27	better	well	ADJ
afs-90955	40	28	in	in	ADP
afs-90955	40	29	af	af	PROPN
afs-90955	40	30	estimation	estimation	NOUN
afs-90955	40	31	for	for	ADP
afs-90955	40	32	large	large	ADJ
afs-90955	40	33	data	datum	NOUN
afs-90955	40	34	sets	set	NOUN
afs-90955	40	35	having	have	VERB
afs-90955	40	36	millions	million	NOUN
afs-90955	40	37	of	of	ADP
afs-90955	40	38	genotyped	genotype	VERB
afs-90955	40	39	animals	animal	NOUN
afs-90955	40	40	.	.	PUNCT
afs-90955	41	1	in	in	ADP
afs-90955	41	2	this	this	DET
afs-90955	41	3	study	study	NOUN
afs-90955	41	4	,	,	PUNCT
afs-90955	41	5	we	we	PRON
afs-90955	41	6	describe	describe	VERB
afs-90955	41	7	bpop	bpop	NOUN
afs-90955	41	8	program	program	NOUN
afs-90955	41	9	for	for	ADP
afs-90955	41	10	estimation	estimation	NOUN
afs-90955	41	11	of	of	ADP
afs-90955	41	12	base	base	ADJ
afs-90955	41	13	population	population	NOUN
afs-90955	41	14	af	af	VERB
afs-90955	41	15	using	use	VERB
afs-90955	41	16	the	the	DET
afs-90955	41	17	gls	gls	ADJ
afs-90955	41	18	method	method	NOUN
afs-90955	41	19	.	.	PUNCT
afs-90955	42	1	we	we	PRON
afs-90955	42	2	consider	consider	VERB
afs-90955	42	3	one	one	NUM
afs-90955	42	4	and	and	CCONJ
afs-90955	42	5	multiple	multiple	ADJ
afs-90955	42	6	group	group	NOUN
afs-90955	42	7	populations	population	NOUN
afs-90955	42	8	in	in	ADP
afs-90955	42	9	af	af	PROPN
afs-90955	42	10	estimation	estimation	NOUN
afs-90955	42	11	.	.	PUNCT
afs-90955	43	1	we	we	PRON
afs-90955	43	2	implement	implement	VERB
afs-90955	43	3	and	and	CCONJ
afs-90955	43	4	compare	compare	VERB
afs-90955	43	5	the	the	DET
afs-90955	43	6	three	three	NUM
afs-90955	43	7	algorithms	algorithm	NOUN
afs-90955	43	8	,	,	PUNCT
afs-90955	43	9	called	call	VERB
afs-90955	43	10	iop	iop	PROPN
afs-90955	43	11	,	,	PUNCT
afs-90955	43	12	i	i	PRON
afs-90955	43	13	m	m	VERB
afs-90955	43	14	and	and	CCONJ
afs-90955	43	15	chm	chm	NOUN
afs-90955	43	16	,	,	PUNCT
afs-90955	43	17	presented	present	VERB
afs-90955	43	18	in	in	ADP
afs-90955	43	19	strandén	strandén	PROPN
afs-90955	43	20	et	et	PROPN
afs-90955	43	21	al	al	PROPN
afs-90955	43	22	.	.	PROPN
afs-90955	44	1	(	(	PUNCT
afs-90955	44	2	2017	2017	NUM
afs-90955	44	3	)	)	PUNCT
afs-90955	44	4	.	.	PUNCT
afs-90955	45	1	we	we	PRON
afs-90955	45	2	use	use	VERB
afs-90955	45	3	a	a	DET
afs-90955	45	4	large	large	ADJ
afs-90955	45	5	genomic	genomic	NOUN
afs-90955	45	6	data	datum	NOUN
afs-90955	45	7	from	from	ADP
afs-90955	45	8	cattle	cattle	NOUN
afs-90955	45	9	to	to	PART
afs-90955	45	10	illustrate	illustrate	VERB
afs-90955	45	11	performance	performance	NOUN
afs-90955	45	12	of	of	ADP
afs-90955	45	13	the	the	DET
afs-90955	45	14	developed	develop	VERB
afs-90955	45	15	approaches	approach	NOUN
afs-90955	45	16	.	.	PUNCT
afs-90955	46	1	material	material	NOUN
afs-90955	46	2	and	and	CCONJ
afs-90955	46	3	methods	method	NOUN
afs-90955	46	4	base	base	NOUN
afs-90955	46	5	population	population	NOUN
afs-90955	46	6	allele	allele	PROPN
afs-90955	46	7	frequency	frequency	NOUN
afs-90955	46	8	estimation	estimation	NOUN
afs-90955	46	9	base	base	NOUN
afs-90955	46	10	population	population	NOUN
afs-90955	46	11	af	af	VERB
afs-90955	46	12	in	in	ADP
afs-90955	46	13	a	a	DET
afs-90955	46	14	single	single	ADJ
afs-90955	46	15	population	population	NOUN
afs-90955	46	16	can	can	AUX
afs-90955	46	17	be	be	AUX
afs-90955	46	18	estimated	estimate	VERB
afs-90955	46	19	using	use	VERB
afs-90955	46	20	the	the	DET
afs-90955	46	21	gls	gls	ADJ
afs-90955	46	22	model	model	NOUN
afs-90955	46	23	in	in	ADP
afs-90955	46	24	mcpeek	mcpeek	NOUN
afs-90955	46	25	et	et	PROPN
afs-90955	46	26	al	al	PROPN
afs-90955	46	27	.	.	PROPN
afs-90955	47	1	(	(	PUNCT
afs-90955	47	2	2004	2004	NUM
afs-90955	47	3	)	)	PUNCT
afs-90955	47	4	.	.	PUNCT
afs-90955	48	1	let	let	VERB
afs-90955	48	2	m	m	PRON
afs-90955	48	3	be	be	AUX
afs-90955	48	4	an	an	DET
afs-90955	48	5	n	n	NOUN
afs-90955	48	6	by	by	ADP
afs-90955	48	7	m	m	PROPN
afs-90955	48	8	genotype	genotype	NOUN
afs-90955	48	9	matrix	matrix	NOUN
afs-90955	48	10	for	for	ADP
afs-90955	48	11	n	n	DET
afs-90955	48	12	individuals	individual	NOUN
afs-90955	48	13	and	and	CCONJ
afs-90955	48	14	m	m	NOUN
afs-90955	48	15	snp	snp	ADJ
afs-90955	48	16	(	(	PUNCT
afs-90955	48	17	single	single	ADJ
afs-90955	48	18	-	-	PUNCT
afs-90955	48	19	nucleotide	nucleotide	NOUN
afs-90955	48	20	polymorphism	polymorphism	NOUN
afs-90955	48	21	)	)	PUNCT
afs-90955	48	22	markers	marker	NOUN
afs-90955	48	23	.	.	PUNCT
afs-90955	49	1	genotype	genotype	NOUN
afs-90955	49	2	is	be	AUX
afs-90955	49	3	coded	code	VERB
afs-90955	49	4	0	0	NUM
afs-90955	49	5	for	for	ADP
afs-90955	49	6	homozygote	homozygote	NOUN
afs-90955	49	7	aa	aa	NOUN
afs-90955	49	8	,	,	PUNCT
afs-90955	49	9	1	1	NUM
afs-90955	49	10	for	for	ADP
afs-90955	49	11	the	the	DET
afs-90955	49	12	heterozygote	heterozygote	PROPN
afs-90955	49	13	ab	ab	PROPN
afs-90955	49	14	,	,	PUNCT
afs-90955	49	15	and	and	CCONJ
afs-90955	49	16	2	2	NUM
afs-90955	49	17	for	for	ADP
afs-90955	49	18	the	the	DET
afs-90955	49	19	homozygote	homozygote	NOUN
afs-90955	49	20	bb	bb	NOUN
afs-90955	49	21	.	.	PUNCT
afs-90955	50	1	for	for	ADP
afs-90955	50	2	each	each	DET
afs-90955	50	3	marker	marker	NOUN
afs-90955	50	4	i	i	PRON
afs-90955	50	5	,	,	PUNCT
afs-90955	50	6	the	the	DET
afs-90955	50	7	approach	approach	NOUN
afs-90955	50	8	uses	use	VERB
afs-90955	50	9	a	a	DET
afs-90955	50	10	gls	gls	ADJ
afs-90955	50	11	model	model	NOUN
afs-90955	50	12	where	where	SCONJ
afs-90955	50	13	the	the	DET
afs-90955	50	14	only	only	ADJ
afs-90955	50	15	fixed	fix	VERB
afs-90955	50	16	effect	effect	NOUN
afs-90955	50	17	is	be	AUX
afs-90955	50	18	the	the	DET
afs-90955	50	19	unknown	unknown	ADJ
afs-90955	50	20	general	general	ADJ
afs-90955	50	21	mean	mean	VERB
afs-90955	50	22	µi	µi	PROPN
afs-90955	50	23	:	:	PUNCT
afs-90955	50	24	where	where	SCONJ
afs-90955	50	25	mi	mi	PROPN
afs-90955	50	26	is	be	AUX
afs-90955	50	27	marker	marker	NOUN
afs-90955	50	28	genotype	genotype	NOUN
afs-90955	50	29	column	column	NOUN
afs-90955	50	30	i	i	PRON
afs-90955	50	31	in	in	ADP
afs-90955	50	32	m	m	PROPN
afs-90955	50	33	,	,	PUNCT
afs-90955	50	34	i	i	PRON
afs-90955	50	35	=	=	NOUN
afs-90955	50	36	1,	1,	NUM
afs-90955	50	37	...	...	SYM
afs-90955	50	38	m	m	VERB
afs-90955	50	39	,	,	PUNCT
afs-90955	50	40	e~	e~	PROPN
afs-90955	50	41	(	(	PUNCT
afs-90955	50	42	0	0	NUM
afs-90955	50	43	,	,	PUNCT
afs-90955	50	44	a22σ	a22σ	ADP
afs-90955	50	45	2	2	NUM
afs-90955	50	46	)	)	PUNCT
afs-90955	50	47	,	,	PUNCT
afs-90955	50	48	a22	a22	PROPN
afs-90955	50	49	is	be	AUX
afs-90955	50	50	pedigree	pedigree	ADJ
afs-90955	50	51	relationship	relationship	NOUN
afs-90955	50	52	matrix	matrix	NOUN
afs-90955	50	53	of	of	ADP
afs-90955	50	54	the	the	DET
afs-90955	50	55	genotyped	genotype	VERB
afs-90955	50	56	animals	animal	NOUN
afs-90955	50	57	,	,	PUNCT
afs-90955	50	58	and	and	CCONJ
afs-90955	50	59	σ2	σ2	NOUN
afs-90955	50	60	is	be	AUX
afs-90955	50	61	common	common	ADJ
afs-90955	50	62	variance	variance	NOUN
afs-90955	50	63	.	.	PUNCT
afs-90955	51	1	the	the	DET
afs-90955	51	2	variance	variance	NOUN
afs-90955	51	3	of	of	ADP
afs-90955	51	4	gene	gene	NOUN
afs-90955	51	5	content	content	NOUN
afs-90955	51	6	σ2	σ2	PROPN
afs-90955	51	7	is	be	AUX
afs-90955	51	8	assumed	assume	VERB
afs-90955	51	9	to	to	PART
afs-90955	51	10	be	be	AUX
afs-90955	51	11	the	the	DET
afs-90955	51	12	same	same	ADJ
afs-90955	51	13	for	for	ADP
afs-90955	51	14	all	all	DET
afs-90955	51	15	genotypes	genotype	NOUN
afs-90955	51	16	and	and	CCONJ
afs-90955	51	17	need	need	AUX
afs-90955	51	18	not	not	PART
afs-90955	51	19	be	be	AUX
afs-90955	51	20	known	know	VERB
afs-90955	51	21	(	(	PUNCT
afs-90955	51	22	e.g.	e.g.	ADV
afs-90955	51	23	garcia	garcia	PROPN
afs-90955	51	24	-	-	PUNCT
afs-90955	51	25	baccino	baccino	PROPN
afs-90955	51	26	et	et	PROPN
afs-90955	51	27	al	al	PROPN
afs-90955	51	28	.	.	PROPN
afs-90955	51	29	2017	2017	NUM
afs-90955	51	30	)	)	PUNCT
afs-90955	51	31	.	.	PUNCT
afs-90955	52	1	solving	solve	VERB
afs-90955	52	2	this	this	DET
afs-90955	52	3	gls	gls	ADJ
afs-90955	52	4	model	model	NOUN
afs-90955	52	5	gives	give	VERB
afs-90955	52	6	estimator	estimator	NOUN
afs-90955	52	7	[	[	X
afs-90955	52	8	1	1	NUM
afs-90955	52	9	]	]	PUNCT
afs-90955	52	10	base	base	NOUN
afs-90955	52	11	population	population	NOUN
afs-90955	52	12	af	af	PROPN
afs-90955	52	13	is	be	AUX
afs-90955	52	14	half	half	NOUN
afs-90955	52	15	of	of	ADP
afs-90955	52	16	this	this	PRON
afs-90955	52	17	,	,	PUNCT
afs-90955	52	18	i.e.	i.e.	X
afs-90955	52	19	,	,	PUNCT
afs-90955	52	20	this	this	DET
afs-90955	52	21	approach	approach	NOUN
afs-90955	52	22	can	can	AUX
afs-90955	52	23	be	be	AUX
afs-90955	52	24	generalized	generalize	VERB
afs-90955	52	25	for	for	ADP
afs-90955	52	26	an	an	DET
afs-90955	52	27	admixed	admix	VERB
afs-90955	52	28	population	population	NOUN
afs-90955	52	29	using	use	VERB
afs-90955	52	30	a	a	DET
afs-90955	52	31	genetic	genetic	ADJ
afs-90955	52	32	groups	group	NOUN
afs-90955	52	33	model	model	VERB
afs-90955	52	34	having	have	VERB
afs-90955	52	35	r	r	NOUN
afs-90955	52	36	groups	group	NOUN
afs-90955	52	37	(	(	PUNCT
afs-90955	52	38	garcia	garcia	PROPN
afs-90955	52	39	-	-	PUNCT
afs-90955	52	40	baccino	baccino	PROPN
afs-90955	52	41	et	et	PROPN
afs-90955	52	42	al	al	PROPN
afs-90955	52	43	.	.	PROPN
afs-90955	52	44	2017	2017	NUM
afs-90955	52	45	)	)	PUNCT
afs-90955	52	46	.	.	PUNCT
afs-90955	53	1	let	let	VERB
afs-90955	53	2	q	q	PRON
afs-90955	53	3	be	be	AUX
afs-90955	53	4	an	an	DET
afs-90955	53	5	n	n	NOUN
afs-90955	53	6	by	by	ADP
afs-90955	53	7	r	r	NOUN
afs-90955	53	8	matrix	matrix	NOUN
afs-90955	53	9	of	of	ADP
afs-90955	53	10	fractions	fraction	NOUN
afs-90955	53	11	of	of	ADP
afs-90955	53	12	genetic	genetic	ADJ
afs-90955	53	13	groups	group	NOUN
afs-90955	53	14	represented	represent	VERB
afs-90955	53	15	in	in	ADP
afs-90955	53	16	individuals	individual	NOUN
afs-90955	53	17	where	where	SCONJ
afs-90955	53	18	each	each	DET
afs-90955	53	19	row	row	NOUN
afs-90955	53	20	sums	sum	VERB
afs-90955	53	21	to	to	ADP
afs-90955	53	22	one	one	NUM
afs-90955	53	23	.	.	PUNCT
afs-90955	54	1	the	the	DET
afs-90955	54	2	q	q	NOUN
afs-90955	54	3	matrix	matrix	NOUN
afs-90955	54	4	can	can	AUX
afs-90955	54	5	be	be	AUX
afs-90955	54	6	calculated	calculate	VERB
afs-90955	54	7	using	use	VERB
afs-90955	54	8	pedigree	pedigree	ADJ
afs-90955	54	9	information	information	NOUN
afs-90955	54	10	where	where	SCONJ
afs-90955	54	11	offspring	offspring	NOUN
afs-90955	54	12	group	group	NOUN
afs-90955	54	13	proportions	proportion	NOUN
afs-90955	54	14	are	be	AUX
afs-90955	54	15	calculated	calculate	VERB
afs-90955	54	16	as	as	ADP
afs-90955	54	17	mean	mean	NOUN
afs-90955	54	18	of	of	ADP
afs-90955	54	19	the	the	DET
afs-90955	54	20	parent	parent	NOUN
afs-90955	54	21	group	group	NOUN
afs-90955	54	22	proportions	proportion	NOUN
afs-90955	54	23	and	and	CCONJ
afs-90955	54	24	unknown	unknown	ADJ
afs-90955	54	25	parent	parent	NOUN
afs-90955	54	26	is	be	AUX
afs-90955	54	27	assigned	assign	VERB
afs-90955	54	28	to	to	ADP
afs-90955	54	29	a	a	DET
afs-90955	54	30	group	group	NOUN
afs-90955	54	31	.	.	PUNCT
afs-90955	55	1	the	the	DET
afs-90955	55	2	gls	gls	PROPN
afs-90955	55	3	model	model	NOUN
afs-90955	55	4	can	can	AUX
afs-90955	55	5	be	be	AUX
afs-90955	55	6	presented	present	VERB
afs-90955	55	7	as	as	ADP
afs-90955	55	8	where	where	SCONJ
afs-90955	55	9	µi	µi	PROPN
afs-90955	55	10	is	be	AUX
afs-90955	55	11	an	an	DET
afs-90955	55	12	r	r	NOUN
afs-90955	55	13	by	by	ADP
afs-90955	55	14	1	1	NUM
afs-90955	55	15	vector	vector	NOUN
afs-90955	55	16	of	of	ADP
afs-90955	55	17	unknown	unknown	ADJ
afs-90955	55	18	general	general	ADJ
afs-90955	55	19	means	mean	NOUN
afs-90955	55	20	of	of	ADP
afs-90955	55	21	the	the	DET
afs-90955	55	22	groups	group	NOUN
afs-90955	55	23	.	.	PUNCT
afs-90955	56	1	note	note	VERB
afs-90955	56	2	that	that	SCONJ
afs-90955	56	3	this	this	DET
afs-90955	56	4	gls	gls	ADJ
afs-90955	56	5	model	model	NOUN
afs-90955	56	6	assumes	assume	VERB
afs-90955	56	7	that	that	SCONJ
afs-90955	56	8	the	the	DET
afs-90955	56	9	variance	variance	NOUN
afs-90955	56	10	of	of	ADP
afs-90955	56	11	gene	gene	NOUN
afs-90955	56	12	content	content	NOUN
afs-90955	56	13	is	be	AUX
afs-90955	56	14	the	the	DET
afs-90955	56	15	same	same	ADJ
afs-90955	56	16	in	in	ADP
afs-90955	56	17	all	all	DET
afs-90955	56	18	groups	group	NOUN
afs-90955	56	19	(	(	PUNCT
afs-90955	56	20	garcia	garcia	PROPN
afs-90955	56	21	-	-	PUNCT
afs-90955	56	22	baccino	baccino	PROPN
afs-90955	56	23	et	et	PROPN
afs-90955	56	24	al	al	PROPN
afs-90955	56	25	.	.	PROPN
afs-90955	56	26	2017	2017	NUM
afs-90955	56	27	)	)	PUNCT
afs-90955	56	28	.	.	PUNCT
afs-90955	57	1	estimator	estimator	NOUN
afs-90955	57	2	to	to	ADP
afs-90955	57	3	the	the	DET
afs-90955	57	4	base	base	ADJ
afs-90955	57	5	population	population	NOUN
afs-90955	57	6	af	af	X
afs-90955	57	7	of	of	ADP
afs-90955	57	8	the	the	DET
afs-90955	57	9	groups	group	NOUN
afs-90955	57	10	for	for	ADP
afs-90955	57	11	marker	marker	NOUN
afs-90955	57	12	i	i	PRON
afs-90955	57	13	are	be	AUX
afs-90955	57	14	solutions	solution	NOUN
afs-90955	57	15	[	[	X
afs-90955	57	16	2	2	NUM
afs-90955	57	17	]	]	PUNCT
afs-90955	57	18	which	which	PRON
afs-90955	57	19	is	be	AUX
afs-90955	57	20	an	an	DET
afs-90955	57	21	r	r	NOUN
afs-90955	57	22	by	by	ADP
afs-90955	57	23	1	1	NUM
afs-90955	57	24	vector	vector	NOUN
afs-90955	57	25	.	.	PUNCT
afs-90955	58	1	in	in	ADP
afs-90955	58	2	some	some	DET
afs-90955	58	3	cases	case	NOUN
afs-90955	58	4	,	,	PUNCT
afs-90955	58	5	it	it	PRON
afs-90955	58	6	is	be	AUX
afs-90955	58	7	useful	useful	ADJ
afs-90955	58	8	to	to	PART
afs-90955	58	9	estimate	estimate	VERB
afs-90955	58	10	the	the	DET
afs-90955	58	11	af	af	NOUN
afs-90955	58	12	using	use	VERB
afs-90955	58	13	the	the	DET
afs-90955	58	14	observed	observed	ADJ
afs-90955	58	15	genotypes	genotype	NOUN
afs-90955	58	16	,	,	PUNCT
afs-90955	58	17	i.e.	i.e.	X
afs-90955	58	18	,	,	PUNCT
afs-90955	58	19	ignore	ignore	VERB
afs-90955	58	20	the	the	DET
afs-90955	58	21	pedigree	pedigree	ADJ
afs-90955	58	22	structure	structure	NOUN
afs-90955	58	23	.	.	PUNCT
afs-90955	59	1	this	this	PRON
afs-90955	59	2	can	can	AUX
afs-90955	59	3	be	be	AUX
afs-90955	59	4	done	do	VERB
afs-90955	59	5	using	use	VERB
afs-90955	59	6	simplified	simplified	ADJ
afs-90955	59	7	equations	equation	NOUN
afs-90955	59	8	:	:	PUNCT
afs-90955	59	9	and	and	CCONJ
afs-90955	59	10	.	.	PUNCT
afs-90955	60	1	we	we	PRON
afs-90955	60	2	call	call	VERB
afs-90955	60	3	these	these	DET
afs-90955	60	4	least	least	ADJ
afs-90955	60	5	squares	square	NOUN
afs-90955	60	6	(	(	PUNCT
afs-90955	60	7	ls	ls	ADJ
afs-90955	60	8	)	)	PUNCT
afs-90955	60	9	estimators	estimator	NOUN
afs-90955	60	10	.	.	PUNCT
afs-90955	61	1	note	note	VERB
afs-90955	61	2	that	that	SCONJ
afs-90955	61	3	the	the	DET
afs-90955	61	4	computation	computation	NOUN
afs-90955	61	5	of	of	ADP
afs-90955	61	6	observed	observed	ADJ
afs-90955	61	7	genotype	genotype	NOUN
afs-90955	61	8	data	datum	NOUN
afs-90955	61	9	af	af	PROPN
afs-90955	61	10	neglects	neglect	VERB
afs-90955	61	11	the	the	DET
afs-90955	61	12	pedigree	pedigree	ADV
afs-90955	61	13	-	-	PUNCT
afs-90955	61	14	based	base	VERB
afs-90955	61	15	covariance	covariance	NOUN
afs-90955	61	16	structure	structure	NOUN
afs-90955	61	17	between	between	ADP
afs-90955	61	18	the	the	DET
afs-90955	61	19	genotyped	genotype	VERB
afs-90955	61	20	animals	animal	NOUN
afs-90955	61	21	.	.	PUNCT
afs-90955	62	1	p	p	PRON
afs-90955	62	2	�	�	PROPN
afs-90955	62	3	i=1n'mi/(2n	i=1n'mi/(2n	NOUN
afs-90955	62	4	)	)	PUNCT
afs-90955	63	1	p	p	X
afs-90955	63	2	�	�	X
afs-90955	63	3	i=	i=	PROPN
afs-90955	63	4	1	1	NUM
afs-90955	63	5	2	2	NUM
afs-90955	63	6	(	(	PUNCT
afs-90955	63	7	q'q)-1q'mi	q'q)-1q'mi	PROPN
afs-90955	63	8	.	.	PUNCT
afs-90955	64	1	μ	μ	NUM
afs-90955	64	2	�	�	PROPN
afs-90955	64	3	i=1n'(a22)-1mi/(1n'(a22)-11n	i=1n'(a22)-1mi/(1n'(a22)-11n	PROPN
afs-90955	64	4	)	)	PUNCT
afs-90955	64	5	.	.	PUNCT
afs-90955	65	1	p	p	X
afs-90955	65	2	�	�	PROPN
afs-90955	65	3	i=	i=	PROPN
afs-90955	65	4	1	1	NUM
afs-90955	65	5	2	2	NUM
afs-90955	65	6	μ	μ	NUM
afs-90955	65	7	�	�	PROPN
afs-90955	65	8	i.	i.	PROPN
afs-90955	65	9	mi=1nμi+e	mi=1nμi+e	PROPN
afs-90955	65	10	,	,	PUNCT
afs-90955	65	11	mi	mi	PROPN
afs-90955	65	12	=	=	NOUN
afs-90955	65	13	qμi+e	qμi+e	PROPN
afs-90955	65	14	,	,	PUNCT
afs-90955	65	15	p	p	NOUN
afs-90955	65	16	�	�	X
afs-90955	65	17	i=	i=	PROPN
afs-90955	65	18	1	1	NUM
afs-90955	65	19	2	2	NUM
afs-90955	65	20	(	(	PUNCT
afs-90955	65	21	q'(a22)-1q)-1q'(a22)-1mi	q'(a22)-1q)-1q'(a22)-1mi	NOUN
afs-90955	65	22	,	,	PUNCT
afs-90955	65	23	agricultural	agricultural	ADJ
afs-90955	65	24	and	and	CCONJ
afs-90955	65	25	food	food	NOUN
afs-90955	65	26	science	science	PROPN
afs-90955	65	27	i.	i.	PROPN
afs-90955	65	28	strandén	strandén	PROPN
afs-90955	65	29	&	&	CCONJ
afs-90955	65	30	e.a	e.a	PROPN
afs-90955	65	31	.	.	PROPN
afs-90955	65	32	mäntysaari	mäntysaari	PROPN
afs-90955	65	33	(	(	PUNCT
afs-90955	65	34	2020	2020	NUM
afs-90955	65	35	)	)	PUNCT
afs-90955	65	36	29	29	NUM
afs-90955	65	37	:	:	PUNCT
afs-90955	65	38	166–176	166–176	NUM
afs-90955	65	39	168	168	NUM
afs-90955	65	40	computational	computational	ADJ
afs-90955	65	41	algorithms	algorithm	NOUN
afs-90955	65	42	computationally	computationally	ADV
afs-90955	65	43	,	,	PUNCT
afs-90955	65	44	the	the	DET
afs-90955	65	45	most	most	ADV
afs-90955	65	46	challenging	challenging	ADJ
afs-90955	65	47	terms	term	NOUN
afs-90955	65	48	in	in	ADP
afs-90955	65	49	formulas	formula	NOUN
afs-90955	65	50	[	[	X
afs-90955	65	51	1	1	NUM
afs-90955	65	52	]	]	PUNCT
afs-90955	65	53	and	and	CCONJ
afs-90955	65	54	[	[	X
afs-90955	65	55	2	2	NUM
afs-90955	65	56	]	]	PUNCT
afs-90955	65	57	are	be	AUX
afs-90955	65	58	due	due	ADJ
afs-90955	65	59	to	to	ADP
afs-90955	65	60	(	(	PUNCT
afs-90955	65	61	a22	a22	PROPN
afs-90955	65	62	)	)	PUNCT
afs-90955	65	63	-1	-1	NOUN
afs-90955	65	64	,	,	PUNCT
afs-90955	65	65	particularly	particularly	ADV
afs-90955	65	66	when	when	SCONJ
afs-90955	65	67	n	n	PRON
afs-90955	65	68	is	be	AUX
afs-90955	65	69	large	large	ADJ
afs-90955	65	70	.	.	PUNCT
afs-90955	66	1	note	note	VERB
afs-90955	66	2	that	that	SCONJ
afs-90955	66	3	the	the	DET
afs-90955	66	4	computations	computation	NOUN
afs-90955	66	5	involving	involve	VERB
afs-90955	66	6	(	(	PUNCT
afs-90955	66	7	a22	a22	PROPN
afs-90955	66	8	)	)	PUNCT
afs-90955	66	9	-1	-1	PUNCT
afs-90955	66	10	need	need	VERB
afs-90955	66	11	to	to	PART
afs-90955	66	12	be	be	AUX
afs-90955	66	13	done	do	VERB
afs-90955	66	14	for	for	ADP
afs-90955	66	15	each	each	DET
afs-90955	66	16	group	group	NOUN
afs-90955	66	17	and	and	CCONJ
afs-90955	66	18	marker	marker	NOUN
afs-90955	66	19	,	,	PUNCT
afs-90955	66	20	i.e.	i.e.	X
afs-90955	66	21	,	,	PUNCT
afs-90955	66	22	in	in	ADP
afs-90955	66	23	total	total	ADJ
afs-90955	66	24	mr	mr	PROPN
afs-90955	66	25	times	times	PROPN
afs-90955	66	26	.	.	PUNCT
afs-90955	67	1	fortunately	fortunately	ADV
afs-90955	67	2	,	,	PUNCT
afs-90955	67	3	all	all	DET
afs-90955	67	4	terms	term	NOUN
afs-90955	67	5	involving	involve	VERB
afs-90955	67	6	(	(	PUNCT
afs-90955	67	7	a22	a22	PROPN
afs-90955	67	8	)	)	PUNCT
afs-90955	67	9	-1	-1	X
afs-90955	67	10	are	be	AUX
afs-90955	67	11	independent	independent	ADJ
afs-90955	67	12	from	from	ADP
afs-90955	67	13	the	the	DET
afs-90955	67	14	marker	marker	NOUN
afs-90955	67	15	genotypes	genotype	NOUN
afs-90955	67	16	in	in	ADP
afs-90955	67	17	m	m	PRON
afs-90955	67	18	and	and	CCONJ
afs-90955	67	19	can	can	AUX
afs-90955	67	20	be	be	AUX
afs-90955	67	21	factored	factor	VERB
afs-90955	67	22	as	as	ADP
afs-90955	67	23	a	a	DET
afs-90955	67	24	common	common	ADJ
afs-90955	67	25	multiplier	multipli	ADJ
afs-90955	67	26	which	which	PRON
afs-90955	67	27	is	be	AUX
afs-90955	67	28	calculated	calculate	VERB
afs-90955	67	29	only	only	ADV
afs-90955	67	30	once	once	ADV
afs-90955	67	31	.	.	PUNCT
afs-90955	68	1	for	for	ADP
afs-90955	68	2	the	the	DET
afs-90955	68	3	single	single	ADJ
afs-90955	68	4	group	group	NOUN
afs-90955	68	5	case	case	NOUN
afs-90955	68	6	,	,	PUNCT
afs-90955	68	7	formula	formula	NOUN
afs-90955	68	8	[	[	X
afs-90955	68	9	1	1	NUM
afs-90955	68	10	]	]	PUNCT
afs-90955	68	11	can	can	AUX
afs-90955	68	12	be	be	AUX
afs-90955	68	13	written	write	VERB
afs-90955	68	14	as	as	ADP
afs-90955	68	15	where	where	SCONJ
afs-90955	68	16	is	be	AUX
afs-90955	68	17	a	a	DET
afs-90955	68	18	row	row	NOUN
afs-90955	68	19	vector	vector	NOUN
afs-90955	68	20	of	of	ADP
afs-90955	68	21	length	length	NOUN
afs-90955	68	22	n.	n.	PROPN
afs-90955	68	23	note	note	VERB
afs-90955	68	24	that	that	SCONJ
afs-90955	68	25	the	the	DET
afs-90955	68	26	c	c	PROPN
afs-90955	68	27	vector	vector	NOUN
afs-90955	68	28	can	can	AUX
afs-90955	68	29	be	be	AUX
afs-90955	68	30	written	write	VERB
afs-90955	68	31	[	[	X
afs-90955	68	32	3	3	X
afs-90955	68	33	]	]	PUNCT
afs-90955	68	34	where	where	SCONJ
afs-90955	68	35	f=(a22	f=(a22	PROPN
afs-90955	68	36	)	)	PUNCT
afs-90955	68	37	-11n	-11n	PROPN
afs-90955	68	38	is	be	AUX
afs-90955	68	39	an	an	DET
afs-90955	68	40	n	n	NOUN
afs-90955	68	41	by	by	ADP
afs-90955	68	42	1	1	NUM
afs-90955	68	43	vector	vector	NOUN
afs-90955	68	44	.	.	PUNCT
afs-90955	69	1	for	for	ADP
afs-90955	69	2	the	the	DET
afs-90955	69	3	multiple	multiple	ADJ
afs-90955	69	4	group	group	NOUN
afs-90955	69	5	case	case	NOUN
afs-90955	69	6	,	,	PUNCT
afs-90955	69	7	formula	formula	NOUN
afs-90955	69	8	[	[	X
afs-90955	69	9	2	2	NUM
afs-90955	69	10	]	]	PUNCT
afs-90955	69	11	can	can	AUX
afs-90955	69	12	be	be	AUX
afs-90955	69	13	written	write	VERB
afs-90955	69	14	where	where	SCONJ
afs-90955	69	15	is	be	AUX
afs-90955	69	16	an	an	DET
afs-90955	69	17	r	r	NOUN
afs-90955	69	18	by	by	ADP
afs-90955	69	19	n	n	PRON
afs-90955	69	20	matrix	matrix	NOUN
afs-90955	69	21	.	.	PUNCT
afs-90955	70	1	like	like	INTJ
afs-90955	70	2	for	for	ADP
afs-90955	70	3	the	the	DET
afs-90955	70	4	c	c	PROPN
afs-90955	70	5	vector	vector	NOUN
afs-90955	70	6	,	,	PUNCT
afs-90955	70	7	the	the	DET
afs-90955	70	8	c	c	NOUN
afs-90955	70	9	matrix	matrix	NOUN
afs-90955	70	10	can	can	AUX
afs-90955	70	11	be	be	AUX
afs-90955	70	12	expressed	express	VERB
afs-90955	70	13	[	[	X
afs-90955	70	14	4	4	X
afs-90955	70	15	]	]	PUNCT
afs-90955	70	16	where	where	SCONJ
afs-90955	70	17	f=(a22	f=(a22	PROPN
afs-90955	70	18	)	)	PUNCT
afs-90955	70	19	-1q	-1q	PROPN
afs-90955	70	20	is	be	AUX
afs-90955	70	21	an	an	DET
afs-90955	70	22	n	n	NOUN
afs-90955	70	23	by	by	ADP
afs-90955	70	24	r	r	NOUN
afs-90955	70	25	matrix	matrix	NOUN
afs-90955	70	26	.	.	PUNCT
afs-90955	71	1	note	note	VERB
afs-90955	71	2	that	that	SCONJ
afs-90955	71	3	for	for	ADP
afs-90955	71	4	the	the	DET
afs-90955	71	5	multiple	multiple	ADJ
afs-90955	71	6	group	group	NOUN
afs-90955	71	7	case	case	NOUN
afs-90955	71	8	,	,	PUNCT
afs-90955	71	9	(	(	PUNCT
afs-90955	71	10	a22	a22	PROPN
afs-90955	71	11	)	)	PUNCT
afs-90955	71	12	-1	-1	PUNCT
afs-90955	71	13	is	be	AUX
afs-90955	71	14	needed	need	VERB
afs-90955	71	15	in	in	ADP
afs-90955	71	16	r	r	NOUN
afs-90955	71	17	multiplications	multiplication	NOUN
afs-90955	71	18	due	due	ADP
afs-90955	71	19	to	to	ADP
afs-90955	71	20	the	the	DET
afs-90955	71	21	r	r	NOUN
afs-90955	71	22	columns	column	NOUN
afs-90955	71	23	in	in	ADP
afs-90955	71	24	q.	q.	PROPN
afs-90955	71	25	thus	thus	ADV
afs-90955	71	26	,	,	PUNCT
afs-90955	71	27	solving	solve	VERB
afs-90955	71	28	each	each	PRON
afs-90955	71	29	of	of	ADP
afs-90955	71	30	the	the	DET
afs-90955	71	31	af	af	PROPN
afs-90955	71	32	requires	require	VERB
afs-90955	71	33	multiplication	multiplication	NOUN
afs-90955	71	34	of	of	ADP
afs-90955	71	35	the	the	DET
afs-90955	71	36	marker	marker	NOUN
afs-90955	71	37	vector	vector	NOUN
afs-90955	71	38	mi	mi	PROPN
afs-90955	71	39	by	by	ADP
afs-90955	71	40	a	a	DET
afs-90955	71	41	constant	constant	ADJ
afs-90955	71	42	vector	vector	NOUN
afs-90955	71	43	c	c	NOUN
afs-90955	71	44	or	or	CCONJ
afs-90955	71	45	matrix	matrix	VERB
afs-90955	71	46	c.	c.	NOUN
afs-90955	71	47	an	an	DET
afs-90955	71	48	alternative	alternative	ADJ
afs-90955	71	49	approach	approach	NOUN
afs-90955	71	50	is	be	AUX
afs-90955	71	51	to	to	PART
afs-90955	71	52	calculate	calculate	VERB
afs-90955	71	53	all	all	DET
afs-90955	71	54	af	af	VERB
afs-90955	71	55	simultaneously	simultaneously	ADV
afs-90955	71	56	by	by	ADP
afs-90955	71	57	and	and	CCONJ
afs-90955	71	58	for	for	ADP
afs-90955	71	59	the	the	DET
afs-90955	71	60	single	single	ADJ
afs-90955	71	61	and	and	CCONJ
afs-90955	71	62	multiple	multiple	ADJ
afs-90955	71	63	group	group	NOUN
afs-90955	71	64	cases	case	NOUN
afs-90955	71	65	,	,	PUNCT
afs-90955	71	66	respectively	respectively	ADV
afs-90955	71	67	.	.	PUNCT
afs-90955	72	1	computations	computation	NOUN
afs-90955	72	2	of	of	ADP
afs-90955	72	3	the	the	DET
afs-90955	72	4	f	f	PROPN
afs-90955	72	5	vector	vector	NOUN
afs-90955	72	6	and	and	CCONJ
afs-90955	72	7	the	the	DET
afs-90955	72	8	f	f	PROPN
afs-90955	72	9	matrix	matrix	NOUN
afs-90955	72	10	need	need	VERB
afs-90955	72	11	the	the	DET
afs-90955	72	12	inverse	inverse	NOUN
afs-90955	72	13	matrix	matrix	NOUN
afs-90955	72	14	(	(	PUNCT
afs-90955	72	15	a22	a22	PROPN
afs-90955	72	16	)	)	PUNCT
afs-90955	72	17	-1	-1	NOUN
afs-90955	72	18	.	.	PUNCT
afs-90955	73	1	as	as	SCONJ
afs-90955	73	2	described	describe	VERB
afs-90955	73	3	in	in	ADP
afs-90955	73	4	strandén	strandén	PROPN
afs-90955	73	5	et	et	PROPN
afs-90955	73	6	al	al	PROPN
afs-90955	73	7	.	.	PROPN
afs-90955	74	1	(	(	PUNCT
afs-90955	74	2	2017	2017	NUM
afs-90955	74	3	)	)	PUNCT
afs-90955	74	4	,	,	PUNCT
afs-90955	74	5	the	the	DET
afs-90955	74	6	computations	computation	NOUN
afs-90955	74	7	involving	involve	VERB
afs-90955	74	8	this	this	DET
afs-90955	74	9	matrix	matrix	NOUN
afs-90955	74	10	can	can	AUX
afs-90955	74	11	be	be	AUX
afs-90955	74	12	made	make	VERB
afs-90955	74	13	efficiently	efficiently	ADV
afs-90955	74	14	using	use	VERB
afs-90955	74	15	submatrices	submatrice	NOUN
afs-90955	74	16	of	of	ADP
afs-90955	74	17	the	the	DET
afs-90955	74	18	inverse	inverse	NOUN
afs-90955	74	19	of	of	ADP
afs-90955	74	20	the	the	DET
afs-90955	74	21	full	full	ADJ
afs-90955	74	22	relationship	relationship	NOUN
afs-90955	74	23	matrix	matrix	NOUN
afs-90955	74	24	a.	a.	NOUN
afs-90955	74	25	animals	animal	NOUN
afs-90955	74	26	can	can	AUX
afs-90955	74	27	be	be	AUX
afs-90955	74	28	assigned	assign	VERB
afs-90955	74	29	to	to	ADP
afs-90955	74	30	two	two	NUM
afs-90955	74	31	sets	set	NOUN
afs-90955	74	32	:	:	PUNCT
afs-90955	74	33	set	set	NOUN
afs-90955	74	34	1	1	NUM
afs-90955	74	35	has	have	AUX
afs-90955	74	36	the	the	DET
afs-90955	74	37	non	non	ADJ
afs-90955	74	38	-	-	ADJ
afs-90955	74	39	genotyped	genotyped	ADJ
afs-90955	74	40	ancestors	ancestor	NOUN
afs-90955	74	41	of	of	ADP
afs-90955	74	42	genotyped	genotype	VERB
afs-90955	74	43	animals	animal	NOUN
afs-90955	74	44	,	,	PUNCT
afs-90955	74	45	set	set	VERB
afs-90955	74	46	2	2	NUM
afs-90955	74	47	has	have	VERB
afs-90955	74	48	the	the	DET
afs-90955	74	49	genotyped	genotype	VERB
afs-90955	74	50	animals	animal	NOUN
afs-90955	74	51	.	.	PUNCT
afs-90955	75	1	then	then	ADV
afs-90955	75	2	,	,	PUNCT
afs-90955	75	3	the	the	DET
afs-90955	75	4	relationship	relationship	NOUN
afs-90955	75	5	matrix	matrix	NOUN
afs-90955	75	6	a	a	PRON
afs-90955	75	7	and	and	CCONJ
afs-90955	75	8	its	its	PRON
afs-90955	75	9	inverse	inverse	NOUN
afs-90955	75	10	a-1	a-1	NOUN
afs-90955	75	11	can	can	AUX
afs-90955	75	12	be	be	AUX
afs-90955	75	13	expressed	express	VERB
afs-90955	75	14	by	by	ADP
afs-90955	75	15	submatrices	submatrice	NOUN
afs-90955	75	16	referring	refer	VERB
afs-90955	75	17	to	to	ADP
afs-90955	75	18	the	the	DET
afs-90955	75	19	two	two	NUM
afs-90955	75	20	sets	set	NOUN
afs-90955	75	21	:	:	PUNCT
afs-90955	75	22	and	and	CCONJ
afs-90955	75	23	according	accord	VERB
afs-90955	75	24	to	to	ADP
afs-90955	75	25	the	the	DET
afs-90955	75	26	rules	rule	NOUN
afs-90955	75	27	of	of	ADP
afs-90955	75	28	matrix	matrix	NOUN
afs-90955	75	29	algebra	algebra	NOUN
afs-90955	75	30	,	,	PUNCT
afs-90955	75	31	inverse	inverse	NOUN
afs-90955	75	32	of	of	ADP
afs-90955	75	33	the	the	DET
afs-90955	75	34	a22	a22	PROPN
afs-90955	75	35	matrix	matrix	NOUN
afs-90955	75	36	can	can	AUX
afs-90955	75	37	be	be	AUX
afs-90955	75	38	expressed	express	VERB
afs-90955	75	39	using	use	VERB
afs-90955	75	40	elements	element	NOUN
afs-90955	75	41	of	of	ADP
afs-90955	75	42	the	the	DET
afs-90955	75	43	inverse	inverse	NOUN
afs-90955	75	44	matrix	matrix	NOUN
afs-90955	75	45	a-1	a-1	NOUN
afs-90955	75	46	:	:	PUNCT
afs-90955	76	1	[	[	X
afs-90955	76	2	5	5	NUM
afs-90955	76	3	]	]	X
afs-90955	76	4	computations	computation	NOUN
afs-90955	76	5	involving	involve	VERB
afs-90955	76	6	sub	sub	NOUN
afs-90955	76	7	-	-	NOUN
afs-90955	76	8	matrices	matrix	NOUN
afs-90955	76	9	of	of	ADP
afs-90955	76	10	a-1	a-1	PROPN
afs-90955	76	11	can	can	AUX
afs-90955	76	12	be	be	AUX
afs-90955	76	13	made	make	VERB
afs-90955	76	14	by	by	ADP
afs-90955	76	15	using	use	VERB
afs-90955	76	16	the	the	DET
afs-90955	76	17	pedigree	pedigree	ADJ
afs-90955	76	18	list	list	NOUN
afs-90955	76	19	(	(	PUNCT
afs-90955	76	20	henderson	henderson	PROPN
afs-90955	76	21	1976	1976	NUM
afs-90955	76	22	,	,	PUNCT
afs-90955	76	23	quaas	quaas	NOUN
afs-90955	76	24	1976	1976	NUM
afs-90955	76	25	)	)	PUNCT
afs-90955	76	26	.	.	PUNCT
afs-90955	77	1	note	note	VERB
afs-90955	77	2	that	that	SCONJ
afs-90955	77	3	while	while	SCONJ
afs-90955	77	4	the	the	DET
afs-90955	77	5	whole	whole	ADJ
afs-90955	77	6	population	population	NOUN
afs-90955	77	7	pedigree	pedigree	NOUN
afs-90955	77	8	can	can	AUX
afs-90955	77	9	hold	hold	VERB
afs-90955	77	10	millions	million	NOUN
afs-90955	77	11	of	of	ADP
afs-90955	77	12	animals	animal	NOUN
afs-90955	77	13	,	,	PUNCT
afs-90955	77	14	the	the	DET
afs-90955	77	15	matrix	matrix	NOUN
afs-90955	77	16	a	a	PRON
afs-90955	77	17	can	can	AUX
afs-90955	77	18	be	be	AUX
afs-90955	77	19	restricted	restrict	VERB
afs-90955	77	20	to	to	PART
afs-90955	77	21	include	include	VERB
afs-90955	77	22	only	only	ADV
afs-90955	77	23	genotyped	genotype	VERB
afs-90955	77	24	animals	animal	NOUN
afs-90955	77	25	and	and	CCONJ
afs-90955	77	26	their	their	PRON
afs-90955	77	27	ancestors	ancestor	NOUN
afs-90955	77	28	.	.	PUNCT
afs-90955	78	1	for	for	ADP
afs-90955	78	2	example	example	NOUN
afs-90955	78	3	,	,	PUNCT
afs-90955	78	4	non	non	ADJ
afs-90955	78	5	-	-	ADJ
afs-90955	78	6	genotyped	genotyped	ADJ
afs-90955	78	7	progeny	progeny	NOUN
afs-90955	78	8	of	of	ADP
afs-90955	78	9	these	these	PRON
afs-90955	78	10	do	do	AUX
afs-90955	78	11	not	not	PART
afs-90955	78	12	contribute	contribute	VERB
afs-90955	78	13	information	information	NOUN
afs-90955	78	14	to	to	ADP
afs-90955	78	15	af	af	PROPN
afs-90955	78	16	.	.	PUNCT
afs-90955	79	1	this	this	DET
afs-90955	79	2	reduction	reduction	NOUN
afs-90955	79	3	of	of	ADP
afs-90955	79	4	the	the	DET
afs-90955	79	5	a	a	DET
afs-90955	79	6	matrix	matrix	NOUN
afs-90955	79	7	to	to	ADP
afs-90955	79	8	genotyped	genotype	VERB
afs-90955	79	9	animals	animal	NOUN
afs-90955	79	10	and	and	CCONJ
afs-90955	79	11	their	their	PRON
afs-90955	79	12	ancestors	ancestor	NOUN
afs-90955	79	13	can	can	AUX
afs-90955	79	14	reduce	reduce	VERB
afs-90955	79	15	substantially	substantially	ADV
afs-90955	79	16	the	the	DET
afs-90955	79	17	amount	amount	NOUN
afs-90955	79	18	of	of	ADP
afs-90955	79	19	computations	computation	NOUN
afs-90955	79	20	.	.	PUNCT
afs-90955	80	1	consider	consider	VERB
afs-90955	80	2	calculating	calculate	VERB
afs-90955	80	3	v=(a22	v=(a22	NOUN
afs-90955	80	4	)	)	PUNCT
afs-90955	81	1	--1s	--1s	ADV
afs-90955	81	2	where	where	SCONJ
afs-90955	81	3	s	s	NOUN
afs-90955	81	4	is	be	AUX
afs-90955	81	5	an	an	DET
afs-90955	81	6	n	n	NOUN
afs-90955	81	7	by	by	ADP
afs-90955	81	8	1	1	NUM
afs-90955	81	9	vector	vector	NOUN
afs-90955	81	10	.	.	PUNCT
afs-90955	82	1	according	accord	VERB
afs-90955	82	2	to	to	ADP
afs-90955	82	3	formula	formula	NOUN
afs-90955	82	4	[	[	X
afs-90955	82	5	5	5	NUM
afs-90955	82	6	]	]	PUNCT
afs-90955	82	7	,	,	PUNCT
afs-90955	82	8	we	we	PRON
afs-90955	82	9	need	need	VERB
afs-90955	82	10	to	to	PART
afs-90955	82	11	compute	compute	VERB
afs-90955	82	12	v=(a22	v=(a22	NOUN
afs-90955	82	13	)	)	PUNCT
afs-90955	83	1	-1s=	-1s=	PROPN
afs-90955	83	2	(	(	PUNCT
afs-90955	83	3	a22	a22	PROPN
afs-90955	83	4	–	–	PUNCT
afs-90955	83	5	a21(a11)-1a12)s	a21(a11)-1a12)s	PROPN
afs-90955	83	6	.	.	PUNCT
afs-90955	84	1	this	this	DET
afs-90955	84	2	calculation	calculation	NOUN
afs-90955	84	3	can	can	AUX
afs-90955	84	4	be	be	AUX
afs-90955	84	5	split	split	VERB
afs-90955	84	6	into	into	ADP
afs-90955	84	7	the	the	DET
afs-90955	84	8	following	follow	VERB
afs-90955	84	9	three	three	NUM
afs-90955	84	10	steps	step	NOUN
afs-90955	84	11	(	(	PUNCT
afs-90955	84	12	strandén	strandén	PROPN
afs-90955	84	13	et	et	PROPN
afs-90955	84	14	al	al	PROPN
afs-90955	84	15	.	.	PROPN
afs-90955	84	16	2017	2017	NUM
afs-90955	84	17	):	):	PUNCT
afs-90955	84	18	1	1	NUM
afs-90955	84	19	)	)	PUNCT
afs-90955	84	20	2	2	NUM
afs-90955	84	21	)	)	PUNCT
afs-90955	84	22	3	3	NUM
afs-90955	84	23	)	)	PUNCT
afs-90955	84	24	steps	step	NOUN
afs-90955	84	25	1	1	NUM
afs-90955	84	26	)	)	PUNCT
afs-90955	84	27	and	and	CCONJ
afs-90955	84	28	3	3	X
afs-90955	84	29	)	)	PUNCT
afs-90955	84	30	involve	involve	VERB
afs-90955	84	31	sparse	sparse	ADJ
afs-90955	84	32	submatrices	submatrice	NOUN
afs-90955	84	33	a12	a12	NOUN
afs-90955	84	34	and	and	CCONJ
afs-90955	84	35	a21	a21	NOUN
afs-90955	84	36	of	of	ADP
afs-90955	84	37	a-1	a-1	PROPN
afs-90955	84	38	.	.	PUNCT
afs-90955	85	1	because	because	SCONJ
afs-90955	85	2	these	these	DET
afs-90955	85	3	steps	step	NOUN
afs-90955	85	4	compute	compute	VERB
afs-90955	85	5	a	a	DET
afs-90955	85	6	submatrix	submatrix	NOUN
afs-90955	85	7	by	by	ADP
afs-90955	85	8	vector	vector	NOUN
afs-90955	85	9	product	product	NOUN
afs-90955	85	10	,	,	PUNCT
afs-90955	85	11	the	the	DET
afs-90955	85	12	calculations	calculation	NOUN
afs-90955	85	13	can	can	AUX
afs-90955	85	14	be	be	AUX
afs-90955	85	15	performed	perform	VERB
afs-90955	85	16	using	use	VERB
afs-90955	85	17	pedigree	pedigree	ADJ
afs-90955	85	18	information	information	NOUN
afs-90955	85	19	without	without	ADP
afs-90955	85	20	making	make	VERB
afs-90955	85	21	the	the	DET
afs-90955	85	22	submatrices	submatrice	NOUN
afs-90955	85	23	(	(	PUNCT
afs-90955	85	24	henderson	henderson	PROPN
afs-90955	85	25	1976	1976	NUM
afs-90955	85	26	,	,	PUNCT
afs-90955	85	27	quaas	quaas	NOUN
afs-90955	85	28	1976	1976	NUM
afs-90955	85	29	)	)	PUNCT
afs-90955	85	30	.	.	PUNCT
afs-90955	86	1	step	step	NOUN
afs-90955	86	2	2	2	NUM
afs-90955	86	3	)	)	PUNCT
afs-90955	86	4	can	can	AUX
afs-90955	86	5	be	be	AUX
afs-90955	86	6	calculated	calculate	VERB
afs-90955	86	7	by	by	ADP
afs-90955	86	8	solving	solve	VERB
afs-90955	86	9	y1	y1	NOUN
afs-90955	86	10	in	in	ADP
afs-90955	86	11	a11y1	a11y1	NOUN
afs-90955	86	12	=	=	PROPN
afs-90955	86	13	x1	x1	NOUN
afs-90955	86	14	which	which	PRON
afs-90955	86	15	can	can	AUX
afs-90955	86	16	be	be	AUX
afs-90955	86	17	done	do	VERB
afs-90955	86	18	by	by	ADP
afs-90955	86	19	alternative	alternative	ADJ
afs-90955	86	20	approaches	approach	NOUN
afs-90955	86	21	(	(	PUNCT
afs-90955	86	22	see	see	VERB
afs-90955	86	23	“	"	PUNCT
afs-90955	86	24	solving	solve	VERB
afs-90955	86	25	approaches	approach	NOUN
afs-90955	86	26	in	in	ADP
afs-90955	86	27	bpop	bpop	ADJ
afs-90955	86	28	”	"	PUNCT
afs-90955	86	29	)	)	PUNCT
afs-90955	86	30	.	.	PUNCT
afs-90955	87	1	the	the	DET
afs-90955	87	2	above	above	ADJ
afs-90955	87	3	three	three	NUM
afs-90955	87	4	steps	step	NOUN
afs-90955	87	5	can	can	AUX
afs-90955	87	6	be	be	AUX
afs-90955	87	7	used	use	VERB
afs-90955	87	8	to	to	PART
afs-90955	87	9	calculate	calculate	VERB
afs-90955	87	10	vector	vector	NOUN
afs-90955	87	11	f	f	PROPN
afs-90955	87	12	in	in	ADP
afs-90955	87	13	equation	equation	NOUN
afs-90955	87	14	[	[	X
afs-90955	87	15	3	3	NUM
afs-90955	87	16	]	]	PUNCT
afs-90955	87	17	,	,	PUNCT
afs-90955	87	18	,	,	PUNCT
afs-90955	87	19	by	by	ADP
afs-90955	87	20	assigning	assign	VERB
afs-90955	87	21	vector	vector	NOUN
afs-90955	87	22	s	s	NOUN
afs-90955	87	23	to	to	PART
afs-90955	87	24	be	be	AUX
afs-90955	87	25	1n	1n	NUM
afs-90955	87	26	,	,	PUNCT
afs-90955	87	27	and	and	CCONJ
afs-90955	87	28	the	the	DET
afs-90955	87	29	result	result	NOUN
afs-90955	87	30	v	v	NOUN
afs-90955	87	31	equals	equal	VERB
afs-90955	87	32	f.	f.	PROPN
afs-90955	87	33	for	for	ADP
afs-90955	87	34	the	the	DET
afs-90955	87	35	computation	computation	NOUN
afs-90955	87	36	of	of	ADP
afs-90955	87	37	equation	equation	NOUN
afs-90955	87	38	[	[	X
afs-90955	87	39	4	4	NUM
afs-90955	87	40	]	]	PUNCT
afs-90955	87	41	,	,	PUNCT
afs-90955	87	42	the	the	DET
afs-90955	87	43	three	three	NUM
afs-90955	87	44	steps	step	NOUN
afs-90955	87	45	need	need	VERB
afs-90955	87	46	to	to	PART
afs-90955	87	47	be	be	AUX
afs-90955	87	48	done	do	VERB
afs-90955	87	49	r	r	NOUN
afs-90955	87	50	times	time	NOUN
afs-90955	87	51	,	,	PUNCT
afs-90955	87	52	separately	separately	ADV
afs-90955	87	53	for	for	ADP
afs-90955	87	54	each	each	DET
afs-90955	87	55	column	column	NOUN
afs-90955	87	56	of	of	ADP
afs-90955	87	57	q	q	PROPN
afs-90955	87	58	,	,	PUNCT
afs-90955	87	59	to	to	PART
afs-90955	87	60	compute	compute	VERB
afs-90955	87	61	columns	column	NOUN
afs-90955	87	62	of	of	ADP
afs-90955	87	63	f.	f.	PROPN
afs-90955	87	64	hence	hence	PROPN
afs-90955	87	65	,	,	PUNCT
afs-90955	87	66	vector	vector	NOUN
afs-90955	87	67	s	s	NOUN
afs-90955	87	68	is	be	AUX
afs-90955	87	69	a	a	DET
afs-90955	87	70	column	column	NOUN
afs-90955	87	71	of	of	ADP
afs-90955	87	72	q	q	NOUN
afs-90955	87	73	,	,	PUNCT
afs-90955	87	74	and	and	CCONJ
afs-90955	87	75	the	the	DET
afs-90955	87	76	result	result	NOUN
afs-90955	87	77	v	v	NOUN
afs-90955	87	78	is	be	AUX
afs-90955	87	79	the	the	DET
afs-90955	87	80	corresponding	corresponding	ADJ
afs-90955	87	81	column	column	NOUN
afs-90955	87	82	in	in	ADP
afs-90955	87	83	f.	f.	PROPN
afs-90955	87	84	p	p	PROPN
afs-90955	87	85	�	�	PROPN
afs-90955	87	86	i	i	PROPN
afs-90955	87	87	=	=	PROPN
afs-90955	87	88	cmi	cmi	NOUN
afs-90955	87	89	c=	c=	VERB
afs-90955	87	90	1	1	NUM
afs-90955	87	91	2	2	NUM
afs-90955	87	92	1n	1n	NUM
afs-90955	87	93	'	'	PUNCT
afs-90955	87	94	(	(	PUNCT
afs-90955	87	95	(	(	PUNCT
afs-90955	87	96	a22))-1	a22))-1	NOUN
afs-90955	87	97	�	�	PROPN
afs-90955	87	98	�	�	PROPN
afs-90955	87	99	1n	1n	PROPN
afs-90955	87	100	'	'	PUNCT
afs-90955	88	1	(	(	PUNCT
afs-90955	88	2	(	(	PUNCT
afs-90955	88	3	a22))-11n	a22))-11n	PROPN
afs-90955	88	4	�	�	PROPN
afs-90955	88	5	�	�	PROPN
afs-90955	88	6	�	�	PROPN
afs-90955	88	7	�	�	PROPN
afs-90955	88	8	c=	c=	NOUN
afs-90955	88	9	1	1	NUM
afs-90955	88	10	2	2	NUM
afs-90955	88	11	f'	f'	NUM
afs-90955	88	12	�	�	PROPN
afs-90955	88	13	�	�	PROPN
afs-90955	88	14	1n	1n	PROPN
afs-90955	88	15	'	'	PART
afs-90955	88	16	f	f	PROPN
afs-90955	88	17	�	�	PROPN
afs-90955	88	18	�	�	PROPN
afs-90955	88	19	-1	-1	PROPN
afs-90955	88	20	p	p	X
afs-90955	88	21	�	�	PROPN
afs-90955	88	22	i	i	PROPN
afs-90955	88	23	=	=	PROPN
afs-90955	88	24	cmi	cmi	NOUN
afs-90955	88	25	c=	c=	VERB
afs-90955	88	26	1	1	NUM
afs-90955	88	27	2	2	NUM
afs-90955	88	28	(	(	PUNCT
afs-90955	88	29	(	(	PUNCT
afs-90955	88	30	q'((a22))-1q))-1q'((a22))-1	q'((a22))-1q))-1q'((a22))-1	VERB
afs-90955	88	31	p	p	PRON
afs-90955	88	32	�	�	PROPN
afs-90955	88	33	=cm	=cm	NOUN
afs-90955	88	34	p	p	ADJ
afs-90955	88	35	�	�	PROPN
afs-90955	88	36	=cm	=cm	NOUN
afs-90955	88	37	a-1=	a-1=	NOUN
afs-90955	88	38	�	�	X
afs-90955	88	39	a	a	DET
afs-90955	88	40	11	11	NUM
afs-90955	88	41	a12	a12	NOUN
afs-90955	88	42	a21	a21	PROPN
afs-90955	88	43	a22	a22	PROPN
afs-90955	88	44	�	�	PROPN
afs-90955	88	45	.	.	PUNCT
afs-90955	89	1	a=	a=	PROPN
afs-90955	89	2	�	�	PROPN
afs-90955	89	3	�	�	PROPN
afs-90955	89	4	a11	a11	PROPN
afs-90955	89	5	a12	a12	PROPN
afs-90955	89	6	a21	a21	PROPN
afs-90955	89	7	a22	a22	PROPN
afs-90955	89	8	�	�	PROPN
afs-90955	89	9	�	�	PROPN
afs-90955	89	10	(	(	PUNCT
afs-90955	89	11	a22)-1	a22)-1	NOUN
afs-90955	89	12	=	=	NUM
afs-90955	89	13	a22	a22	NOUN
afs-90955	89	14	-	-	PUNCT
afs-90955	89	15	a21	a21	PROPN
afs-90955	89	16	�	�	PROPN
afs-90955	89	17	a11	a11	PROPN
afs-90955	89	18	�	�	PROPN
afs-90955	89	19	-1	-1	PROPN
afs-90955	89	20	a12	a12	PROPN
afs-90955	89	21	.	.	PUNCT
afs-90955	90	1	�	�	PROPN
afs-90955	91	1	x1	x1	PROPN
afs-90955	91	2	x2	x2	PROPN
afs-90955	91	3	�	�	PROPN
afs-90955	91	4	=	=	SYM
afs-90955	91	5	�	�	PROPN
afs-90955	91	6	a	a	DET
afs-90955	91	7	12	12	NUM
afs-90955	91	8	a22	a22	PROPN
afs-90955	91	9	�	�	PROPN
afs-90955	91	10	s	s	PART
afs-90955	91	11	y1=	y1=	PROPN
afs-90955	91	12	�	�	PROPN
afs-90955	91	13	a11	a11	PROPN
afs-90955	91	14	�	�	PROPN
afs-90955	91	15	-1	-1	PROPN
afs-90955	91	16	x1	x1	PROPN
afs-90955	92	1	v	v	PROPN
afs-90955	92	2	=	=	SYM
afs-90955	92	3	x2	x2	PROPN
afs-90955	92	4	−	−	PROPN
afs-90955	92	5	a21y1	a21y1	PRON
afs-90955	92	6	c=	c=	VERB
afs-90955	92	7	f	f	X
afs-90955	92	8	'	'	PUNCT
afs-90955	92	9	�	�	PROPN
afs-90955	92	10	�	�	PROPN
afs-90955	92	11	21n	21n	NOUN
afs-90955	92	12	'	'	PART
afs-90955	92	13	f	f	X
afs-90955	92	14	�	�	PROPN
afs-90955	92	15	�	�	PROPN
afs-90955	92	16	⁄⁄	⁄⁄	NUM
afs-90955	92	17	,	,	PUNCT
afs-90955	92	18	c=	c=	VERB
afs-90955	92	19	1	1	NUM
afs-90955	92	20	2	2	NUM
afs-90955	92	21	(	(	PUNCT
afs-90955	92	22	(	(	PUNCT
afs-90955	92	23	q'f))-1f	q'f))-1f	NOUN
afs-90955	92	24	'	'	PUNCT
afs-90955	92	25	,	,	PUNCT
afs-90955	92	26	c=	c=	VERB
afs-90955	92	27	1	1	NUM
afs-90955	92	28	2	2	NUM
afs-90955	92	29	(	(	PUNCT
afs-90955	92	30	(	(	PUNCT
afs-90955	92	31	q'f))-1f	q'f))-1f	NOUN
afs-90955	92	32	'	'	PUNCT
afs-90955	92	33	agricultural	agricultural	ADJ
afs-90955	92	34	and	and	CCONJ
afs-90955	92	35	food	food	NOUN
afs-90955	92	36	science	science	PROPN
afs-90955	92	37	i.	i.	PROPN
afs-90955	92	38	strandén	strandén	PROPN
afs-90955	92	39	&	&	CCONJ
afs-90955	92	40	e.a	e.a	PROPN
afs-90955	92	41	.	.	PROPN
afs-90955	92	42	mäntysaari	mäntysaari	PROPN
afs-90955	92	43	(	(	PUNCT
afs-90955	92	44	2020	2020	NUM
afs-90955	92	45	)	)	PUNCT
afs-90955	92	46	29	29	NUM
afs-90955	92	47	:	:	PUNCT
afs-90955	92	48	166–176	166–176	NUM
afs-90955	92	49	169	169	NUM
afs-90955	92	50	bpop	bpop	NOUN
afs-90955	92	51	program	program	NOUN
afs-90955	92	52	we	we	PRON
afs-90955	92	53	have	have	AUX
afs-90955	92	54	written	write	VERB
afs-90955	92	55	an	an	DET
afs-90955	92	56	easy	easy	ADJ
afs-90955	92	57	-	-	PUNCT
afs-90955	92	58	to	to	ADP
afs-90955	92	59	-	-	PUNCT
afs-90955	92	60	use	use	NOUN
afs-90955	92	61	software	software	NOUN
afs-90955	92	62	,	,	PUNCT
afs-90955	92	63	called	call	VERB
afs-90955	92	64	bpop	bpop	ADV
afs-90955	92	65	,	,	PUNCT
afs-90955	92	66	to	to	PART
afs-90955	92	67	calculate	calculate	VERB
afs-90955	92	68	estimates	estimate	NOUN
afs-90955	92	69	to	to	ADP
afs-90955	92	70	the	the	DET
afs-90955	92	71	base	base	ADJ
afs-90955	92	72	population	population	NOUN
afs-90955	92	73	af	af	AUX
afs-90955	92	74	using	use	VERB
afs-90955	92	75	the	the	DET
afs-90955	92	76	described	describe	VERB
afs-90955	92	77	approaches	approach	NOUN
afs-90955	92	78	.	.	PUNCT
afs-90955	93	1	to	to	PART
afs-90955	93	2	address	address	VERB
afs-90955	93	3	large	large	ADJ
afs-90955	93	4	populations	population	NOUN
afs-90955	93	5	and	and	CCONJ
afs-90955	93	6	numbers	number	NOUN
afs-90955	93	7	of	of	ADP
afs-90955	93	8	genotyped	genotype	VERB
afs-90955	93	9	animals	animal	NOUN
afs-90955	93	10	,	,	PUNCT
afs-90955	93	11	bpop	bpop	PROPN
afs-90955	93	12	has	have	AUX
afs-90955	93	13	been	be	AUX
afs-90955	93	14	written	write	VERB
afs-90955	93	15	with	with	ADP
afs-90955	93	16	fortran	fortran	NOUN
afs-90955	93	17	95	95	NUM
afs-90955	93	18	.	.	PUNCT
afs-90955	94	1	the	the	DET
afs-90955	94	2	program	program	NOUN
afs-90955	94	3	expects	expect	VERB
afs-90955	94	4	at	at	ADP
afs-90955	94	5	least	least	ADJ
afs-90955	94	6	names	name	NOUN
afs-90955	94	7	of	of	ADP
afs-90955	94	8	pedigree	pedigree	ADJ
afs-90955	94	9	and	and	CCONJ
afs-90955	94	10	marker	marker	NOUN
afs-90955	94	11	genotype	genotype	NOUN
afs-90955	94	12	files	file	NOUN
afs-90955	94	13	which	which	PRON
afs-90955	94	14	include	include	VERB
afs-90955	94	15	the	the	DET
afs-90955	94	16	input	input	NOUN
afs-90955	94	17	information	information	NOUN
afs-90955	94	18	for	for	ADP
afs-90955	94	19	the	the	DET
afs-90955	94	20	calculations	calculation	NOUN
afs-90955	94	21	.	.	PUNCT
afs-90955	95	1	by	by	ADP
afs-90955	95	2	default	default	NOUN
afs-90955	95	3	,	,	PUNCT
afs-90955	95	4	the	the	DET
afs-90955	95	5	relationship	relationship	NOUN
afs-90955	95	6	matrix	matrix	NOUN
afs-90955	95	7	computations	computation	NOUN
afs-90955	95	8	,	,	PUNCT
afs-90955	95	9	v=(a22	v=(a22	PROPN
afs-90955	95	10	)	)	PUNCT
afs-90955	95	11	-1s	-1s	PROPN
afs-90955	95	12	,	,	PUNCT
afs-90955	95	13	do	do	AUX
afs-90955	95	14	not	not	PART
afs-90955	95	15	use	use	VERB
afs-90955	95	16	inbreeding	inbreede	VERB
afs-90955	95	17	coefficients	coefficient	NOUN
afs-90955	95	18	because	because	SCONJ
afs-90955	95	19	the	the	DET
afs-90955	95	20	program	program	NOUN
afs-90955	95	21	does	do	AUX
afs-90955	95	22	not	not	PART
afs-90955	95	23	compute	compute	VERB
afs-90955	95	24	them	they	PRON
afs-90955	95	25	.	.	PUNCT
afs-90955	96	1	the	the	DET
afs-90955	96	2	pedigree	pedigree	ADJ
afs-90955	96	3	information	information	NOUN
afs-90955	96	4	can	can	AUX
afs-90955	96	5	be	be	AUX
afs-90955	96	6	supported	support	VERB
afs-90955	96	7	by	by	ADP
afs-90955	96	8	inbreeding	inbreede	VERB
afs-90955	96	9	coefficients	coefficient	NOUN
afs-90955	96	10	from	from	ADP
afs-90955	96	11	a	a	DET
afs-90955	96	12	file	file	NOUN
afs-90955	96	13	such	such	ADJ
afs-90955	96	14	that	that	SCONJ
afs-90955	96	15	the	the	DET
afs-90955	96	16	relationship	relationship	NOUN
afs-90955	96	17	matrix	matrix	NOUN
afs-90955	96	18	computations	computation	NOUN
afs-90955	96	19	include	include	VERB
afs-90955	96	20	inbreeding	inbreede	VERB
afs-90955	96	21	coefficients	coefficient	NOUN
afs-90955	96	22	.	.	PUNCT
afs-90955	97	1	all	all	DET
afs-90955	97	2	the	the	DET
afs-90955	97	3	information	information	NOUN
afs-90955	97	4	to	to	PART
afs-90955	97	5	compute	compute	VERB
afs-90955	97	6	elements	element	NOUN
afs-90955	97	7	of	of	ADP
afs-90955	97	8	the	the	DET
afs-90955	97	9	a22	a22	PROPN
afs-90955	97	10	matrix	matrix	NOUN
afs-90955	97	11	is	be	AUX
afs-90955	97	12	included	include	VERB
afs-90955	97	13	in	in	ADP
afs-90955	97	14	the	the	DET
afs-90955	97	15	pedigree	pedigree	NOUN
afs-90955	97	16	of	of	ADP
afs-90955	97	17	the	the	DET
afs-90955	97	18	genotyped	genotype	VERB
afs-90955	97	19	animals	animal	NOUN
afs-90955	97	20	and	and	CCONJ
afs-90955	97	21	their	their	PRON
afs-90955	97	22	ancestors	ancestor	NOUN
afs-90955	97	23	.	.	PUNCT
afs-90955	98	1	the	the	DET
afs-90955	98	2	bpop	bpop	PROPN
afs-90955	98	3	program	program	NOUN
afs-90955	98	4	prunes	prune	NOUN
afs-90955	98	5	the	the	DET
afs-90955	98	6	given	give	VERB
afs-90955	98	7	pedigree	pedigree	NOUN
afs-90955	98	8	to	to	PART
afs-90955	98	9	contain	contain	VERB
afs-90955	98	10	only	only	ADV
afs-90955	98	11	the	the	DET
afs-90955	98	12	genotyped	genotype	VERB
afs-90955	98	13	animals	animal	NOUN
afs-90955	98	14	and	and	CCONJ
afs-90955	98	15	their	their	PRON
afs-90955	98	16	ancestors	ancestor	NOUN
afs-90955	98	17	before	before	ADP
afs-90955	98	18	the	the	DET
afs-90955	98	19	af	af	PROPN
afs-90955	98	20	estimation	estimation	NOUN
afs-90955	98	21	.	.	PUNCT
afs-90955	99	1	the	the	DET
afs-90955	99	2	pedigree	pedigree	ADJ
afs-90955	99	3	file	file	NOUN
afs-90955	99	4	is	be	AUX
afs-90955	99	5	expected	expect	VERB
afs-90955	99	6	to	to	PART
afs-90955	99	7	have	have	VERB
afs-90955	99	8	a	a	DET
afs-90955	99	9	line	line	NOUN
afs-90955	99	10	for	for	ADP
afs-90955	99	11	each	each	DET
afs-90955	99	12	animal	animal	NOUN
afs-90955	99	13	.	.	PUNCT
afs-90955	100	1	each	each	DET
afs-90955	100	2	row	row	NOUN
afs-90955	100	3	has	have	VERB
afs-90955	100	4	three	three	NUM
afs-90955	100	5	numbers	number	NOUN
afs-90955	100	6	.	.	PUNCT
afs-90955	101	1	the	the	DET
afs-90955	101	2	first	first	ADJ
afs-90955	101	3	column	column	NOUN
afs-90955	101	4	has	have	VERB
afs-90955	101	5	the	the	DET
afs-90955	101	6	animal	animal	NOUN
afs-90955	101	7	i	i	PROPN
afs-90955	101	8	d	d	PROPN
afs-90955	101	9	code	code	PROPN
afs-90955	101	10	and	and	CCONJ
afs-90955	101	11	the	the	DET
afs-90955	101	12	next	next	ADJ
afs-90955	101	13	two	two	NUM
afs-90955	101	14	columns	column	NOUN
afs-90955	101	15	have	have	VERB
afs-90955	101	16	its	its	PRON
afs-90955	101	17	parent	parent	NOUN
afs-90955	101	18	i	i	PROPN
afs-90955	101	19	d	d	PROPN
afs-90955	101	20	codes	code	NOUN
afs-90955	101	21	.	.	PUNCT
afs-90955	102	1	all	all	DET
afs-90955	102	2	i	i	PRON
afs-90955	102	3	d	d	PROPN
afs-90955	102	4	codes	code	NOUN
afs-90955	102	5	must	must	AUX
afs-90955	102	6	be	be	AUX
afs-90955	102	7	positive	positive	ADJ
afs-90955	102	8	64	64	NUM
afs-90955	102	9	-	-	PUNCT
afs-90955	102	10	bit	bit	NOUN
afs-90955	102	11	integer	integer	NOUN
afs-90955	102	12	numbers	number	NOUN
afs-90955	102	13	which	which	PRON
afs-90955	102	14	can	can	AUX
afs-90955	102	15	be	be	AUX
afs-90955	102	16	at	at	ADP
afs-90955	102	17	most	most	ADJ
afs-90955	102	18	263	263	NUM
afs-90955	102	19	-	-	SYM
afs-90955	102	20	1	1	NUM
afs-90955	102	21	.	.	PUNCT
afs-90955	102	22	unknown	unknown	ADJ
afs-90955	102	23	parent	parent	NOUN
afs-90955	102	24	i	i	PROPN
afs-90955	102	25	d	d	PROPN
afs-90955	102	26	code	code	PROPN
afs-90955	102	27	is	be	AUX
afs-90955	102	28	either	either	PRON
afs-90955	102	29	zero	zero	NUM
afs-90955	102	30	or	or	CCONJ
afs-90955	102	31	a	a	DET
afs-90955	102	32	negative	negative	ADJ
afs-90955	102	33	number	number	NOUN
afs-90955	102	34	.	.	PUNCT
afs-90955	103	1	the	the	DET
afs-90955	103	2	genotypes	genotype	NOUN
afs-90955	103	3	are	be	AUX
afs-90955	103	4	expected	expect	VERB
afs-90955	103	5	to	to	PART
afs-90955	103	6	be	be	AUX
afs-90955	103	7	in	in	ADP
afs-90955	103	8	a	a	DET
afs-90955	103	9	text	text	NOUN
afs-90955	103	10	file	file	NOUN
afs-90955	103	11	.	.	PUNCT
afs-90955	104	1	the	the	DET
afs-90955	104	2	first	first	ADJ
afs-90955	104	3	column	column	NOUN
afs-90955	104	4	in	in	ADP
afs-90955	104	5	the	the	DET
afs-90955	104	6	genotype	genotype	NOUN
afs-90955	104	7	file	file	NOUN
afs-90955	104	8	has	have	VERB
afs-90955	104	9	the	the	DET
afs-90955	104	10	i	i	PROPN
afs-90955	104	11	d	d	PROPN
afs-90955	104	12	code	code	NOUN
afs-90955	104	13	numbers	number	NOUN
afs-90955	104	14	.	.	PUNCT
afs-90955	105	1	the	the	DET
afs-90955	105	2	genotypes	genotype	NOUN
afs-90955	105	3	of	of	ADP
afs-90955	105	4	an	an	DET
afs-90955	105	5	individual	individual	NOUN
afs-90955	105	6	are	be	AUX
afs-90955	105	7	on	on	ADP
afs-90955	105	8	the	the	DET
afs-90955	105	9	same	same	ADJ
afs-90955	105	10	line	line	NOUN
afs-90955	105	11	after	after	ADP
afs-90955	105	12	its	its	PRON
afs-90955	105	13	i	i	PROPN
afs-90955	105	14	d	d	PROPN
afs-90955	105	15	code	code	PROPN
afs-90955	105	16	.	.	PUNCT
afs-90955	106	1	the	the	DET
afs-90955	106	2	genotypes	genotype	NOUN
afs-90955	106	3	are	be	AUX
afs-90955	106	4	assumed	assume	VERB
afs-90955	106	5	to	to	PART
afs-90955	106	6	have	have	VERB
afs-90955	106	7	count	count	NOUN
afs-90955	106	8	of	of	ADP
afs-90955	106	9	one	one	NUM
afs-90955	106	10	of	of	ADP
afs-90955	106	11	the	the	DET
afs-90955	106	12	alleles	allele	NOUN
afs-90955	106	13	,	,	PUNCT
afs-90955	106	14	i.e.	i.e.	X
afs-90955	106	15	,	,	PUNCT
afs-90955	106	16	numbers	number	NOUN
afs-90955	106	17	zero	zero	NUM
afs-90955	106	18	,	,	PUNCT
afs-90955	106	19	one	one	NUM
afs-90955	106	20	or	or	CCONJ
afs-90955	106	21	two	two	NUM
afs-90955	106	22	,	,	PUNCT
afs-90955	106	23	as	as	SCONJ
afs-90955	106	24	described	describe	VERB
afs-90955	106	25	earlier	early	ADV
afs-90955	106	26	.	.	PUNCT
afs-90955	107	1	by	by	ADP
afs-90955	107	2	default	default	NOUN
afs-90955	107	3	,	,	PUNCT
afs-90955	107	4	the	the	DET
afs-90955	107	5	genotypes	genotype	NOUN
afs-90955	107	6	are	be	AUX
afs-90955	107	7	expected	expect	VERB
afs-90955	107	8	to	to	PART
afs-90955	107	9	be	be	AUX
afs-90955	107	10	space	space	NOUN
afs-90955	107	11	separated	separate	VERB
afs-90955	107	12	integer	integer	NOUN
afs-90955	107	13	numbers	number	NOUN
afs-90955	107	14	.	.	PUNCT
afs-90955	108	1	option	option	NOUN
afs-90955	108	2	“	"	PUNCT
afs-90955	108	3	-fmt	-fmt	NUM
afs-90955	108	4	”	"	PUNCT
afs-90955	108	5	(	(	PUNCT
afs-90955	108	6	table	table	NOUN
afs-90955	108	7	1	1	NUM
afs-90955	108	8	)	)	PUNCT
afs-90955	108	9	enables	enable	VERB
afs-90955	108	10	user	user	NOUN
afs-90955	108	11	to	to	PART
afs-90955	108	12	give	give	VERB
afs-90955	108	13	a	a	DET
afs-90955	108	14	fixed	fix	VERB
afs-90955	108	15	format	format	NOUN
afs-90955	108	16	with	with	ADP
afs-90955	108	17	fortran	fortran	ADJ
afs-90955	108	18	syntax	syntax	NOUN
afs-90955	108	19	.	.	PUNCT
afs-90955	109	1	for	for	ADP
afs-90955	109	2	example	example	NOUN
afs-90955	109	3	,	,	PUNCT
afs-90955	109	4	-fmt	-fmt	PUNCT
afs-90955	109	5	“	"	PUNCT
afs-90955	109	6	(	(	PUNCT
afs-90955	109	7	i10,26x,50240i1	i10,26x,50240i1	PROPN
afs-90955	109	8	)	)	PUNCT
afs-90955	109	9	”	"	PUNCT
afs-90955	109	10	assumes	assume	VERB
afs-90955	109	11	there	there	ADV
afs-90955	109	12	to	to	PART
afs-90955	109	13	be	be	AUX
afs-90955	109	14	a	a	DET
afs-90955	109	15	10	10	NUM
afs-90955	109	16	-	-	PUNCT
afs-90955	109	17	digit	digit	NOUN
afs-90955	109	18	i	i	PROPN
afs-90955	109	19	d	d	PROPN
afs-90955	109	20	code	code	PROPN
afs-90955	109	21	,	,	PUNCT
afs-90955	109	22	26	26	NUM
afs-90955	109	23	spaces	space	NOUN
afs-90955	109	24	,	,	PUNCT
afs-90955	109	25	and	and	CCONJ
afs-90955	109	26	50240	50240	NUM
afs-90955	109	27	genotypes	genotype	NOUN
afs-90955	109	28	without	without	ADP
afs-90955	109	29	space	space	NOUN
afs-90955	109	30	separation	separation	NOUN
afs-90955	109	31	.	.	PUNCT
afs-90955	110	1	number	number	NOUN
afs-90955	110	2	of	of	ADP
afs-90955	110	3	markers	marker	NOUN
afs-90955	110	4	in	in	ADP
afs-90955	110	5	the	the	DET
afs-90955	110	6	format	format	NOUN
afs-90955	110	7	(	(	PUNCT
afs-90955	110	8	50240	50240	NUM
afs-90955	110	9	in	in	ADP
afs-90955	110	10	the	the	DET
afs-90955	110	11	example	example	NOUN
afs-90955	110	12	above	above	ADV
afs-90955	110	13	)	)	PUNCT
afs-90955	110	14	has	have	VERB
afs-90955	110	15	to	to	PART
afs-90955	110	16	be	be	AUX
afs-90955	110	17	equal	equal	ADJ
afs-90955	110	18	or	or	CCONJ
afs-90955	110	19	more	more	ADJ
afs-90955	110	20	than	than	ADP
afs-90955	110	21	in	in	ADP
afs-90955	110	22	the	the	DET
afs-90955	110	23	genotype	genotype	NOUN
afs-90955	110	24	file	file	NOUN
afs-90955	110	25	.	.	PUNCT
afs-90955	111	1	the	the	DET
afs-90955	111	2	program	program	NOUN
afs-90955	111	3	calculates	calculate	VERB
afs-90955	111	4	and	and	CCONJ
afs-90955	111	5	uses	use	VERB
afs-90955	111	6	the	the	DET
afs-90955	111	7	actual	actual	ADJ
afs-90955	111	8	number	number	NOUN
afs-90955	111	9	of	of	ADP
afs-90955	111	10	markers	marker	NOUN
afs-90955	111	11	on	on	ADP
afs-90955	111	12	the	the	DET
afs-90955	111	13	first	first	ADJ
afs-90955	111	14	row	row	NOUN
afs-90955	111	15	of	of	ADP
afs-90955	111	16	the	the	DET
afs-90955	111	17	genotype	genotype	NOUN
afs-90955	111	18	file	file	NOUN
afs-90955	111	19	if	if	SCONJ
afs-90955	111	20	a	a	DET
afs-90955	111	21	too	too	ADV
afs-90955	111	22	large	large	ADJ
afs-90955	111	23	number	number	NOUN
afs-90955	111	24	of	of	ADP
afs-90955	111	25	genotypes	genotype	NOUN
afs-90955	111	26	is	be	AUX
afs-90955	111	27	given	give	VERB
afs-90955	111	28	in	in	ADP
afs-90955	111	29	the	the	DET
afs-90955	111	30	format	format	NOUN
afs-90955	111	31	.	.	PUNCT
afs-90955	112	1	the	the	DET
afs-90955	112	2	base	base	ADJ
afs-90955	112	3	population	population	NOUN
afs-90955	112	4	af	af	PROPN
afs-90955	112	5	are	be	AUX
afs-90955	112	6	computed	compute	VERB
afs-90955	112	7	by	by	ADP
afs-90955	112	8	equation	equation	NOUN
afs-90955	112	9	[	[	X
afs-90955	112	10	1	1	X
afs-90955	112	11	]	]	PUNCT
afs-90955	112	12	when	when	SCONJ
afs-90955	112	13	no	no	DET
afs-90955	112	14	information	information	NOUN
afs-90955	112	15	on	on	ADP
afs-90955	112	16	groups	group	NOUN
afs-90955	112	17	is	be	AUX
afs-90955	112	18	provided	provide	VERB
afs-90955	112	19	.	.	PUNCT
afs-90955	113	1	the	the	DET
afs-90955	113	2	base	base	ADJ
afs-90955	113	3	population	population	NOUN
afs-90955	113	4	animals	animal	NOUN
afs-90955	113	5	can	can	AUX
afs-90955	113	6	be	be	AUX
afs-90955	113	7	assigned	assign	VERB
afs-90955	113	8	to	to	ADP
afs-90955	113	9	groups	group	NOUN
afs-90955	113	10	for	for	ADP
afs-90955	113	11	which	which	PRON
afs-90955	113	12	the	the	DET
afs-90955	113	13	base	base	ADJ
afs-90955	113	14	population	population	NOUN
afs-90955	113	15	af	af	VERB
afs-90955	113	16	are	be	AUX
afs-90955	113	17	estimated	estimate	VERB
afs-90955	113	18	using	use	VERB
afs-90955	113	19	equation	equation	NOUN
afs-90955	113	20	[	[	X
afs-90955	113	21	2	2	NUM
afs-90955	113	22	]	]	PUNCT
afs-90955	113	23	.	.	PUNCT
afs-90955	114	1	the	the	DET
afs-90955	114	2	group	group	NOUN
afs-90955	114	3	numbers	number	NOUN
afs-90955	114	4	should	should	AUX
afs-90955	114	5	be	be	AUX
afs-90955	114	6	negative	negative	ADJ
afs-90955	114	7	integer	integer	NOUN
afs-90955	114	8	numbers	number	NOUN
afs-90955	114	9	in	in	ADP
afs-90955	114	10	the	the	DET
afs-90955	114	11	place	place	NOUN
afs-90955	114	12	of	of	ADP
afs-90955	114	13	unknown	unknown	ADJ
afs-90955	114	14	parents	parent	NOUN
afs-90955	114	15	,	,	PUNCT
afs-90955	114	16	i.e.	i.e.	X
afs-90955	114	17	,	,	PUNCT
afs-90955	114	18	any	any	DET
afs-90955	114	19	negative	negative	ADJ
afs-90955	114	20	integer	integer	NOUN
afs-90955	114	21	value	value	NOUN
afs-90955	114	22	as	as	ADP
afs-90955	114	23	a	a	DET
afs-90955	114	24	parent	parent	NOUN
afs-90955	114	25	indicates	indicate	VERB
afs-90955	114	26	that	that	SCONJ
afs-90955	114	27	the	the	DET
afs-90955	114	28	animal	animal	NOUN
afs-90955	114	29	has	have	VERB
afs-90955	114	30	a	a	DET
afs-90955	114	31	missing	miss	VERB
afs-90955	114	32	parent	parent	NOUN
afs-90955	114	33	.	.	PUNCT
afs-90955	115	1	these	these	DET
afs-90955	115	2	group	group	NOUN
afs-90955	115	3	numbers	number	NOUN
afs-90955	115	4	are	be	AUX
afs-90955	115	5	needed	need	VERB
afs-90955	115	6	for	for	ADP
afs-90955	115	7	the	the	DET
afs-90955	115	8	base	base	ADJ
afs-90955	115	9	population	population	NOUN
afs-90955	115	10	animals	animal	NOUN
afs-90955	115	11	only	only	ADV
afs-90955	115	12	.	.	PUNCT
afs-90955	116	1	in	in	ADP
afs-90955	116	2	other	other	ADJ
afs-90955	116	3	words	word	NOUN
afs-90955	116	4	,	,	PUNCT
afs-90955	116	5	the	the	DET
afs-90955	116	6	program	program	NOUN
afs-90955	116	7	calculates	calculate	VERB
afs-90955	116	8	elements	element	NOUN
afs-90955	116	9	of	of	ADP
afs-90955	116	10	the	the	DET
afs-90955	116	11	q	q	NOUN
afs-90955	116	12	matrix	matrix	NOUN
afs-90955	116	13	for	for	ADP
afs-90955	116	14	each	each	DET
afs-90955	116	15	animal	animal	NOUN
afs-90955	116	16	by	by	ADP
afs-90955	116	17	tracing	trace	VERB
afs-90955	116	18	the	the	DET
afs-90955	116	19	pedigree	pedigree	NOUN
afs-90955	116	20	to	to	ADP
afs-90955	116	21	the	the	DET
afs-90955	116	22	base	base	ADJ
afs-90955	116	23	population	population	NOUN
afs-90955	116	24	identified	identify	VERB
afs-90955	116	25	by	by	ADP
afs-90955	116	26	the	the	DET
afs-90955	116	27	base	base	ADJ
afs-90955	116	28	population	population	NOUN
afs-90955	116	29	unknown	unknown	ADJ
afs-90955	116	30	parent	parent	NOUN
afs-90955	116	31	group	group	NOUN
afs-90955	116	32	numbers	number	NOUN
afs-90955	116	33	.	.	PUNCT
afs-90955	117	1	in	in	ADP
afs-90955	117	2	order	order	NOUN
afs-90955	117	3	to	to	PART
afs-90955	117	4	estimate	estimate	VERB
afs-90955	117	5	base	base	NOUN
afs-90955	117	6	population	population	NOUN
afs-90955	117	7	af	af	VERB
afs-90955	117	8	for	for	ADP
afs-90955	117	9	the	the	DET
afs-90955	117	10	groups	group	NOUN
afs-90955	117	11	using	use	VERB
afs-90955	117	12	equation	equation	NOUN
afs-90955	117	13	[	[	X
afs-90955	117	14	2	2	NUM
afs-90955	117	15	]	]	PUNCT
afs-90955	117	16	,	,	PUNCT
afs-90955	117	17	option	option	NOUN
afs-90955	117	18	“	"	PUNCT
afs-90955	117	19	-group	-group	NOUN
afs-90955	117	20	n	n	CCONJ
afs-90955	117	21	”	"	PUNCT
afs-90955	117	22	has	have	VERB
afs-90955	117	23	to	to	PART
afs-90955	117	24	be	be	AUX
afs-90955	117	25	given	give	VERB
afs-90955	117	26	where	where	SCONJ
afs-90955	117	27	n	n	PRON
afs-90955	117	28	is	be	AUX
afs-90955	117	29	equal	equal	ADJ
afs-90955	117	30	to	to	ADP
afs-90955	117	31	or	or	CCONJ
afs-90955	117	32	more	more	ADJ
afs-90955	117	33	than	than	ADP
afs-90955	117	34	the	the	DET
afs-90955	117	35	number	number	NOUN
afs-90955	117	36	of	of	ADP
afs-90955	117	37	groups	group	NOUN
afs-90955	117	38	in	in	ADP
afs-90955	117	39	the	the	DET
afs-90955	117	40	pedigree	pedigree	NOUN
afs-90955	117	41	.	.	PUNCT
afs-90955	118	1	more	more	ADJ
afs-90955	118	2	bpop	bpop	PROPN
afs-90955	118	3	program	program	NOUN
afs-90955	118	4	options	option	NOUN
afs-90955	118	5	are	be	AUX
afs-90955	118	6	in	in	ADP
afs-90955	118	7	table	table	NOUN
afs-90955	118	8	1	1	NUM
afs-90955	118	9	.	.	PUNCT
afs-90955	118	10	table	table	NOUN
afs-90955	118	11	1	1	NUM
afs-90955	118	12	.	.	X
afs-90955	118	13	bpop	bpop	PROPN
afs-90955	118	14	program	program	NOUN
afs-90955	118	15	requires	require	VERB
afs-90955	118	16	always	always	ADV
afs-90955	118	17	the	the	DET
afs-90955	118	18	file	file	NOUN
afs-90955	118	19	names	name	NOUN
afs-90955	118	20	of	of	ADP
afs-90955	118	21	pedigree	pedigree	ADJ
afs-90955	118	22	and	and	CCONJ
afs-90955	118	23	marker	marker	NOUN
afs-90955	118	24	genotype	genotype	NOUN
afs-90955	118	25	(	(	PUNCT
afs-90955	118	26	m	m	NOUN
afs-90955	118	27	matrix	matrix	NOUN
afs-90955	118	28	)	)	PUNCT
afs-90955	118	29	as	as	ADP
afs-90955	118	30	user	user	NOUN
afs-90955	118	31	input	input	NOUN
afs-90955	118	32	.	.	PUNCT
afs-90955	119	1	optional	optional	ADJ
afs-90955	119	2	input	input	NOUN
afs-90955	119	3	,	,	PUNCT
afs-90955	119	4	their	their	PRON
afs-90955	119	5	description	description	NOUN
afs-90955	119	6	and	and	CCONJ
afs-90955	119	7	defaults	default	NOUN
afs-90955	119	8	are	be	AUX
afs-90955	119	9	given	give	VERB
afs-90955	119	10	below	below	ADV
afs-90955	119	11	.	.	PUNCT
afs-90955	120	1	option	option	NOUN
afs-90955	120	2	description	description	NOUN
afs-90955	120	3	-info	-info	NOUN
afs-90955	120	4	print	print	NOUN
afs-90955	120	5	program	program	NOUN
afs-90955	120	6	instructions	instruction	NOUN
afs-90955	120	7	,	,	PUNCT
afs-90955	120	8	current	current	ADJ
afs-90955	120	9	option	option	NOUN
afs-90955	120	10	values	value	NOUN
afs-90955	120	11	and	and	CCONJ
afs-90955	120	12	stop	stop	VERB
afs-90955	120	13	.	.	PUNCT
afs-90955	121	1	-nthr	-nthr	NOUN
afs-90955	122	1	n	n	DET
afs-90955	122	2	number	number	NOUN
afs-90955	122	3	of	of	ADP
afs-90955	122	4	threads	thread	NOUN
afs-90955	122	5	.	.	PUNCT
afs-90955	123	1	default	default	NOUN
afs-90955	123	2	is	be	AUX
afs-90955	123	3	1	1	NUM
afs-90955	123	4	.	.	PUNCT
afs-90955	123	5	-a	-a	PUNCT
afs-90955	123	6	<	<	X
afs-90955	123	7	file	file	NOUN
afs-90955	123	8	>	>	X
afs-90955	123	9	output	output	NOUN
afs-90955	123	10	file	file	NOUN
afs-90955	123	11	name	name	NOUN
afs-90955	123	12	for	for	ADP
afs-90955	123	13	the	the	DET
afs-90955	123	14	estimated	estimate	VERB
afs-90955	123	15	base	base	NOUN
afs-90955	123	16	population	population	NOUN
afs-90955	123	17	allele	allele	NOUN
afs-90955	123	18	frequencies	frequency	NOUN
afs-90955	123	19	.	.	PUNCT
afs-90955	124	1	default	default	NOUN
afs-90955	124	2	:	:	PUNCT
afs-90955	124	3	marker	marker	NOUN
afs-90955	124	4	genotype	genotype	NOUN
afs-90955	124	5	file	file	NOUN
afs-90955	124	6	appended	append	VERB
afs-90955	124	7	with	with	ADP
afs-90955	124	8	“	"	PUNCT
afs-90955	124	9	_	_	PROPN
afs-90955	124	10	af_mth	af_mth	PROPN
afs-90955	124	11	”	"	PUNCT
afs-90955	124	12	where	where	SCONJ
afs-90955	124	13	mth	mth	NOUN
afs-90955	124	14	equals	equal	VERB
afs-90955	124	15	the	the	DET
afs-90955	124	16	calculation	calculation	NOUN
afs-90955	124	17	method	method	NOUN
afs-90955	124	18	(	(	PUNCT
afs-90955	124	19	iop	iop	PROPN
afs-90955	124	20	,	,	PUNCT
afs-90955	124	21	i	i	PRON
afs-90955	124	22	m	m	PROPN
afs-90955	124	23	,	,	PUNCT
afs-90955	124	24	or	or	CCONJ
afs-90955	124	25	chm	chm	NOUN
afs-90955	124	26	)	)	PUNCT
afs-90955	124	27	.	.	PUNCT
afs-90955	125	1	-f	-f	NUM
afs-90955	126	1	<	<	X
afs-90955	126	2	file	file	NOUN
afs-90955	126	3	>	>	X
afs-90955	126	4	input	input	NOUN
afs-90955	126	5	file	file	NOUN
afs-90955	126	6	name	name	NOUN
afs-90955	126	7	for	for	ADP
afs-90955	126	8	the	the	DET
afs-90955	126	9	inbreeding	inbreede	VERB
afs-90955	126	10	coefficients	coefficient	NOUN
afs-90955	126	11	file	file	NOUN
afs-90955	126	12	(	(	PUNCT
afs-90955	126	13	input	input	NOUN
afs-90955	126	14	)	)	PUNCT
afs-90955	126	15	.	.	PUNCT
afs-90955	127	1	defaut	defaut	PROPN
afs-90955	127	2	file	file	NOUN
afs-90955	127	3	format	format	NOUN
afs-90955	127	4	:	:	PUNCT
afs-90955	127	5	<	<	X
afs-90955	127	6	i	i	X
afs-90955	127	7	d	d	PROPN
afs-90955	127	8	>	>	X
afs-90955	127	9	<	<	X
afs-90955	127	10	number	number	X
afs-90955	127	11	>	>	X
afs-90955	127	12	<	<	X
afs-90955	127	13	inbreeding	inbreede	VERB
afs-90955	127	14	coefficient	coefficient	NOUN
afs-90955	127	15	>	>	X
afs-90955	127	16	-fcol	-fcol	PROPN
afs-90955	127	17	c	c	PROPN
afs-90955	127	18	column	column	NOUN
afs-90955	127	19	number	number	NOUN
afs-90955	127	20	for	for	ADP
afs-90955	127	21	the	the	DET
afs-90955	127	22	inbreeding	inbreede	VERB
afs-90955	127	23	coefficients	coefficient	NOUN
afs-90955	127	24	in	in	ADP
afs-90955	127	25	the	the	DET
afs-90955	127	26	-f	-f	NUM
afs-90955	127	27	file	file	NOUN
afs-90955	127	28	option	option	NOUN
afs-90955	127	29	.	.	PUNCT
afs-90955	128	1	default	default	NOUN
afs-90955	128	2	is	be	AUX
afs-90955	128	3	3	3	NUM
afs-90955	128	4	.	.	PUNCT
afs-90955	129	1	-m1	-m1	PROPN
afs-90955	129	2	c	c	NOUN
afs-90955	129	3	change	change	NOUN
afs-90955	129	4	default	default	NOUN
afs-90955	129	5	column	column	NOUN
afs-90955	129	6	number	number	NOUN
afs-90955	129	7	(	(	PUNCT
afs-90955	129	8	2	2	NUM
afs-90955	129	9	)	)	PUNCT
afs-90955	129	10	of	of	ADP
afs-90955	129	11	the	the	DET
afs-90955	129	12	first	first	ADJ
afs-90955	129	13	marker	marker	NOUN
afs-90955	129	14	in	in	ADP
afs-90955	129	15	the	the	DET
afs-90955	129	16	marker	marker	NOUN
afs-90955	129	17	file	file	NOUN
afs-90955	129	18	.	.	PUNCT
afs-90955	130	1	-fmt	-fmt	NOUN
afs-90955	130	2	fmt	fmt	ADJ
afs-90955	130	3	format	format	NOUN
afs-90955	130	4	given	give	VERB
afs-90955	130	5	for	for	ADP
afs-90955	130	6	<	<	PROPN
afs-90955	130	7	i	i	PROPN
afs-90955	130	8	d	d	PROPN
afs-90955	130	9	code	code	PROPN
afs-90955	130	10	>	>	X
afs-90955	130	11	and	and	CCONJ
afs-90955	130	12	<	<	X
afs-90955	130	13	genotypes	genotype	NOUN
afs-90955	130	14	>	>	X
afs-90955	130	15	,	,	PUNCT
afs-90955	130	16	e.g.	e.g.	ADV
afs-90955	130	17	-fmt	-fmt	PUNCT
afs-90955	130	18	“	"	PUNCT
afs-90955	130	19	(	(	PUNCT
afs-90955	130	20	i2,1x,6i1	i2,1x,6i1	PROPN
afs-90955	130	21	)	)	PUNCT
afs-90955	130	22	”	"	PUNCT
afs-90955	130	23	.	.	PUNCT
afs-90955	131	1	-cr	-cr	PRON
afs-90955	131	2	v	v	PROPN
afs-90955	131	3	convergence	convergence	NOUN
afs-90955	131	4	statistic	statistic	NOUN
afs-90955	131	5	threshold	threshold	NOUN
afs-90955	131	6	value	value	NOUN
afs-90955	131	7	in	in	ADP
afs-90955	131	8	iterative	iterative	ADJ
afs-90955	131	9	solving	solving	NOUN
afs-90955	131	10	,	,	PUNCT
afs-90955	131	11	default	default	NOUN
afs-90955	131	12	10	10	NUM
afs-90955	131	13	-	-	SYM
afs-90955	131	14	5	5	NUM
afs-90955	131	15	.	.	PUNCT
afs-90955	132	1	-groups	-group	NOUN
afs-90955	132	2	n	n	PRON
afs-90955	132	3	allele	allele	NOUN
afs-90955	132	4	frequencies	frequency	NOUN
afs-90955	132	5	by	by	ADP
afs-90955	132	6	group	group	NOUN
afs-90955	132	7	(	(	PUNCT
afs-90955	132	8	negative	negative	ADJ
afs-90955	132	9	unknown	unknown	ADJ
afs-90955	132	10	parent	parent	NOUN
afs-90955	132	11	number	number	NOUN
afs-90955	132	12	)	)	PUNCT
afs-90955	132	13	,	,	PUNCT
afs-90955	132	14	n=	n=	ADJ
afs-90955	132	15	maximum	maximum	ADJ
afs-90955	132	16	number	number	NOUN
afs-90955	132	17	of	of	ADP
afs-90955	132	18	groups	group	NOUN
afs-90955	132	19	in	in	ADP
afs-90955	132	20	the	the	DET
afs-90955	132	21	pedigree	pedigree	NOUN
afs-90955	132	22	.	.	PUNCT
afs-90955	133	1	default	default	NOUN
afs-90955	133	2	:	:	PUNCT
afs-90955	133	3	n=1	n=1	PROPN
afs-90955	133	4	,	,	PUNCT
afs-90955	133	5	and	and	CCONJ
afs-90955	133	6	negative	negative	ADJ
afs-90955	133	7	parent	parent	NOUN
afs-90955	133	8	numbers	number	NOUN
afs-90955	133	9	are	be	AUX
afs-90955	133	10	ignored	ignore	VERB
afs-90955	133	11	.	.	PUNCT
afs-90955	134	1	-proportions	-proportion	NOUN
afs-90955	134	2	<	<	X
afs-90955	134	3	file	file	X
afs-90955	134	4	>	>	X
afs-90955	134	5	write	write	VERB
afs-90955	134	6	the	the	DET
afs-90955	134	7	group	group	NOUN
afs-90955	134	8	proportions	proportion	NOUN
afs-90955	134	9	in	in	ADP
afs-90955	134	10	q	q	NOUN
afs-90955	134	11	by	by	ADP
afs-90955	134	12	genotyped	genotype	VERB
afs-90955	134	13	animal	animal	NOUN
afs-90955	134	14	to	to	PART
afs-90955	134	15	file	file	VERB
afs-90955	134	16	.	.	PUNCT
afs-90955	135	1	default	default	NOUN
afs-90955	135	2	:	:	PUNCT
afs-90955	135	3	no	no	DET
afs-90955	135	4	file	file	NOUN
afs-90955	135	5	created	create	VERB
afs-90955	135	6	.	.	PUNCT
afs-90955	136	1	calculation	calculation	NOUN
afs-90955	136	2	method	method	NOUN
afs-90955	136	3	(	(	PUNCT
afs-90955	136	4	only	only	ADV
afs-90955	136	5	one	one	NUM
afs-90955	136	6	can	can	AUX
afs-90955	136	7	be	be	AUX
afs-90955	136	8	used	use	VERB
afs-90955	136	9	):	):	PUNCT
afs-90955	136	10	-iop	-iop	X
afs-90955	136	11	iteration	iteration	NOUN
afs-90955	136	12	on	on	ADP
afs-90955	136	13	pedigree	pedigree	PROPN
afs-90955	136	14	.	.	PUNCT
afs-90955	137	1	-im	-im	PUNCT
afs-90955	137	2	iteration	iteration	NOUN
afs-90955	137	3	in	in	ADP
afs-90955	137	4	memory	memory	NOUN
afs-90955	137	5	(	(	PUNCT
afs-90955	137	6	default	default	NOUN
afs-90955	137	7	)	)	PUNCT
afs-90955	137	8	.	.	PUNCT
afs-90955	138	1	-chm	-chm	PUNCT
afs-90955	139	1	cholmod	cholmod	PROPN
afs-90955	139	2	approach	approach	PROPN
afs-90955	139	3	.	.	PUNCT
afs-90955	140	1	agricultural	agricultural	ADJ
afs-90955	140	2	and	and	CCONJ
afs-90955	140	3	food	food	NOUN
afs-90955	140	4	science	science	PROPN
afs-90955	140	5	i.	i.	PROPN
afs-90955	140	6	strandén	strandén	PROPN
afs-90955	140	7	&	&	CCONJ
afs-90955	140	8	e.a	e.a	PROPN
afs-90955	140	9	.	.	PROPN
afs-90955	140	10	mäntysaari	mäntysaari	PROPN
afs-90955	140	11	(	(	PUNCT
afs-90955	140	12	2020	2020	NUM
afs-90955	140	13	)	)	PUNCT
afs-90955	140	14	29	29	NUM
afs-90955	140	15	:	:	PUNCT
afs-90955	140	16	166–176	166–176	NUM
afs-90955	140	17	170	170	NUM
afs-90955	140	18	in	in	ADP
afs-90955	140	19	the	the	DET
afs-90955	140	20	bpop	bpop	PROPN
afs-90955	140	21	program	program	NOUN
afs-90955	140	22	,	,	PUNCT
afs-90955	140	23	the	the	DET
afs-90955	140	24	base	base	ADJ
afs-90955	140	25	population	population	NOUN
afs-90955	140	26	af	af	PROPN
afs-90955	140	27	are	be	AUX
afs-90955	140	28	computed	compute	VERB
afs-90955	140	29	by	by	ADP
afs-90955	140	30	for	for	ADP
afs-90955	140	31	a	a	DET
afs-90955	140	32	single	single	ADJ
afs-90955	140	33	group	group	NOUN
afs-90955	140	34	population	population	NOUN
afs-90955	140	35	,	,	PUNCT
afs-90955	140	36	and	and	CCONJ
afs-90955	140	37	by	by	ADP
afs-90955	140	38	for	for	ADP
afs-90955	140	39	a	a	DET
afs-90955	140	40	multiple	multiple	ADJ
afs-90955	140	41	group	group	NOUN
afs-90955	140	42	population	population	NOUN
afs-90955	140	43	,	,	PUNCT
afs-90955	140	44	where	where	SCONJ
afs-90955	140	45	i	i	PRON
afs-90955	140	46	is	be	AUX
afs-90955	140	47	the	the	DET
afs-90955	140	48	marker	marker	NOUN
afs-90955	140	49	number	number	NOUN
afs-90955	140	50	,	,	PUNCT
afs-90955	140	51	and	and	CCONJ
afs-90955	140	52	mi	mi	PROPN
afs-90955	140	53	is	be	AUX
afs-90955	140	54	column	column	NOUN
afs-90955	140	55	i	i	PRON
afs-90955	140	56	in	in	ADP
afs-90955	140	57	the	the	DET
afs-90955	140	58	marker	marker	NOUN
afs-90955	140	59	matrix	matrix	NOUN
afs-90955	140	60	m.	m.	NOUN
afs-90955	141	1	the	the	DET
afs-90955	141	2	marker	marker	NOUN
afs-90955	141	3	genotypes	genotype	NOUN
afs-90955	141	4	m	m	VERB
afs-90955	141	5	are	be	AUX
afs-90955	141	6	assumed	assume	VERB
afs-90955	141	7	to	to	PART
afs-90955	141	8	be	be	AUX
afs-90955	141	9	in	in	ADP
afs-90955	141	10	a	a	DET
afs-90955	141	11	file	file	NOUN
afs-90955	141	12	where	where	SCONJ
afs-90955	141	13	each	each	DET
afs-90955	141	14	line	line	NOUN
afs-90955	141	15	has	have	VERB
afs-90955	141	16	all	all	DET
afs-90955	141	17	markers	marker	NOUN
afs-90955	141	18	for	for	ADP
afs-90955	141	19	an	an	DET
afs-90955	141	20	individual	individual	NOUN
afs-90955	141	21	.	.	PUNCT
afs-90955	142	1	in	in	ADP
afs-90955	142	2	order	order	NOUN
afs-90955	142	3	to	to	PART
afs-90955	142	4	save	save	VERB
afs-90955	142	5	memory	memory	NOUN
afs-90955	142	6	and	and	CCONJ
afs-90955	142	7	allow	allow	VERB
afs-90955	142	8	large	large	ADJ
afs-90955	142	9	genotyped	genotyped	ADJ
afs-90955	142	10	populations	population	NOUN
afs-90955	142	11	,	,	PUNCT
afs-90955	142	12	the	the	DET
afs-90955	142	13	m	m	NOUN
afs-90955	142	14	matrix	matrix	NOUN
afs-90955	142	15	is	be	AUX
afs-90955	142	16	not	not	PART
afs-90955	142	17	stored	store	VERB
afs-90955	142	18	to	to	ADP
afs-90955	142	19	memory	memory	NOUN
afs-90955	142	20	.	.	PUNCT
afs-90955	143	1	instead	instead	ADV
afs-90955	143	2	,	,	PUNCT
afs-90955	143	3	the	the	DET
afs-90955	143	4	genotype	genotype	NOUN
afs-90955	143	5	file	file	NOUN
afs-90955	143	6	is	be	AUX
afs-90955	143	7	read	read	VERB
afs-90955	143	8	line	line	NOUN
afs-90955	143	9	by	by	ADP
afs-90955	143	10	line	line	NOUN
afs-90955	143	11	,	,	PUNCT
afs-90955	143	12	i.e.	i.e.	X
afs-90955	143	13	,	,	PUNCT
afs-90955	143	14	rows	row	NOUN
afs-90955	143	15	of	of	ADP
afs-90955	143	16	matrix	matrix	NOUN
afs-90955	143	17	m	m	VERB
afs-90955	143	18	are	be	AUX
afs-90955	143	19	processed	process	VERB
afs-90955	143	20	.	.	PUNCT
afs-90955	144	1	the	the	DET
afs-90955	144	2	c	c	PROPN
afs-90955	144	3	vector	vector	NOUN
afs-90955	144	4	or	or	CCONJ
afs-90955	144	5	the	the	DET
afs-90955	144	6	c	c	NOUN
afs-90955	144	7	matrix	matrix	NOUN
afs-90955	144	8	is	be	AUX
afs-90955	144	9	kept	keep	VERB
afs-90955	144	10	in	in	ADP
afs-90955	144	11	memory	memory	NOUN
afs-90955	144	12	.	.	PUNCT
afs-90955	145	1	multiplication	multiplication	NOUN
afs-90955	145	2	of	of	ADP
afs-90955	145	3	each	each	DET
afs-90955	145	4	marker	marker	NOUN
afs-90955	145	5	row	row	NOUN
afs-90955	145	6	of	of	ADP
afs-90955	145	7	m	m	PRON
afs-90955	145	8	by	by	ADP
afs-90955	145	9	c	c	PROPN
afs-90955	145	10	or	or	CCONJ
afs-90955	145	11	c	c	PROPN
afs-90955	145	12	is	be	AUX
afs-90955	145	13	performed	perform	VERB
afs-90955	145	14	to	to	ADP
afs-90955	145	15	all	all	DET
afs-90955	145	16	markers	marker	NOUN
afs-90955	145	17	simultaneously	simultaneously	ADV
afs-90955	145	18	,	,	PUNCT
afs-90955	145	19	and	and	CCONJ
afs-90955	145	20	the	the	DET
afs-90955	145	21	result	result	NOUN
afs-90955	145	22	is	be	AUX
afs-90955	145	23	accumulated	accumulate	VERB
afs-90955	145	24	to	to	ADP
afs-90955	145	25	the	the	DET
afs-90955	145	26	af	af	PROPN
afs-90955	145	27	estimates	estimate	NOUN
afs-90955	145	28	.	.	PUNCT
afs-90955	146	1	for	for	ADP
afs-90955	146	2	example	example	NOUN
afs-90955	146	3	,	,	PUNCT
afs-90955	146	4	consider	consider	VERB
afs-90955	146	5	af	af	PROPN
afs-90955	146	6	matrix	matrix	VERB
afs-90955	146	7	.	.	PUNCT
afs-90955	147	1	it	it	PRON
afs-90955	147	2	is	be	AUX
afs-90955	147	3	calculated	calculate	VERB
afs-90955	147	4	by	by	ADP
afs-90955	147	5	sum	sum	NOUN
afs-90955	147	6	,	,	PUNCT
afs-90955	147	7	where	where	SCONJ
afs-90955	147	8	c.j	c.j	PROPN
afs-90955	147	9	is	be	AUX
afs-90955	147	10	column	column	NOUN
afs-90955	147	11	j	j	PROPN
afs-90955	147	12	of	of	ADP
afs-90955	147	13	c	c	PROPN
afs-90955	147	14	and	and	CCONJ
afs-90955	147	15	m.j	m.j	PROPN
afs-90955	147	16	is	be	AUX
afs-90955	147	17	row	row	NOUN
afs-90955	147	18	j	j	PROPN
afs-90955	147	19	of	of	ADP
afs-90955	147	20	m.	m.	NOUN
afs-90955	147	21	solving	solve	VERB
afs-90955	147	22	approaches	approach	NOUN
afs-90955	147	23	in	in	ADP
afs-90955	147	24	bpop	bpop	ADJ
afs-90955	147	25	computation	computation	NOUN
afs-90955	147	26	of	of	ADP
afs-90955	147	27	gls	gls	ADJ
afs-90955	147	28	estimates	estimate	NOUN
afs-90955	147	29	can	can	AUX
afs-90955	147	30	be	be	AUX
afs-90955	147	31	done	do	VERB
afs-90955	147	32	following	follow	VERB
afs-90955	147	33	the	the	DET
afs-90955	147	34	three	three	NUM
afs-90955	147	35	steps	step	NOUN
afs-90955	147	36	described	describe	VERB
afs-90955	147	37	earlier	early	ADV
afs-90955	147	38	in	in	ADP
afs-90955	147	39	section	section	NOUN
afs-90955	147	40	“	"	PUNCT
afs-90955	147	41	computational	computational	ADJ
afs-90955	147	42	algorithms	algorithm	NOUN
afs-90955	147	43	”	"	PUNCT
afs-90955	147	44	.	.	PUNCT
afs-90955	148	1	two	two	NUM
afs-90955	148	2	of	of	ADP
afs-90955	148	3	the	the	DET
afs-90955	148	4	steps	step	NOUN
afs-90955	148	5	,	,	PUNCT
afs-90955	148	6	numbered	number	VERB
afs-90955	148	7	1	1	NUM
afs-90955	148	8	)	)	PUNCT
afs-90955	148	9	and	and	CCONJ
afs-90955	148	10	3	3	X
afs-90955	148	11	)	)	PUNCT
afs-90955	148	12	are	be	AUX
afs-90955	148	13	matrix	matrix	NOUN
afs-90955	148	14	times	time	NOUN
afs-90955	148	15	vector	vector	NOUN
afs-90955	148	16	multiplications	multiplication	NOUN
afs-90955	148	17	.	.	PUNCT
afs-90955	149	1	computationally	computationally	ADV
afs-90955	149	2	most	most	ADV
afs-90955	149	3	challenging	challenging	ADJ
afs-90955	149	4	is	be	AUX
afs-90955	149	5	step	step	NOUN
afs-90955	149	6	2	2	NUM
afs-90955	149	7	)	)	PUNCT
afs-90955	149	8	which	which	PRON
afs-90955	149	9	requires	require	VERB
afs-90955	149	10	calculating	calculate	VERB
afs-90955	149	11	v=(a22	v=(a22	PROPN
afs-90955	149	12	)	)	PUNCT
afs-90955	149	13	-1s	-1s	PROPN
afs-90955	149	14	,	,	PUNCT
afs-90955	149	15	i.e.	i.e.	X
afs-90955	149	16	,	,	PUNCT
afs-90955	149	17	solving	solve	VERB
afs-90955	149	18	y1	y1	NOUN
afs-90955	149	19	in	in	ADP
afs-90955	149	20	a11	a11	PROPN
afs-90955	149	21	y1=	y1=	PROPN
afs-90955	149	22	x1	x1	PROPN
afs-90955	149	23	.	.	PUNCT
afs-90955	150	1	this	this	DET
afs-90955	150	2	solving	solving	NOUN
afs-90955	150	3	of	of	ADP
afs-90955	150	4	a	a	DET
afs-90955	150	5	linear	linear	ADJ
afs-90955	150	6	system	system	NOUN
afs-90955	150	7	of	of	ADP
afs-90955	150	8	equations	equation	NOUN
afs-90955	150	9	can	can	AUX
afs-90955	150	10	be	be	AUX
afs-90955	150	11	done	do	VERB
afs-90955	150	12	in	in	ADP
afs-90955	150	13	many	many	ADJ
afs-90955	150	14	ways	way	NOUN
afs-90955	150	15	,	,	PUNCT
afs-90955	150	16	and	and	CCONJ
afs-90955	150	17	the	the	DET
afs-90955	150	18	bpop	bpop	ADJ
afs-90955	150	19	program	program	NOUN
afs-90955	150	20	allows	allow	VERB
afs-90955	150	21	choosing	choose	VERB
afs-90955	150	22	one	one	NUM
afs-90955	150	23	of	of	ADP
afs-90955	150	24	three	three	NUM
afs-90955	150	25	alternatives	alternative	NOUN
afs-90955	150	26	(	(	PUNCT
afs-90955	150	27	table	table	NOUN
afs-90955	150	28	1	1	NUM
afs-90955	150	29	)	)	PUNCT
afs-90955	150	30	.	.	PUNCT
afs-90955	151	1	two	two	NUM
afs-90955	151	2	of	of	ADP
afs-90955	151	3	the	the	DET
afs-90955	151	4	approached	approach	VERB
afs-90955	151	5	,	,	PUNCT
afs-90955	151	6	options	option	NOUN
afs-90955	151	7	named	name	VERB
afs-90955	151	8	iop	iop	NOUN
afs-90955	151	9	and	and	CCONJ
afs-90955	151	10	i	i	PRON
afs-90955	151	11	m	m	PROPN
afs-90955	151	12	,	,	PUNCT
afs-90955	151	13	use	use	VERB
afs-90955	151	14	preconditioned	precondition	VERB
afs-90955	151	15	conjugate	conjugate	ADJ
afs-90955	151	16	gradient	gradient	NOUN
afs-90955	151	17	(	(	PUNCT
afs-90955	151	18	pcg	pcg	PROPN
afs-90955	151	19	)	)	PUNCT
afs-90955	151	20	iteration	iteration	NOUN
afs-90955	151	21	,	,	PUNCT
afs-90955	151	22	and	and	CCONJ
afs-90955	151	23	the	the	DET
afs-90955	151	24	third	third	ADJ
afs-90955	151	25	option	option	NOUN
afs-90955	151	26	,	,	PUNCT
afs-90955	151	27	named	name	VERB
afs-90955	151	28	chm	chm	NOUN
afs-90955	151	29	,	,	PUNCT
afs-90955	151	30	uses	use	VERB
afs-90955	151	31	direct	direct	ADJ
afs-90955	151	32	solving	solving	NOUN
afs-90955	151	33	by	by	ADP
afs-90955	151	34	cholmod	cholmod	PROPN
afs-90955	151	35	library	library	PROPN
afs-90955	151	36	(	(	PUNCT
afs-90955	151	37	davis	davis	PROPN
afs-90955	151	38	and	and	CCONJ
afs-90955	151	39	hager	hager	PROPN
afs-90955	151	40	2009	2009	NUM
afs-90955	151	41	,	,	PUNCT
afs-90955	151	42	chen	chen	PROPN
afs-90955	151	43	et	et	PROPN
afs-90955	151	44	al	al	PROPN
afs-90955	151	45	.	.	PROPN
afs-90955	151	46	2008	2008	NUM
afs-90955	151	47	)	)	PUNCT
afs-90955	151	48	.	.	PUNCT
afs-90955	152	1	in	in	ADP
afs-90955	152	2	the	the	DET
afs-90955	152	3	iop	iop	NOUN
afs-90955	152	4	and	and	CCONJ
afs-90955	152	5	i	i	PRON
afs-90955	152	6	m	m	VERB
afs-90955	152	7	approaches	approach	NOUN
afs-90955	152	8	,	,	PUNCT
afs-90955	152	9	pcg	pcg	PROPN
afs-90955	152	10	iteration	iteration	NOUN
afs-90955	152	11	is	be	AUX
afs-90955	152	12	used	use	VERB
afs-90955	152	13	to	to	PART
afs-90955	152	14	solve	solve	VERB
afs-90955	152	15	y1	y1	PROPN
afs-90955	152	16	in	in	ADP
afs-90955	152	17	a11	a11	PROPN
afs-90955	152	18	y1	y1	PROPN
afs-90955	152	19	=	=	PROPN
afs-90955	152	20	x1	x1	PROPN
afs-90955	152	21	.	.	PUNCT
afs-90955	153	1	in	in	ADP
afs-90955	153	2	pcg	pcg	PROPN
afs-90955	153	3	,	,	PUNCT
afs-90955	153	4	the	the	DET
afs-90955	153	5	core	core	ADJ
afs-90955	153	6	iteration	iteration	NOUN
afs-90955	153	7	step	step	NOUN
afs-90955	153	8	involves	involve	VERB
afs-90955	153	9	multiplication	multiplication	NOUN
afs-90955	153	10	of	of	ADP
afs-90955	153	11	a	a	DET
afs-90955	153	12	vector	vector	NOUN
afs-90955	153	13	by	by	ADP
afs-90955	153	14	the	the	DET
afs-90955	153	15	a11	a11	PROPN
afs-90955	153	16	matrix	matrix	NOUN
afs-90955	153	17	.	.	PUNCT
afs-90955	154	1	in	in	ADP
afs-90955	154	2	the	the	DET
afs-90955	154	3	iop	iop	NOUN
afs-90955	154	4	aproach	aproach	PROPN
afs-90955	154	5	,	,	PUNCT
afs-90955	154	6	the	the	DET
afs-90955	154	7	required	require	VERB
afs-90955	154	8	computations	computation	NOUN
afs-90955	154	9	are	be	AUX
afs-90955	154	10	done	do	VERB
afs-90955	154	11	by	by	ADP
afs-90955	154	12	reading	read	VERB
afs-90955	154	13	pedigree	pedigree	ADJ
afs-90955	154	14	list	list	NOUN
afs-90955	154	15	of	of	ADP
afs-90955	154	16	the	the	DET
afs-90955	154	17	genotyped	genotype	VERB
afs-90955	154	18	animals	animal	NOUN
afs-90955	154	19	and	and	CCONJ
afs-90955	154	20	their	their	PRON
afs-90955	154	21	ancestors	ancestor	NOUN
afs-90955	154	22	without	without	ADP
afs-90955	154	23	ever	ever	ADV
afs-90955	154	24	explicitly	explicitly	ADV
afs-90955	154	25	forming	form	VERB
afs-90955	154	26	the	the	DET
afs-90955	154	27	a11	a11	PROPN
afs-90955	154	28	matrix	matrix	NOUN
afs-90955	154	29	(	(	PUNCT
afs-90955	154	30	see	see	VERB
afs-90955	154	31	appendix	appendix	NOUN
afs-90955	154	32	)	)	PUNCT
afs-90955	154	33	.	.	PUNCT
afs-90955	155	1	because	because	SCONJ
afs-90955	155	2	no	no	DET
afs-90955	155	3	a11	a11	NOUN
afs-90955	155	4	matrix	matrix	NOUN
afs-90955	155	5	was	be	AUX
afs-90955	155	6	formed	form	VERB
afs-90955	155	7	for	for	ADP
afs-90955	155	8	the	the	DET
afs-90955	155	9	iop	iop	PROPN
afs-90955	155	10	approach	approach	NOUN
afs-90955	155	11	,	,	PUNCT
afs-90955	155	12	the	the	DET
afs-90955	155	13	ram	ram	NOUN
afs-90955	155	14	memory	memory	NOUN
afs-90955	155	15	need	need	NOUN
afs-90955	155	16	is	be	AUX
afs-90955	155	17	expected	expect	VERB
afs-90955	155	18	to	to	PART
afs-90955	155	19	be	be	AUX
afs-90955	155	20	small	small	ADJ
afs-90955	155	21	.	.	PUNCT
afs-90955	156	1	in	in	ADP
afs-90955	156	2	the	the	DET
afs-90955	156	3	i	i	PROPN
afs-90955	156	4	m	m	VERB
afs-90955	156	5	approach	approach	NOUN
afs-90955	156	6	,	,	PUNCT
afs-90955	156	7	the	the	DET
afs-90955	156	8	a11	a11	PROPN
afs-90955	156	9	matrix	matrix	NOUN
afs-90955	156	10	is	be	AUX
afs-90955	156	11	stored	store	VERB
afs-90955	156	12	in	in	ADP
afs-90955	156	13	memory	memory	NOUN
afs-90955	156	14	as	as	ADP
afs-90955	156	15	a	a	DET
afs-90955	156	16	sparse	sparse	ADJ
afs-90955	156	17	matrix	matrix	NOUN
afs-90955	156	18	and	and	CCONJ
afs-90955	156	19	used	use	VERB
afs-90955	156	20	in	in	ADP
afs-90955	156	21	pcg	pcg	PROPN
afs-90955	156	22	.	.	PUNCT
afs-90955	157	1	the	the	DET
afs-90955	157	2	iop	iop	PROPN
afs-90955	157	3	and	and	CCONJ
afs-90955	157	4	i	i	PROPN
afs-90955	157	5	m	m	VERB
afs-90955	157	6	methods	method	NOUN
afs-90955	157	7	(	(	PUNCT
afs-90955	157	8	options	option	NOUN
afs-90955	157	9	“	"	PUNCT
afs-90955	157	10	-iop	-iop	NOUN
afs-90955	157	11	”	"	PUNCT
afs-90955	157	12	and	and	CCONJ
afs-90955	157	13	“	"	PUNCT
afs-90955	157	14	-im	-im	X
afs-90955	157	15	”	"	PUNCT
afs-90955	157	16	)	)	PUNCT
afs-90955	157	17	use	use	VERB
afs-90955	157	18	the	the	DET
afs-90955	157	19	preconditioned	precondition	VERB
afs-90955	157	20	conjugate	conjugate	NOUN
afs-90955	157	21	gradient	gradient	NOUN
afs-90955	157	22	(	(	PUNCT
afs-90955	157	23	pcg	pcg	PROPN
afs-90955	157	24	)	)	PUNCT
afs-90955	157	25	method	method	NOUN
afs-90955	157	26	in	in	ADP
afs-90955	157	27	solving	solve	VERB
afs-90955	157	28	y1	y1	NOUN
afs-90955	157	29	in	in	ADP
afs-90955	157	30	a11	a11	PROPN
afs-90955	157	31	y1=	y1=	PROPN
afs-90955	157	32	x1	x1	PROPN
afs-90955	157	33	.	.	PUNCT
afs-90955	158	1	diagonal	diagonal	ADJ
afs-90955	158	2	of	of	ADP
afs-90955	158	3	the	the	DET
afs-90955	158	4	a11	a11	PROPN
afs-90955	158	5	matrix	matrix	NOUN
afs-90955	158	6	is	be	AUX
afs-90955	158	7	used	use	VERB
afs-90955	158	8	as	as	ADP
afs-90955	158	9	the	the	DET
afs-90955	158	10	preconditioner	preconditioner	NOUN
afs-90955	158	11	in	in	ADP
afs-90955	158	12	the	the	DET
afs-90955	158	13	pcg	pcg	PROPN
afs-90955	158	14	method	method	NOUN
afs-90955	158	15	.	.	PUNCT
afs-90955	159	1	convergence	convergence	NOUN
afs-90955	159	2	statistic	statistic	NOUN
afs-90955	159	3	at	at	ADP
afs-90955	159	4	the	the	DET
afs-90955	159	5	iteration	iteration	NOUN
afs-90955	159	6	round	round	NOUN
afs-90955	160	1	k	k	PROPN
afs-90955	160	2	is	be	AUX
afs-90955	160	3	where	where	SCONJ
afs-90955	160	4	is	be	AUX
afs-90955	160	5	vector	vector	NOUN
afs-90955	160	6	of	of	ADP
afs-90955	160	7	solutions	solution	NOUN
afs-90955	160	8	at	at	ADP
afs-90955	160	9	round	round	NOUN
afs-90955	160	10	k	k	PROPN
afs-90955	160	11	,	,	PUNCT
afs-90955	160	12	and	and	CCONJ
afs-90955	160	13	x1	x1	PROPN
afs-90955	160	14	is	be	AUX
afs-90955	160	15	the	the	DET
afs-90955	160	16	right	right	ADJ
afs-90955	160	17	-	-	PUNCT
afs-90955	160	18	hand	hand	NOUN
afs-90955	160	19	side	side	NOUN
afs-90955	160	20	.	.	PUNCT
afs-90955	161	1	convergence	convergence	NOUN
afs-90955	161	2	is	be	AUX
afs-90955	161	3	assumed	assume	VERB
afs-90955	161	4	when	when	SCONJ
afs-90955	161	5	ck	ck	PROPN
afs-90955	161	6	is	be	AUX
afs-90955	161	7	less	less	ADJ
afs-90955	161	8	than	than	ADP
afs-90955	161	9	10	10	NUM
afs-90955	161	10	-	-	SYM
afs-90955	161	11	5	5	NUM
afs-90955	161	12	.	.	PUNCT
afs-90955	162	1	the	the	DET
afs-90955	162	2	default	default	NOUN
afs-90955	162	3	convergence	convergence	NOUN
afs-90955	162	4	limit	limit	NOUN
afs-90955	162	5	can	can	AUX
afs-90955	162	6	be	be	AUX
afs-90955	162	7	changed	change	VERB
afs-90955	162	8	using	use	VERB
afs-90955	162	9	option	option	NOUN
afs-90955	162	10	“	"	PUNCT
afs-90955	162	11	-cr	-cr	NOUN
afs-90955	162	12	”	"	PUNCT
afs-90955	162	13	(	(	PUNCT
afs-90955	162	14	table	table	NOUN
afs-90955	162	15	1	1	NUM
afs-90955	162	16	)	)	PUNCT
afs-90955	162	17	.	.	PUNCT
afs-90955	163	1	in	in	ADP
afs-90955	163	2	the	the	DET
afs-90955	163	3	chm	chm	NOUN
afs-90955	163	4	approach	approach	NOUN
afs-90955	163	5	,	,	PUNCT
afs-90955	163	6	the	the	DET
afs-90955	163	7	sparse	sparse	ADJ
afs-90955	163	8	a11	a11	NOUN
afs-90955	163	9	matrix	matrix	NOUN
afs-90955	163	10	is	be	AUX
afs-90955	163	11	built	build	VERB
afs-90955	163	12	in	in	ADP
afs-90955	163	13	memory	memory	NOUN
afs-90955	163	14	as	as	ADP
afs-90955	163	15	in	in	ADP
afs-90955	163	16	the	the	DET
afs-90955	163	17	i	i	PROPN
afs-90955	163	18	m	m	VERB
afs-90955	163	19	approach	approach	NOUN
afs-90955	163	20	.	.	PUNCT
afs-90955	164	1	inverse	inverse	NOUN
afs-90955	164	2	of	of	ADP
afs-90955	164	3	the	the	DET
afs-90955	164	4	a11	a11	PROPN
afs-90955	164	5	matrix	matrix	NOUN
afs-90955	164	6	can	can	AUX
afs-90955	164	7	be	be	AUX
afs-90955	164	8	dense	dense	ADJ
afs-90955	164	9	although	although	SCONJ
afs-90955	164	10	the	the	DET
afs-90955	164	11	a11	a11	PROPN
afs-90955	164	12	matrix	matrix	NOUN
afs-90955	164	13	is	be	AUX
afs-90955	164	14	sparse	sparse	ADJ
afs-90955	164	15	.	.	PUNCT
afs-90955	165	1	consequently	consequently	ADV
afs-90955	165	2	,	,	PUNCT
afs-90955	165	3	sparse	sparse	ADJ
afs-90955	165	4	cholesky	cholesky	ADJ
afs-90955	165	5	factorization	factorization	NOUN
afs-90955	165	6	of	of	ADP
afs-90955	165	7	a11	a11	PROPN
afs-90955	165	8	by	by	ADP
afs-90955	165	9	cholmod	cholmod	PROPN
afs-90955	165	10	library	library	PROPN
afs-90955	165	11	is	be	AUX
afs-90955	165	12	used	use	VERB
afs-90955	165	13	in	in	ADP
afs-90955	165	14	solving	solving	NOUN
afs-90955	165	15	of	of	ADP
afs-90955	165	16	a11	a11	PROPN
afs-90955	165	17	y1	y1	PROPN
afs-90955	165	18	=	=	PROPN
afs-90955	165	19	x1	x1	PROPN
afs-90955	165	20	,	,	PUNCT
afs-90955	165	21	i.e.	i.e.	X
afs-90955	165	22	,	,	PUNCT
afs-90955	165	23	a	a	DET
afs-90955	165	24	direct	direct	ADJ
afs-90955	165	25	method	method	NOUN
afs-90955	165	26	is	be	AUX
afs-90955	165	27	used	use	VERB
afs-90955	165	28	instead	instead	ADV
afs-90955	165	29	of	of	ADP
afs-90955	165	30	pcg	pcg	PROPN
afs-90955	165	31	iteration	iteration	NOUN
afs-90955	165	32	.	.	PUNCT
afs-90955	166	1	the	the	DET
afs-90955	166	2	factorization	factorization	NOUN
afs-90955	166	3	is	be	AUX
afs-90955	166	4	done	do	VERB
afs-90955	166	5	with	with	ADP
afs-90955	166	6	minimal	minimal	ADJ
afs-90955	166	7	fill	fill	NOUN
afs-90955	166	8	-	-	PUNCT
afs-90955	166	9	ins	in	NOUN
afs-90955	166	10	of	of	ADP
afs-90955	166	11	the	the	DET
afs-90955	166	12	(	(	PUNCT
afs-90955	166	13	sparse	sparse	ADJ
afs-90955	166	14	)	)	PUNCT
afs-90955	166	15	matrix	matrix	NOUN
afs-90955	166	16	.	.	PUNCT
afs-90955	167	1	cholmod	cholmod	PROPN
afs-90955	167	2	includes	include	VERB
afs-90955	167	3	high	high	ADJ
afs-90955	167	4	-	-	PUNCT
afs-90955	167	5	performance	performance	NOUN
afs-90955	167	6	left	leave	VERB
afs-90955	167	7	-	-	PUNCT
afs-90955	167	8	looking	look	VERB
afs-90955	167	9	supernodal	supernodal	NOUN
afs-90955	167	10	factorization	factorization	NOUN
afs-90955	167	11	and	and	CCONJ
afs-90955	167	12	solving	solving	NOUN
afs-90955	167	13	methods	method	NOUN
afs-90955	167	14	(	(	PUNCT
afs-90955	167	15	ng	ng	PROPN
afs-90955	167	16	and	and	CCONJ
afs-90955	167	17	peyton	peyton	PROPN
afs-90955	167	18	1993	1993	NUM
afs-90955	167	19	)	)	PUNCT
afs-90955	167	20	based	base	VERB
afs-90955	167	21	on	on	ADP
afs-90955	167	22	lapack	lapack	PROPN
afs-90955	167	23	(	(	PUNCT
afs-90955	167	24	anderson	anderson	PROPN
afs-90955	167	25	et	et	PROPN
afs-90955	167	26	al	al	PROPN
afs-90955	167	27	.	.	PROPN
afs-90955	167	28	1999	1999	NUM
afs-90955	167	29	)	)	PUNCT
afs-90955	167	30	and	and	CCONJ
afs-90955	167	31	blas	blas	PROPN
afs-90955	167	32	(	(	PUNCT
afs-90955	167	33	basic	basic	ADJ
afs-90955	167	34	linear	linear	PROPN
afs-90955	167	35	algebra	algebra	NOUN
afs-90955	167	36	subprograms	subprogram	NOUN
afs-90955	167	37	)	)	PUNCT
afs-90955	167	38	(	(	PUNCT
afs-90955	167	39	dongarra	dongarra	VERB
afs-90955	167	40	et	et	PROPN
afs-90955	167	41	al	al	PROPN
afs-90955	167	42	.	.	PROPN
afs-90955	167	43	1990	1990	NUM
afs-90955	167	44	)	)	PUNCT
afs-90955	167	45	.	.	PUNCT
afs-90955	168	1	the	the	DET
afs-90955	168	2	use	use	NOUN
afs-90955	168	3	of	of	ADP
afs-90955	168	4	cholmod	cholmod	PROPN
afs-90955	168	5	requires	require	VERB
afs-90955	168	6	two	two	NUM
afs-90955	168	7	steps	step	NOUN
afs-90955	168	8	:	:	PUNCT
afs-90955	168	9	ordering	ordering	NOUN
afs-90955	168	10	/	/	SYM
afs-90955	168	11	factorization	factorization	NOUN
afs-90955	168	12	,	,	PUNCT
afs-90955	168	13	and	and	CCONJ
afs-90955	168	14	solving	solving	NOUN
afs-90955	168	15	.	.	PUNCT
afs-90955	169	1	the	the	DET
afs-90955	169	2	first	first	ADJ
afs-90955	169	3	step	step	NOUN
afs-90955	169	4	is	be	AUX
afs-90955	169	5	done	do	VERB
afs-90955	169	6	only	only	ADV
afs-90955	169	7	once	once	ADV
afs-90955	169	8	,	,	PUNCT
afs-90955	169	9	and	and	CCONJ
afs-90955	169	10	the	the	DET
afs-90955	169	11	direct	direct	ADJ
afs-90955	169	12	solving	solving	NOUN
afs-90955	169	13	is	be	AUX
afs-90955	169	14	done	do	VERB
afs-90955	169	15	for	for	ADP
afs-90955	169	16	each	each	DET
afs-90955	169	17	vector	vector	NOUN
afs-90955	169	18	s	s	PART
afs-90955	169	19	which	which	PRON
afs-90955	169	20	is	be	AUX
afs-90955	169	21	1n	1n	NUM
afs-90955	169	22	or	or	CCONJ
afs-90955	169	23	a	a	DET
afs-90955	169	24	column	column	NOUN
afs-90955	169	25	in	in	ADP
afs-90955	169	26	q.	q.	PROPN
afs-90955	169	27	study	study	PROPN
afs-90955	169	28	design	design	NOUN
afs-90955	169	29	and	and	CCONJ
afs-90955	169	30	data	datum	NOUN
afs-90955	169	31	the	the	DET
afs-90955	169	32	three	three	NUM
afs-90955	169	33	approaches	approach	NOUN
afs-90955	169	34	(	(	PUNCT
afs-90955	169	35	iop	iop	PROPN
afs-90955	169	36	,	,	PUNCT
afs-90955	169	37	i	i	PRON
afs-90955	169	38	m	m	VERB
afs-90955	169	39	and	and	CCONJ
afs-90955	169	40	chm	chm	NOUN
afs-90955	169	41	)	)	PUNCT
afs-90955	169	42	were	be	AUX
afs-90955	169	43	tested	test	VERB
afs-90955	169	44	in	in	ADP
afs-90955	169	45	estimation	estimation	NOUN
afs-90955	169	46	of	of	ADP
afs-90955	169	47	af	af	NOUN
afs-90955	169	48	using	use	VERB
afs-90955	169	49	beef	beef	NOUN
afs-90955	169	50	cattle	cattle	NOUN
afs-90955	169	51	data	datum	NOUN
afs-90955	169	52	from	from	ADP
afs-90955	169	53	the	the	DET
afs-90955	169	54	irish	irish	ADJ
afs-90955	169	55	cattle	cattle	NOUN
afs-90955	169	56	breeding	breeding	PROPN
afs-90955	169	57	federation	federation	PROPN
afs-90955	169	58	(	(	PUNCT
afs-90955	169	59	icbf	icbf	PROPN
afs-90955	169	60	)	)	PUNCT
afs-90955	169	61	.	.	PUNCT
afs-90955	170	1	the	the	DET
afs-90955	170	2	full	full	ADJ
afs-90955	170	3	pedigree	pedigree	NOUN
afs-90955	170	4	had	have	VERB
afs-90955	170	5	10.26	10.26	NUM
afs-90955	170	6	million	million	NUM
afs-90955	170	7	animals	animal	NOUN
afs-90955	170	8	of	of	ADP
afs-90955	170	9	which	which	PRON
afs-90955	170	10	1.50	1.50	NUM
afs-90955	170	11	million	million	NUM
afs-90955	170	12	were	be	AUX
afs-90955	170	13	genotyped	genotype	VERB
afs-90955	170	14	.	.	PUNCT
afs-90955	171	1	the	the	DET
afs-90955	171	2	genotyped	genotype	VERB
afs-90955	171	3	animals	animal	NOUN
afs-90955	171	4	had	have	VERB
afs-90955	171	5	an	an	DET
afs-90955	171	6	ancestor	ancestor	NOUN
afs-90955	171	7	pedigree	pedigree	NOUN
afs-90955	171	8	of	of	ADP
afs-90955	171	9	1.83	1.83	NUM
afs-90955	171	10	million	million	NUM
afs-90955	171	11	non	non	ADJ
afs-90955	171	12	-	-	ADJ
afs-90955	171	13	genotyped	genotyped	ADJ
afs-90955	171	14	animals	animal	NOUN
afs-90955	171	15	.	.	PUNCT
afs-90955	172	1	the	the	DET
afs-90955	172	2	animals	animal	NOUN
afs-90955	172	3	had	have	AUX
afs-90955	172	4	been	be	AUX
afs-90955	172	5	genotyped	genotype	VERB
afs-90955	172	6	using	use	VERB
afs-90955	172	7	different	different	ADJ
afs-90955	172	8	versions	version	NOUN
afs-90955	172	9	of	of	ADP
afs-90955	172	10	icbf	icbf	PROPN
afs-90955	172	11	idb	idb	PROPN
afs-90955	172	12	snp	snp	PROPN
afs-90955	172	13	chip	chip	NOUN
afs-90955	172	14	but	but	CCONJ
afs-90955	172	15	before	before	ADP
afs-90955	172	16	the	the	DET
afs-90955	172	17	analyses	analysis	NOUN
afs-90955	172	18	these	these	PRON
afs-90955	172	19	were	be	AUX
afs-90955	172	20	imputed	impute	VERB
afs-90955	172	21	to	to	ADP
afs-90955	172	22	the	the	DET
afs-90955	172	23	standard	standard	PROPN
afs-90955	172	24	illumina	illumina	PROPN
afs-90955	172	25	bovine	bovine	PROPN
afs-90955	172	26	snp50	snp50	PROPN
afs-90955	172	27	bead	bead	PROPN
afs-90955	172	28	chip	chip	NOUN
afs-90955	172	29	(	(	PUNCT
afs-90955	172	30	illumina	illumina	PROPN
afs-90955	172	31	,	,	PUNCT
afs-90955	172	32	san	san	PROPN
afs-90955	172	33	diego	diego	PROPN
afs-90955	172	34	,	,	PUNCT
afs-90955	172	35	usa	usa	PROPN
afs-90955	172	36	)	)	PUNCT
afs-90955	172	37	.	.	PUNCT
afs-90955	173	1	there	there	PRON
afs-90955	173	2	were	be	VERB
afs-90955	173	3	50240	50240	NUM
afs-90955	173	4	markers	marker	NOUN
afs-90955	173	5	from	from	ADP
afs-90955	173	6	29	29	NUM
afs-90955	173	7	bovine	bovine	NOUN
afs-90955	173	8	autosomes	autosome	NOUN
afs-90955	173	9	available	available	ADJ
afs-90955	173	10	for	for	ADP
afs-90955	173	11	the	the	DET
afs-90955	173	12	analysis	analysis	NOUN
afs-90955	173	13	.	.	PUNCT
afs-90955	174	1	original	original	ADJ
afs-90955	174	2	pedigree	pedigree	NOUN
afs-90955	174	3	of	of	ADP
afs-90955	174	4	the	the	DET
afs-90955	174	5	genotyped	genotype	VERB
afs-90955	174	6	animals	animal	NOUN
afs-90955	174	7	had	have	VERB
afs-90955	174	8	46	46	NUM
afs-90955	174	9	unknown	unknown	ADJ
afs-90955	174	10	parent	parent	NOUN
afs-90955	174	11	groups	group	NOUN
afs-90955	174	12	which	which	PRON
afs-90955	174	13	were	be	AUX
afs-90955	174	14	determined	determine	VERB
afs-90955	174	15	by	by	ADP
afs-90955	174	16	breed	breed	NOUN
afs-90955	174	17	of	of	ADP
afs-90955	174	18	animal	animal	NOUN
afs-90955	174	19	with	with	ADP
afs-90955	174	20	unknown	unknown	ADJ
afs-90955	174	21	parent(s	parent(s	NOUN
afs-90955	174	22	)	)	PUNCT
afs-90955	174	23	.	.	PUNCT
afs-90955	175	1	groups	group	NOUN
afs-90955	175	2	having	have	VERB
afs-90955	175	3	average	average	ADJ
afs-90955	175	4	proportion	proportion	NOUN
afs-90955	175	5	in	in	ADP
afs-90955	175	6	the	the	DET
afs-90955	175	7	q	q	NOUN
afs-90955	175	8	matrix	matrix	NOUN
afs-90955	175	9	lower	low	ADJ
afs-90955	175	10	than	than	ADP
afs-90955	175	11	0.01	0.01	NUM
afs-90955	175	12	%	%	NOUN
afs-90955	175	13	were	be	AUX
afs-90955	175	14	combined	combine	VERB
afs-90955	175	15	to	to	ADP
afs-90955	175	16	one	one	NUM
afs-90955	175	17	group	group	NOUN
afs-90955	175	18	such	such	ADJ
afs-90955	175	19	that	that	SCONJ
afs-90955	175	20	the	the	DET
afs-90955	175	21	final	final	ADJ
afs-90955	175	22	number	number	NOUN
afs-90955	175	23	of	of	ADP
afs-90955	175	24	groups	group	NOUN
afs-90955	175	25	was	be	AUX
afs-90955	175	26	24	24	NUM
afs-90955	175	27	.	.	PUNCT
afs-90955	176	1	average	average	ADJ
afs-90955	176	2	proportion	proportion	NOUN
afs-90955	176	3	of	of	ADP
afs-90955	176	4	the	the	DET
afs-90955	176	5	combined	combined	ADJ
afs-90955	176	6	group	group	NOUN
afs-90955	176	7	in	in	ADP
afs-90955	176	8	the	the	DET
afs-90955	176	9	q	q	NOUN
afs-90955	176	10	matrix	matrix	NOUN
afs-90955	176	11	was	be	AUX
afs-90955	176	12	0.01	0.01	NUM
afs-90955	176	13	%	%	NOUN
afs-90955	176	14	.	.	PUNCT
afs-90955	177	1	it	it	PRON
afs-90955	177	2	was	be	AUX
afs-90955	177	3	first	first	ADV
afs-90955	177	4	verified	verify	VERB
afs-90955	177	5	whether	whether	SCONJ
afs-90955	177	6	all	all	DET
afs-90955	177	7	three	three	NUM
afs-90955	177	8	approaches	approach	NOUN
afs-90955	177	9	gave	give	VERB
afs-90955	177	10	the	the	DET
afs-90955	177	11	same	same	ADJ
afs-90955	177	12	solutions	solution	NOUN
afs-90955	177	13	,	,	PUNCT
afs-90955	177	14	and	and	CCONJ
afs-90955	177	15	after	after	ADP
afs-90955	177	16	that	that	PRON
afs-90955	177	17	they	they	PRON
afs-90955	177	18	were	be	AUX
afs-90955	177	19	compared	compare	VERB
afs-90955	177	20	according	accord	VERB
afs-90955	177	21	to	to	ADP
afs-90955	177	22	computing	compute	VERB
afs-90955	177	23	time	time	NOUN
afs-90955	177	24	to	to	PART
afs-90955	177	25	calculate	calculate	VERB
afs-90955	177	26	v=(a22	v=(a22	PROPN
afs-90955	177	27	)	)	PUNCT
afs-90955	177	28	-1s	-1s	PROPN
afs-90955	177	29	,	,	PUNCT
afs-90955	177	30	i.e.	i.e.	X
afs-90955	177	31	,	,	PUNCT
afs-90955	177	32	step	step	NOUN
afs-90955	177	33	2	2	NUM
afs-90955	177	34	)	)	PUNCT
afs-90955	177	35	,	,	PUNCT
afs-90955	177	36	total	total	ADJ
afs-90955	177	37	computing	computing	NOUN
afs-90955	177	38	time	time	NOUN
afs-90955	177	39	,	,	PUNCT
afs-90955	177	40	and	and	CCONJ
afs-90955	177	41	peak	peak	VERB
afs-90955	177	42	random	random	ADJ
afs-90955	177	43	access	access	NOUN
afs-90955	177	44	memory	memory	NOUN
afs-90955	177	45	(	(	PUNCT
afs-90955	177	46	ram	ram	NOUN
afs-90955	177	47	)	)	PUNCT
afs-90955	177	48	use	use	NOUN
afs-90955	177	49	.	.	PUNCT
afs-90955	178	1	number	number	NOUN
afs-90955	178	2	of	of	ADP
afs-90955	178	3	pcg	pcg	PROPN
afs-90955	178	4	iterations	iteration	NOUN
afs-90955	178	5	is	be	AUX
afs-90955	178	6	reported	report	VERB
afs-90955	178	7	for	for	ADP
afs-90955	178	8	the	the	DET
afs-90955	178	9	iop	iop	NOUN
afs-90955	178	10	and	and	CCONJ
afs-90955	178	11	i	i	PRON
afs-90955	178	12	m	m	VERB
afs-90955	178	13	approaches	approach	NOUN
afs-90955	178	14	.	.	PUNCT
afs-90955	179	1	the	the	DET
afs-90955	179	2	full	full	ADJ
afs-90955	179	3	1.50	1.50	NUM
afs-90955	179	4	million	million	NUM
afs-90955	179	5	p	p	DET
afs-90955	179	6	�	�	PROPN
afs-90955	179	7	i	i	PROPN
afs-90955	179	8	=	=	PROPN
afs-90955	179	9	cmi	cmi	PROPN
afs-90955	179	10	p	p	PROPN
afs-90955	179	11	�	�	PROPN
afs-90955	179	12	=cm	=cm	NOUN
afs-90955	179	13	p	p	ADJ
afs-90955	179	14	�	�	PROPN
afs-90955	179	15	=	=	SYM
afs-90955	179	16	�	�	PROPN
afs-90955	179	17	c.jm.j	c.jm.j	ADJ
afs-90955	179	18	n	n	CCONJ
afs-90955	179	19	j=1	j=1	PROPN
afs-90955	179	20	ck=	ck=	PROPN
afs-90955	179	21	�	�	PROPN
afs-90955	179	22	�	�	PROPN
afs-90955	179	23	a11y1	a11y1	PROPN
afs-90955	180	1	[	[	X
afs-90955	180	2	k	k	X
afs-90955	180	3	]	]	X
afs-90955	180	4	−	−	PROPN
afs-90955	181	1	x1	x1	PROPN
afs-90955	181	2	�	�	PROPN
afs-90955	181	3	'	'	PART
afs-90955	181	4	�	�	PROPN
afs-90955	181	5	a11y1	a11y1	NOUN
afs-90955	182	1	[	[	X
afs-90955	182	2	k	k	X
afs-90955	182	3	]	]	X
afs-90955	182	4	−	−	PROPN
afs-90955	182	5	x1	x1	PROPN
afs-90955	182	6	�	�	PROPN
afs-90955	182	7	x1'x1	x1'x1	PROPN
afs-90955	182	8	y1	y1	NOUN
afs-90955	183	1	[	[	X
afs-90955	183	2	k	k	X
afs-90955	183	3	]	]	X
afs-90955	183	4	p	p	X
afs-90955	183	5	�	�	PROPN
afs-90955	183	6	i	i	PROPN
afs-90955	183	7	=	=	PROPN
afs-90955	183	8	cmi	cmi	X
afs-90955	183	9	agricultural	agricultural	ADJ
afs-90955	183	10	and	and	CCONJ
afs-90955	183	11	food	food	NOUN
afs-90955	183	12	science	science	PROPN
afs-90955	183	13	i.	i.	PROPN
afs-90955	183	14	strandén	strandén	PROPN
afs-90955	183	15	&	&	CCONJ
afs-90955	183	16	e.a	e.a	PROPN
afs-90955	183	17	.	.	PROPN
afs-90955	183	18	mäntysaari	mäntysaari	PROPN
afs-90955	183	19	(	(	PUNCT
afs-90955	183	20	2020	2020	NUM
afs-90955	183	21	)	)	PUNCT
afs-90955	183	22	29	29	NUM
afs-90955	183	23	:	:	PUNCT
afs-90955	183	24	166–176	166–176	NUM
afs-90955	183	25	171	171	NUM
afs-90955	183	26	genotyped	genotype	VERB
afs-90955	183	27	data	datum	NOUN
afs-90955	183	28	were	be	AUX
afs-90955	183	29	used	use	VERB
afs-90955	183	30	in	in	ADP
afs-90955	183	31	estimation	estimation	NOUN
afs-90955	183	32	of	of	ADP
afs-90955	183	33	base	base	ADJ
afs-90955	183	34	population	population	NOUN
afs-90955	183	35	af	af	VERB
afs-90955	183	36	for	for	ADP
afs-90955	183	37	two	two	NUM
afs-90955	183	38	base	base	NOUN
afs-90955	183	39	populations	population	NOUN
afs-90955	183	40	:	:	PUNCT
afs-90955	183	41	a	a	DET
afs-90955	183	42	single	single	ADJ
afs-90955	183	43	group	group	NOUN
afs-90955	183	44	and	and	CCONJ
afs-90955	183	45	a	a	DET
afs-90955	183	46	24	24	NUM
afs-90955	183	47	-	-	PUNCT
afs-90955	183	48	group	group	NOUN
afs-90955	183	49	population	population	NOUN
afs-90955	183	50	.	.	PUNCT
afs-90955	184	1	in	in	ADP
afs-90955	184	2	addition	addition	NOUN
afs-90955	184	3	,	,	PUNCT
afs-90955	184	4	single	single	ADJ
afs-90955	184	5	population	population	NOUN
afs-90955	184	6	af	af	PROPN
afs-90955	184	7	were	be	AUX
afs-90955	184	8	computed	compute	VERB
afs-90955	184	9	using	using	AUX
afs-90955	184	10	randomly	randomly	ADV
afs-90955	184	11	sampled	sample	VERB
afs-90955	184	12	0.1	0.1	NUM
afs-90955	184	13	,	,	PUNCT
afs-90955	184	14	0.5	0.5	NUM
afs-90955	184	15	and	and	CCONJ
afs-90955	184	16	1	1	NUM
afs-90955	184	17	million	million	NUM
afs-90955	184	18	genotyped	genotype	VERB
afs-90955	184	19	animals	animal	NOUN
afs-90955	184	20	in	in	ADP
afs-90955	184	21	order	order	NOUN
afs-90955	184	22	to	to	PART
afs-90955	184	23	investigate	investigate	VERB
afs-90955	184	24	scalability	scalability	NOUN
afs-90955	184	25	of	of	ADP
afs-90955	184	26	computations	computation	NOUN
afs-90955	184	27	.	.	PUNCT
afs-90955	185	1	we	we	PRON
afs-90955	185	2	used	use	VERB
afs-90955	185	3	a	a	DET
afs-90955	185	4	multi	multi	ADJ
afs-90955	185	5	-	-	ADJ
afs-90955	185	6	core	core	ADJ
afs-90955	185	7	computer	computer	NOUN
afs-90955	185	8	with	with	ADP
afs-90955	185	9	two	two	NUM
afs-90955	185	10	intel	intel	PROPN
afs-90955	185	11	®	®	NOUN
afs-90955	185	12	xeon	xeon	PROPN
afs-90955	185	13	®	®	PROPN
afs-90955	185	14	e5	e5	PROPN
afs-90955	185	15	-	-	PUNCT
afs-90955	185	16	2680	2680	NUM
afs-90955	185	17	v2	v2	NOUN
afs-90955	185	18	(	(	PUNCT
afs-90955	185	19	2.8	2.8	NUM
afs-90955	185	20	ghz	ghz	NOUN
afs-90955	185	21	)	)	PUNCT
afs-90955	185	22	processors	processor	NOUN
afs-90955	185	23	.	.	PUNCT
afs-90955	186	1	a	a	DET
afs-90955	186	2	single	single	ADJ
afs-90955	186	3	thread	thread	NOUN
afs-90955	186	4	was	be	AUX
afs-90955	186	5	mostly	mostly	ADV
afs-90955	186	6	used	use	VERB
afs-90955	186	7	.	.	PUNCT
afs-90955	187	1	however	however	ADV
afs-90955	187	2	,	,	PUNCT
afs-90955	187	3	parallel	parallel	ADJ
afs-90955	187	4	computing	computing	NOUN
afs-90955	187	5	using	use	VERB
afs-90955	187	6	at	at	ADP
afs-90955	187	7	most	most	ADV
afs-90955	187	8	10	10	NUM
afs-90955	187	9	cpu	cpu	NOUN
afs-90955	187	10	cores	core	NOUN
afs-90955	187	11	was	be	AUX
afs-90955	187	12	tested	test	VERB
afs-90955	187	13	when	when	SCONJ
afs-90955	187	14	computations	computation	NOUN
afs-90955	187	15	used	use	VERB
afs-90955	187	16	the	the	DET
afs-90955	187	17	chm	chm	NOUN
afs-90955	187	18	approach	approach	NOUN
afs-90955	187	19	.	.	PUNCT
afs-90955	188	1	the	the	DET
afs-90955	188	2	bpop	bpop	PROPN
afs-90955	188	3	program	program	NOUN
afs-90955	188	4	has	have	AUX
afs-90955	188	5	command	command	NOUN
afs-90955	188	6	line	line	NOUN
afs-90955	188	7	options	option	NOUN
afs-90955	188	8	(	(	PUNCT
afs-90955	188	9	table	table	NOUN
afs-90955	188	10	1	1	NUM
afs-90955	188	11	)	)	PUNCT
afs-90955	188	12	.	.	PUNCT
afs-90955	189	1	an	an	DET
afs-90955	189	2	example	example	NOUN
afs-90955	189	3	command	command	NOUN
afs-90955	189	4	line	line	NOUN
afs-90955	189	5	to	to	PART
afs-90955	189	6	estimate	estimate	VERB
afs-90955	189	7	base	base	NOUN
afs-90955	189	8	population	population	NOUN
afs-90955	189	9	af	af	NOUN
afs-90955	189	10	using	use	VERB
afs-90955	189	11	the	the	DET
afs-90955	189	12	icbf	icbf	NOUN
afs-90955	189	13	data	datum	NOUN
afs-90955	189	14	set	set	NOUN
afs-90955	189	15	:	:	PUNCT
afs-90955	189	16	bpop	bpop	PROPN
afs-90955	189	17	-a	-a	X
afs-90955	189	18	im.dat	im.dat	PROPN
afs-90955	189	19	-fmt	-fmt	PUNCT
afs-90955	189	20	“	"	PUNCT
afs-90955	189	21	(	(	PUNCT
afs-90955	189	22	i10,26x,50240i1	i10,26x,50240i1	PROPN
afs-90955	189	23	)	)	PUNCT
afs-90955	189	24	”	"	PUNCT
afs-90955	189	25	-f	-f	NUM
afs-90955	189	26	icbf.inbr	icbf.inbr	PROPN
afs-90955	189	27	icbf.ped	icbf.pe	VERB
afs-90955	189	28	icbf_geno.dat	icbf_geno.dat	NOUN
afs-90955	189	29	in	in	ADP
afs-90955	189	30	this	this	DET
afs-90955	189	31	case	case	NOUN
afs-90955	189	32	,	,	PUNCT
afs-90955	189	33	the	the	DET
afs-90955	189	34	default	default	NOUN
afs-90955	189	35	approach	approach	NOUN
afs-90955	189	36	(	(	PUNCT
afs-90955	189	37	i	i	NOUN
afs-90955	189	38	m	m	VERB
afs-90955	189	39	)	)	PUNCT
afs-90955	189	40	will	will	AUX
afs-90955	189	41	be	be	AUX
afs-90955	189	42	used	use	VERB
afs-90955	189	43	in	in	ADP
afs-90955	189	44	the	the	DET
afs-90955	189	45	computations	computation	NOUN
afs-90955	189	46	because	because	SCONJ
afs-90955	189	47	no	no	DET
afs-90955	189	48	computing	computing	NOUN
afs-90955	189	49	approach	approach	NOUN
afs-90955	189	50	is	be	AUX
afs-90955	189	51	given	give	VERB
afs-90955	189	52	.	.	PUNCT
afs-90955	190	1	the	the	DET
afs-90955	190	2	inbreeding	inbreede	VERB
afs-90955	190	3	coefficients	coefficient	NOUN
afs-90955	190	4	are	be	AUX
afs-90955	190	5	in	in	ADP
afs-90955	190	6	file	file	NOUN
afs-90955	190	7	“	"	PUNCT
afs-90955	190	8	icbf.inbr	icbf.inbr	PROPN
afs-90955	190	9	”	"	PUNCT
afs-90955	190	10	,	,	PUNCT
afs-90955	190	11	the	the	DET
afs-90955	190	12	pedigree	pedigree	NOUN
afs-90955	190	13	is	be	AUX
afs-90955	190	14	in	in	ADP
afs-90955	190	15	file	file	NOUN
afs-90955	190	16	“	"	PUNCT
afs-90955	190	17	icbf.ped	icbf.pe	VERB
afs-90955	190	18	”	"	PUNCT
afs-90955	190	19	and	and	CCONJ
afs-90955	190	20	the	the	DET
afs-90955	190	21	genotypes	genotype	NOUN
afs-90955	190	22	in	in	ADP
afs-90955	190	23	file	file	NOUN
afs-90955	190	24	“	"	PUNCT
afs-90955	190	25	icbf_geno.dat	icbf_geno.dat	NOUN
afs-90955	190	26	”	"	PUNCT
afs-90955	190	27	.	.	PUNCT
afs-90955	191	1	the	the	DET
afs-90955	191	2	estimated	estimate	VERB
afs-90955	191	3	base	base	NOUN
afs-90955	191	4	population	population	NOUN
afs-90955	191	5	af	af	PROPN
afs-90955	191	6	will	will	AUX
afs-90955	191	7	be	be	AUX
afs-90955	191	8	written	write	VERB
afs-90955	191	9	to	to	PART
afs-90955	191	10	file	file	VERB
afs-90955	191	11	“	"	PUNCT
afs-90955	191	12	im.dat	im.dat	PROPN
afs-90955	191	13	”	"	PUNCT
afs-90955	191	14	.	.	PUNCT
afs-90955	192	1	because	because	SCONJ
afs-90955	192	2	no	no	DET
afs-90955	192	3	“	"	PUNCT
afs-90955	192	4	-groups	-group	NOUN
afs-90955	192	5	”	"	PUNCT
afs-90955	192	6	option	option	NOUN
afs-90955	192	7	was	be	AUX
afs-90955	192	8	given	give	VERB
afs-90955	192	9	,	,	PUNCT
afs-90955	192	10	a	a	DET
afs-90955	192	11	single	single	ADJ
afs-90955	192	12	population	population	NOUN
afs-90955	192	13	is	be	AUX
afs-90955	192	14	assumed	assume	VERB
afs-90955	192	15	.	.	PUNCT
afs-90955	193	1	including	include	VERB
afs-90955	193	2	command	command	NOUN
afs-90955	193	3	“	"	PUNCT
afs-90955	193	4	-groups	-groups	PROPN
afs-90955	193	5	50	50	NUM
afs-90955	193	6	”	"	PUNCT
afs-90955	193	7	would	would	AUX
afs-90955	193	8	estimate	estimate	VERB
afs-90955	193	9	base	base	ADJ
afs-90955	193	10	population	population	NOUN
afs-90955	193	11	af	af	VERB
afs-90955	193	12	for	for	ADP
afs-90955	193	13	the	the	DET
afs-90955	193	14	groups	group	NOUN
afs-90955	193	15	given	give	VERB
afs-90955	193	16	in	in	ADP
afs-90955	193	17	the	the	DET
afs-90955	193	18	pedigree	pedigree	NOUN
afs-90955	193	19	defined	define	VERB
afs-90955	193	20	as	as	ADP
afs-90955	193	21	negative	negative	ADJ
afs-90955	193	22	parent	parent	NOUN
afs-90955	193	23	numbers	number	NOUN
afs-90955	193	24	for	for	ADP
afs-90955	193	25	the	the	DET
afs-90955	193	26	animals	animal	NOUN
afs-90955	193	27	without	without	ADP
afs-90955	193	28	known	know	VERB
afs-90955	193	29	parents	parent	NOUN
afs-90955	193	30	.	.	PUNCT
afs-90955	194	1	the	the	DET
afs-90955	194	2	number	number	NOUN
afs-90955	194	3	50	50	NUM
afs-90955	194	4	in	in	ADP
afs-90955	194	5	the	the	DET
afs-90955	194	6	option	option	NOUN
afs-90955	194	7	“	"	PUNCT
afs-90955	194	8	-groups	-group	NOUN
afs-90955	194	9	”	"	PUNCT
afs-90955	194	10	is	be	AUX
afs-90955	194	11	at	at	ADV
afs-90955	194	12	least	least	ADJ
afs-90955	194	13	as	as	ADV
afs-90955	194	14	large	large	ADJ
afs-90955	194	15	as	as	ADP
afs-90955	194	16	the	the	DET
afs-90955	194	17	number	number	NOUN
afs-90955	194	18	of	of	ADP
afs-90955	194	19	groups	group	NOUN
afs-90955	194	20	in	in	ADP
afs-90955	194	21	pedigree	pedigree	PROPN
afs-90955	194	22	.	.	PUNCT
afs-90955	195	1	results	result	NOUN
afs-90955	195	2	and	and	CCONJ
afs-90955	195	3	discussion	discussion	NOUN
afs-90955	195	4	the	the	DET
afs-90955	195	5	studied	studied	ADJ
afs-90955	195	6	three	three	NUM
afs-90955	195	7	approaches	approach	NOUN
afs-90955	195	8	gave	give	VERB
afs-90955	195	9	the	the	DET
afs-90955	195	10	same	same	ADJ
afs-90955	195	11	or	or	CCONJ
afs-90955	195	12	almost	almost	ADV
afs-90955	195	13	the	the	DET
afs-90955	195	14	same	same	ADJ
afs-90955	195	15	af	af	PROPN
afs-90955	195	16	estimates	estimate	NOUN
afs-90955	195	17	.	.	PUNCT
afs-90955	196	1	correlations	correlation	NOUN
afs-90955	196	2	between	between	ADP
afs-90955	196	3	af	af	NOUN
afs-90955	196	4	from	from	ADP
afs-90955	196	5	any	any	DET
afs-90955	196	6	two	two	NUM
afs-90955	196	7	approaches	approach	NOUN
afs-90955	196	8	were	be	AUX
afs-90955	196	9	1.00000	1.00000	NUM
afs-90955	196	10	for	for	ADP
afs-90955	196	11	the	the	DET
afs-90955	196	12	single	single	ADJ
afs-90955	196	13	population	population	NOUN
afs-90955	196	14	analysis	analysis	NOUN
afs-90955	196	15	with	with	ADP
afs-90955	196	16	the	the	DET
afs-90955	196	17	largest	large	ADJ
afs-90955	196	18	difference	difference	NOUN
afs-90955	196	19	of	of	ADP
afs-90955	196	20	0.0001	0.0001	NUM
afs-90955	196	21	in	in	ADP
afs-90955	196	22	estimated	estimate	VERB
afs-90955	196	23	base	base	NOUN
afs-90955	196	24	population	population	NOUN
afs-90955	196	25	af	af	VERB
afs-90955	196	26	for	for	ADP
afs-90955	196	27	any	any	DET
afs-90955	196	28	marker	marker	NOUN
afs-90955	196	29	by	by	ADP
afs-90955	196	30	any	any	DET
afs-90955	196	31	two	two	NUM
afs-90955	196	32	approaches	approach	NOUN
afs-90955	196	33	.	.	PUNCT
afs-90955	197	1	for	for	ADP
afs-90955	197	2	the	the	DET
afs-90955	197	3	24	24	NUM
afs-90955	197	4	-	-	PUNCT
afs-90955	197	5	group	group	NOUN
afs-90955	197	6	case	case	NOUN
afs-90955	197	7	,	,	PUNCT
afs-90955	197	8	the	the	DET
afs-90955	197	9	correlations	correlation	NOUN
afs-90955	197	10	between	between	ADP
afs-90955	197	11	af	af	PROPN
afs-90955	197	12	for	for	ADP
afs-90955	197	13	the	the	DET
afs-90955	197	14	approaches	approach	NOUN
afs-90955	197	15	were	be	AUX
afs-90955	197	16	1.00000	1.00000	NUM
afs-90955	197	17	and	and	CCONJ
afs-90955	197	18	the	the	DET
afs-90955	197	19	larger	large	ADJ
afs-90955	197	20	difference	difference	NOUN
afs-90955	197	21	was	be	AUX
afs-90955	197	22	0.0002	0.0002	NUM
afs-90955	197	23	.	.	PUNCT
afs-90955	198	1	thus	thus	ADV
afs-90955	198	2	,	,	PUNCT
afs-90955	198	3	the	the	DET
afs-90955	198	4	pcg	pcg	PROPN
afs-90955	198	5	iteration	iteration	NOUN
afs-90955	198	6	based	base	VERB
afs-90955	198	7	and	and	CCONJ
afs-90955	198	8	the	the	DET
afs-90955	198	9	direct	direct	ADJ
afs-90955	198	10	solver	solver	NOUN
afs-90955	198	11	based	base	VERB
afs-90955	198	12	approaches	approach	NOUN
afs-90955	198	13	reached	reach	VERB
afs-90955	198	14	almost	almost	ADV
afs-90955	198	15	the	the	DET
afs-90955	198	16	same	same	ADJ
afs-90955	198	17	solutions	solution	NOUN
afs-90955	198	18	.	.	PUNCT
afs-90955	199	1	computing	compute	VERB
afs-90955	199	2	time	time	NOUN
afs-90955	199	3	due	due	ADJ
afs-90955	199	4	to	to	ADP
afs-90955	199	5	calculating	calculate	VERB
afs-90955	199	6	the	the	DET
afs-90955	199	7	c	c	PROPN
afs-90955	199	8	vector	vector	NOUN
afs-90955	199	9	in	in	ADP
afs-90955	199	10	[	[	X
afs-90955	199	11	3	3	NUM
afs-90955	199	12	]	]	PUNCT
afs-90955	199	13	took	take	VERB
afs-90955	199	14	only	only	ADV
afs-90955	199	15	a	a	DET
afs-90955	199	16	fraction	fraction	NOUN
afs-90955	199	17	of	of	ADP
afs-90955	199	18	the	the	DET
afs-90955	199	19	total	total	ADJ
afs-90955	199	20	computing	computing	NOUN
afs-90955	199	21	time	time	NOUN
afs-90955	199	22	(	(	PUNCT
afs-90955	199	23	table	table	NOUN
afs-90955	199	24	2	2	NUM
afs-90955	199	25	)	)	PUNCT
afs-90955	199	26	.	.	PUNCT
afs-90955	200	1	consequently	consequently	ADV
afs-90955	200	2	,	,	PUNCT
afs-90955	200	3	differences	difference	NOUN
afs-90955	200	4	in	in	ADP
afs-90955	200	5	total	total	ADJ
afs-90955	200	6	computing	computing	NOUN
afs-90955	200	7	time	time	NOUN
afs-90955	200	8	between	between	ADP
afs-90955	200	9	the	the	DET
afs-90955	200	10	three	three	NUM
afs-90955	200	11	approaches	approach	NOUN
afs-90955	200	12	were	be	AUX
afs-90955	200	13	small	small	ADJ
afs-90955	200	14	.	.	PUNCT
afs-90955	201	1	the	the	DET
afs-90955	201	2	chm	chm	NOUN
afs-90955	201	3	approach	approach	NOUN
afs-90955	201	4	was	be	AUX
afs-90955	201	5	the	the	DET
afs-90955	201	6	slowest	slow	ADJ
afs-90955	201	7	because	because	SCONJ
afs-90955	201	8	the	the	DET
afs-90955	201	9	extra	extra	ADJ
afs-90955	201	10	computing	computing	NOUN
afs-90955	201	11	time	time	NOUN
afs-90955	201	12	due	due	ADP
afs-90955	201	13	to	to	ADP
afs-90955	201	14	making	make	VERB
afs-90955	201	15	the	the	DET
afs-90955	201	16	factorization	factorization	NOUN
afs-90955	201	17	took	take	VERB
afs-90955	201	18	all	all	DET
afs-90955	201	19	the	the	DET
afs-90955	201	20	computing	computing	NOUN
afs-90955	201	21	time	time	NOUN
afs-90955	201	22	benefits	benefit	NOUN
afs-90955	201	23	attained	attain	VERB
afs-90955	201	24	by	by	ADP
afs-90955	201	25	fast	fast	ADJ
afs-90955	201	26	solving	solving	NOUN
afs-90955	201	27	of	of	ADP
afs-90955	201	28	the	the	DET
afs-90955	201	29	c	c	PROPN
afs-90955	201	30	vector	vector	NOUN
afs-90955	201	31	.	.	PUNCT
afs-90955	202	1	the	the	DET
afs-90955	202	2	factorization	factorization	NOUN
afs-90955	202	3	took	take	VERB
afs-90955	202	4	4.38	4.38	NUM
afs-90955	202	5	min	min	NOUN
afs-90955	202	6	and	and	CCONJ
afs-90955	202	7	1.15	1.15	NUM
afs-90955	202	8	min	min	NOUN
afs-90955	202	9	with	with	ADP
afs-90955	202	10	one	one	NUM
afs-90955	202	11	and	and	CCONJ
afs-90955	202	12	ten	ten	NUM
afs-90955	202	13	cores	core	NOUN
afs-90955	202	14	,	,	PUNCT
afs-90955	202	15	respectively	respectively	ADV
afs-90955	202	16	.	.	PUNCT
afs-90955	203	1	when	when	SCONJ
afs-90955	203	2	the	the	DET
afs-90955	203	3	number	number	NOUN
afs-90955	203	4	of	of	ADP
afs-90955	203	5	genotyped	genotype	VERB
afs-90955	203	6	animals	animal	NOUN
afs-90955	203	7	was	be	AUX
afs-90955	203	8	reduced	reduce	VERB
afs-90955	203	9	,	,	PUNCT
afs-90955	203	10	the	the	DET
afs-90955	203	11	total	total	ADJ
afs-90955	203	12	computing	computing	NOUN
afs-90955	203	13	time	time	NOUN
afs-90955	203	14	reduced	reduce	VERB
afs-90955	203	15	as	as	ADV
afs-90955	203	16	well	well	ADV
afs-90955	203	17	(	(	PUNCT
afs-90955	203	18	table	table	NOUN
afs-90955	203	19	3	3	NUM
afs-90955	203	20	)	)	PUNCT
afs-90955	203	21	.	.	PUNCT
afs-90955	204	1	in	in	ADP
afs-90955	204	2	general	general	ADJ
afs-90955	204	3	,	,	PUNCT
afs-90955	204	4	all	all	DET
afs-90955	204	5	approaches	approach	NOUN
afs-90955	204	6	showed	show	VERB
afs-90955	204	7	similar	similar	ADJ
afs-90955	204	8	total	total	ADJ
afs-90955	204	9	computing	computing	NOUN
afs-90955	204	10	times	time	NOUN
afs-90955	204	11	.	.	PUNCT
afs-90955	205	1	the	the	DET
afs-90955	205	2	approaches	approach	NOUN
afs-90955	205	3	needed	need	VERB
afs-90955	205	4	different	different	ADJ
afs-90955	205	5	amount	amount	NOUN
afs-90955	205	6	of	of	ADP
afs-90955	205	7	ram	ram	NOUN
afs-90955	205	8	(	(	PUNCT
afs-90955	205	9	table	table	NOUN
afs-90955	205	10	2	2	NUM
afs-90955	205	11	)	)	PUNCT
afs-90955	205	12	which	which	PRON
afs-90955	205	13	was	be	AUX
afs-90955	205	14	expected	expect	VERB
afs-90955	205	15	.	.	PUNCT
afs-90955	206	1	the	the	DET
afs-90955	206	2	iop	iop	PROPN
afs-90955	206	3	approach	approach	NOUN
afs-90955	206	4	required	require	VERB
afs-90955	206	5	least	least	ADJ
afs-90955	206	6	amount	amount	NOUN
afs-90955	206	7	of	of	ADP
afs-90955	206	8	ram	ram	NOUN
afs-90955	206	9	.	.	PUNCT
afs-90955	207	1	in	in	ADP
afs-90955	207	2	iop	iop	PROPN
afs-90955	207	3	,	,	PUNCT
afs-90955	207	4	only	only	ADV
afs-90955	207	5	the	the	DET
afs-90955	207	6	pedigree	pedigree	ADJ
afs-90955	207	7	list	list	NOUN
afs-90955	207	8	is	be	AUX
afs-90955	207	9	read	read	VERB
afs-90955	207	10	,	,	PUNCT
afs-90955	207	11	and	and	CCONJ
afs-90955	207	12	computations	computation	NOUN
afs-90955	207	13	require	require	VERB
afs-90955	207	14	some	some	DET
afs-90955	207	15	extra	extra	ADJ
afs-90955	207	16	memory	memory	NOUN
afs-90955	207	17	.	.	PUNCT
afs-90955	208	1	in	in	ADP
afs-90955	208	2	the	the	DET
afs-90955	208	3	i	i	NOUN
afs-90955	208	4	m	m	PROPN
afs-90955	208	5	and	and	CCONJ
afs-90955	208	6	chm	chm	NOUN
afs-90955	208	7	approaches	approach	NOUN
afs-90955	208	8	,	,	PUNCT
afs-90955	208	9	it	it	PRON
afs-90955	208	10	was	be	AUX
afs-90955	208	11	necessary	necessary	ADJ
afs-90955	208	12	to	to	PART
afs-90955	208	13	have	have	VERB
afs-90955	208	14	the	the	DET
afs-90955	208	15	sparse	sparse	ADJ
afs-90955	208	16	matrix	matrix	NOUN
afs-90955	208	17	a11	a11	PROPN
afs-90955	208	18	of	of	ADP
afs-90955	208	19	size	size	NOUN
afs-90955	208	20	1828434	1828434	NUM
afs-90955	208	21	,	,	PUNCT
afs-90955	208	22	i.e.	i.e.	X
afs-90955	208	23	,	,	PUNCT
afs-90955	208	24	number	number	NOUN
afs-90955	208	25	of	of	ADP
afs-90955	208	26	ancestors	ancestor	NOUN
afs-90955	208	27	to	to	ADP
afs-90955	208	28	the	the	DET
afs-90955	208	29	genotyped	genotype	VERB
afs-90955	208	30	animals	animal	NOUN
afs-90955	208	31	,	,	PUNCT
afs-90955	208	32	in	in	ADP
afs-90955	208	33	ram	ram	NOUN
afs-90955	208	34	.	.	PUNCT
afs-90955	209	1	the	the	DET
afs-90955	209	2	matrix	matrix	NOUN
afs-90955	209	3	was	be	AUX
afs-90955	209	4	stored	store	VERB
afs-90955	209	5	in	in	ADP
afs-90955	209	6	compressed	compress	VERB
afs-90955	209	7	sparse	sparse	ADJ
afs-90955	209	8	row	row	NOUN
afs-90955	209	9	format	format	NOUN
afs-90955	209	10	where	where	SCONJ
afs-90955	209	11	each	each	DET
afs-90955	209	12	non	non	ADJ
afs-90955	209	13	-	-	ADJ
afs-90955	209	14	zero	zero	ADJ
afs-90955	209	15	coefficient	coefficient	NOUN
afs-90955	209	16	value	value	NOUN
afs-90955	209	17	was	be	AUX
afs-90955	209	18	stored	store	VERB
afs-90955	209	19	in	in	ADP
afs-90955	209	20	a	a	DET
afs-90955	209	21	double	double	ADJ
afs-90955	209	22	precision	precision	NOUN
afs-90955	209	23	real	real	NOUN
afs-90955	209	24	and	and	CCONJ
afs-90955	209	25	its	its	PRON
afs-90955	209	26	column	column	NOUN
afs-90955	209	27	number	number	NOUN
afs-90955	209	28	in	in	ADP
afs-90955	209	29	a	a	DET
afs-90955	209	30	32	32	NUM
afs-90955	209	31	-	-	PUNCT
afs-90955	209	32	bit	bit	NOUN
afs-90955	209	33	integer	integer	NOUN
afs-90955	209	34	.	.	PUNCT
afs-90955	210	1	the	the	DET
afs-90955	210	2	number	number	NOUN
afs-90955	210	3	of	of	ADP
afs-90955	210	4	non	non	ADJ
afs-90955	210	5	-	-	ADJ
afs-90955	210	6	zero	zero	NUM
afs-90955	210	7	elements	element	NOUN
afs-90955	210	8	in	in	ADP
afs-90955	210	9	a11	a11	PROPN
afs-90955	210	10	was	be	AUX
afs-90955	210	11	4140064	4140064	NUM
afs-90955	210	12	.	.	PUNCT
afs-90955	211	1	thus	thus	ADV
afs-90955	211	2	,	,	PUNCT
afs-90955	211	3	less	less	ADJ
afs-90955	211	4	than	than	ADP
afs-90955	211	5	0.001	0.001	NUM
afs-90955	211	6	%	%	NOUN
afs-90955	211	7	of	of	ADP
afs-90955	211	8	the	the	DET
afs-90955	211	9	elements	element	NOUN
afs-90955	211	10	in	in	ADP
afs-90955	211	11	a11	a11	PROPN
afs-90955	211	12	were	be	AUX
afs-90955	211	13	non	non	ADJ
afs-90955	211	14	-	-	ADJ
afs-90955	211	15	zero	zero	NUM
afs-90955	211	16	.	.	PUNCT
afs-90955	212	1	the	the	DET
afs-90955	212	2	needed	need	VERB
afs-90955	212	3	additional	additional	ADJ
afs-90955	212	4	memory	memory	NOUN
afs-90955	212	5	due	due	ADP
afs-90955	212	6	to	to	ADP
afs-90955	212	7	this	this	DET
afs-90955	212	8	sparse	sparse	ADJ
afs-90955	212	9	matrix	matrix	NOUN
afs-90955	212	10	was	be	AUX
afs-90955	212	11	about	about	ADV
afs-90955	212	12	130	130	NUM
afs-90955	212	13	mb	mb	NOUN
afs-90955	212	14	(	(	PUNCT
afs-90955	212	15	table	table	NOUN
afs-90955	212	16	2	2	NUM
afs-90955	212	17	)	)	PUNCT
afs-90955	212	18	.	.	PUNCT
afs-90955	213	1	note	note	VERB
afs-90955	213	2	that	that	SCONJ
afs-90955	213	3	the	the	DET
afs-90955	213	4	memory	memory	NOUN
afs-90955	213	5	need	need	NOUN
afs-90955	213	6	of	of	ADP
afs-90955	213	7	130	130	NUM
afs-90955	213	8	mb	mb	NOUN
afs-90955	213	9	includes	include	VERB
afs-90955	213	10	also	also	ADV
afs-90955	213	11	some	some	DET
afs-90955	213	12	extra	extra	ADJ
afs-90955	213	13	memory	memory	NOUN
afs-90955	213	14	allocation	allocation	NOUN
afs-90955	213	15	for	for	ADP
afs-90955	213	16	the	the	DET
afs-90955	213	17	sparse	sparse	ADJ
afs-90955	213	18	matrix	matrix	NOUN
afs-90955	213	19	because	because	SCONJ
afs-90955	213	20	the	the	DET
afs-90955	213	21	space	space	NOUN
afs-90955	213	22	was	be	AUX
afs-90955	213	23	allocated	allocate	VERB
afs-90955	213	24	before	before	SCONJ
afs-90955	213	25	the	the	DET
afs-90955	213	26	actual	actual	ADJ
afs-90955	213	27	number	number	NOUN
afs-90955	213	28	of	of	ADP
afs-90955	213	29	non	non	NOUN
afs-90955	213	30	-	-	NOUN
afs-90955	213	31	zeros	zero	NOUN
afs-90955	213	32	in	in	ADP
afs-90955	213	33	the	the	DET
afs-90955	213	34	a11	a11	PROPN
afs-90955	213	35	matrix	matrix	NOUN
afs-90955	213	36	was	be	AUX
afs-90955	213	37	known	know	VERB
afs-90955	213	38	.	.	PUNCT
afs-90955	214	1	the	the	DET
afs-90955	214	2	i	i	PRON
afs-90955	214	3	m	m	VERB
afs-90955	214	4	approach	approach	NOUN
afs-90955	214	5	showed	show	VERB
afs-90955	214	6	some	some	DET
afs-90955	214	7	speed	speed	NOUN
afs-90955	214	8	benefit	benefit	NOUN
afs-90955	214	9	over	over	ADP
afs-90955	214	10	the	the	DET
afs-90955	214	11	other	other	ADJ
afs-90955	214	12	approaches	approach	NOUN
afs-90955	214	13	although	although	SCONJ
afs-90955	214	14	the	the	DET
afs-90955	214	15	total	total	ADJ
afs-90955	214	16	computing	computing	NOUN
afs-90955	214	17	time	time	NOUN
afs-90955	214	18	was	be	AUX
afs-90955	214	19	not	not	PART
afs-90955	214	20	much	much	ADV
afs-90955	214	21	affected	affected	ADJ
afs-90955	214	22	(	(	PUNCT
afs-90955	214	23	table	table	NOUN
afs-90955	214	24	2	2	NUM
afs-90955	214	25	)	)	PUNCT
afs-90955	214	26	.	.	PUNCT
afs-90955	215	1	table	table	NOUN
afs-90955	215	2	2	2	NUM
afs-90955	215	3	.	.	X
afs-90955	215	4	number	number	NOUN
afs-90955	215	5	of	of	ADP
afs-90955	215	6	pcg	pcg	PROPN
afs-90955	215	7	iterations	iteration	NOUN
afs-90955	215	8	(	(	PUNCT
afs-90955	215	9	n	n	CCONJ
afs-90955	215	10	)	)	PUNCT
afs-90955	215	11	,	,	PUNCT
afs-90955	215	12	wall	wall	NOUN
afs-90955	215	13	clock	clock	PROPN
afs-90955	215	14	time	time	NOUN
afs-90955	215	15	for	for	ADP
afs-90955	215	16	computing	compute	VERB
afs-90955	215	17	the	the	DET
afs-90955	215	18	c	c	NOUN
afs-90955	215	19	factor	factor	NOUN
afs-90955	215	20	(	(	PUNCT
afs-90955	215	21	tc	tc	NOUN
afs-90955	215	22	)	)	PUNCT
afs-90955	215	23	,	,	PUNCT
afs-90955	215	24	total	total	ADJ
afs-90955	215	25	wall	wall	NOUN
afs-90955	215	26	clock	clock	PROPN
afs-90955	215	27	time	time	NOUN
afs-90955	215	28	(	(	PUNCT
afs-90955	215	29	tt	tt	NOUN
afs-90955	215	30	)	)	PUNCT
afs-90955	215	31	and	and	CCONJ
afs-90955	215	32	peak	peak	NOUN
afs-90955	215	33	memory	memory	NOUN
afs-90955	215	34	use	use	NOUN
afs-90955	215	35	(	(	PUNCT
afs-90955	215	36	ram	ram	NOUN
afs-90955	215	37	)	)	PUNCT
afs-90955	215	38	in	in	ADP
afs-90955	215	39	single	single	ADJ
afs-90955	215	40	group	group	NOUN
afs-90955	215	41	allele	allele	PROPN
afs-90955	215	42	frequency	frequency	NOUN
afs-90955	215	43	estimation	estimation	NOUN
afs-90955	215	44	when	when	SCONJ
afs-90955	215	45	using	use	VERB
afs-90955	215	46	all	all	DET
afs-90955	215	47	genotypes	genotype	NOUN
afs-90955	215	48	and	and	CCONJ
afs-90955	215	49	computations	computation	NOUN
afs-90955	215	50	are	be	AUX
afs-90955	215	51	based	base	VERB
afs-90955	215	52	on	on	ADP
afs-90955	215	53	iteration	iteration	NOUN
afs-90955	215	54	on	on	ADP
afs-90955	215	55	pedigree	pedigree	ADJ
afs-90955	215	56	(	(	PUNCT
afs-90955	215	57	iop	iop	PROPN
afs-90955	215	58	)	)	PUNCT
afs-90955	215	59	,	,	PUNCT
afs-90955	215	60	iteration	iteration	NOUN
afs-90955	215	61	in	in	ADP
afs-90955	215	62	memory	memory	NOUN
afs-90955	215	63	(	(	PUNCT
afs-90955	215	64	i	i	NOUN
afs-90955	215	65	m	m	PROPN
afs-90955	215	66	)	)	PUNCT
afs-90955	215	67	,	,	PUNCT
afs-90955	215	68	or	or	CCONJ
afs-90955	215	69	sparse	sparse	VERB
afs-90955	215	70	cholesky	cholesky	ADJ
afs-90955	215	71	factorization	factorization	NOUN
afs-90955	215	72	(	(	PUNCT
afs-90955	215	73	chm	chm	NOUN
afs-90955	215	74	)	)	PUNCT
afs-90955	215	75	.	.	PUNCT
afs-90955	216	1	approach	approach	NOUN
afs-90955	216	2	n	n	PRON
afs-90955	216	3	iteration	iteration	NOUN
afs-90955	216	4	tc	tc	PROPN
afs-90955	216	5	(	(	PUNCT
afs-90955	216	6	min	min	NOUN
afs-90955	216	7	)	)	PUNCT
afs-90955	216	8	tt	tt	PROPN
afs-90955	216	9	(	(	PUNCT
afs-90955	216	10	min	min	PROPN
afs-90955	216	11	)	)	PUNCT
afs-90955	216	12	ram	ram	NOUN
afs-90955	216	13	(	(	PUNCT
afs-90955	216	14	gb	gb	NOUN
afs-90955	216	15	)	)	PUNCT
afs-90955	216	16	iop	iop	NOUN
afs-90955	216	17	400	400	NUM
afs-90955	216	18	1.18	1.18	NUM
afs-90955	216	19	52.5	52.5	NUM
afs-90955	216	20	0.67	0.67	NUM
afs-90955	217	1	i	i	PRON
afs-90955	217	2	m	m	VERB
afs-90955	217	3	381	381	NUM
afs-90955	217	4	0.32	0.32	NUM
afs-90955	217	5	50.9	50.9	NUM
afs-90955	217	6	0.80	0.80	NUM
afs-90955	217	7	chm	chm	NOUN
afs-90955	217	8	–	–	PUNCT
afs-90955	217	9	4.63	4.63	NUM
afs-90955	217	10	55.9	55.9	NUM
afs-90955	217	11	7.53	7.53	NUM
afs-90955	217	12	chm	chm	NOUN
afs-90955	217	13	,	,	PUNCT
afs-90955	217	14	parallel	parallel	ADJ
afs-90955	217	15	–	–	PUNCT
afs-90955	217	16	1.42	1.42	NUM
afs-90955	217	17	50.4	50.4	NUM
afs-90955	217	18	8.20	8.20	NUM
afs-90955	217	19	agricultural	agricultural	ADJ
afs-90955	217	20	and	and	CCONJ
afs-90955	217	21	food	food	NOUN
afs-90955	217	22	science	science	PROPN
afs-90955	217	23	i.	i.	PROPN
afs-90955	217	24	strandén	strandén	PROPN
afs-90955	217	25	&	&	CCONJ
afs-90955	217	26	e.a	e.a	PROPN
afs-90955	217	27	.	.	PROPN
afs-90955	217	28	mäntysaari	mäntysaari	PROPN
afs-90955	217	29	(	(	PUNCT
afs-90955	217	30	2020	2020	NUM
afs-90955	217	31	)	)	PUNCT
afs-90955	217	32	29	29	NUM
afs-90955	217	33	:	:	PUNCT
afs-90955	217	34	166–176	166–176	NUM
afs-90955	217	35	172	172	NUM
afs-90955	217	36	table	table	NOUN
afs-90955	217	37	3	3	NUM
afs-90955	217	38	illustrates	illustrate	VERB
afs-90955	217	39	the	the	DET
afs-90955	217	40	effect	effect	NOUN
afs-90955	217	41	of	of	ADP
afs-90955	217	42	increase	increase	NOUN
afs-90955	217	43	in	in	ADP
afs-90955	217	44	the	the	DET
afs-90955	217	45	number	number	NOUN
afs-90955	217	46	of	of	ADP
afs-90955	217	47	genotyped	genotype	VERB
afs-90955	217	48	animals	animal	NOUN
afs-90955	217	49	to	to	PART
afs-90955	217	50	peak	peak	VERB
afs-90955	217	51	ram	ram	NOUN
afs-90955	217	52	.	.	PUNCT
afs-90955	218	1	the	the	DET
afs-90955	218	2	iop	iop	NOUN
afs-90955	218	3	and	and	CCONJ
afs-90955	218	4	i	i	PRON
afs-90955	218	5	m	m	VERB
afs-90955	218	6	approaches	approach	NOUN
afs-90955	218	7	showed	show	VERB
afs-90955	218	8	only	only	ADV
afs-90955	218	9	a	a	DET
afs-90955	218	10	modest	modest	ADJ
afs-90955	218	11	increase	increase	NOUN
afs-90955	218	12	in	in	ADP
afs-90955	218	13	peak	peak	NOUN
afs-90955	218	14	ram	ram	NOUN
afs-90955	218	15	but	but	CCONJ
afs-90955	218	16	ram	ram	NOUN
afs-90955	218	17	increase	increase	NOUN
afs-90955	218	18	for	for	ADP
afs-90955	218	19	the	the	DET
afs-90955	218	20	chm	chm	NOUN
afs-90955	218	21	approach	approach	NOUN
afs-90955	218	22	was	be	AUX
afs-90955	218	23	faster	fast	ADJ
afs-90955	218	24	.	.	PUNCT
afs-90955	219	1	however	however	ADV
afs-90955	219	2	,	,	PUNCT
afs-90955	219	3	even	even	ADV
afs-90955	219	4	in	in	ADP
afs-90955	219	5	the	the	DET
afs-90955	219	6	chm	chm	NOUN
afs-90955	219	7	approach	approach	NOUN
afs-90955	219	8	,	,	PUNCT
afs-90955	219	9	the	the	DET
afs-90955	219	10	increase	increase	NOUN
afs-90955	219	11	in	in	ADP
afs-90955	219	12	peak	peak	NOUN
afs-90955	219	13	ram	ram	NOUN
afs-90955	219	14	was	be	AUX
afs-90955	219	15	quite	quite	ADV
afs-90955	219	16	linear	linear	ADJ
afs-90955	219	17	in	in	ADP
afs-90955	219	18	the	the	DET
afs-90955	219	19	number	number	NOUN
afs-90955	219	20	of	of	ADP
afs-90955	219	21	genotyped	genotype	VERB
afs-90955	219	22	animals	animal	NOUN
afs-90955	219	23	.	.	PUNCT
afs-90955	220	1	the	the	DET
afs-90955	220	2	chm	chm	NOUN
afs-90955	220	3	method	method	NOUN
afs-90955	220	4	is	be	AUX
afs-90955	220	5	based	base	VERB
afs-90955	220	6	on	on	ADP
afs-90955	220	7	a	a	DET
afs-90955	220	8	direct	direct	ADJ
afs-90955	220	9	solving	solving	NOUN
afs-90955	220	10	approach	approach	NOUN
afs-90955	220	11	where	where	SCONJ
afs-90955	220	12	reordering	reordering	NOUN
afs-90955	220	13	of	of	ADP
afs-90955	220	14	the	the	DET
afs-90955	220	15	equations	equation	NOUN
afs-90955	220	16	is	be	AUX
afs-90955	220	17	used	use	VERB
afs-90955	220	18	to	to	PART
afs-90955	220	19	minimize	minimize	VERB
afs-90955	220	20	both	both	CCONJ
afs-90955	220	21	the	the	DET
afs-90955	220	22	memory	memory	NOUN
afs-90955	220	23	use	use	NOUN
afs-90955	220	24	and	and	CCONJ
afs-90955	220	25	the	the	DET
afs-90955	220	26	number	number	NOUN
afs-90955	220	27	of	of	ADP
afs-90955	220	28	computations	computation	NOUN
afs-90955	220	29	in	in	ADP
afs-90955	220	30	the	the	DET
afs-90955	220	31	factorization	factorization	NOUN
afs-90955	220	32	and	and	CCONJ
afs-90955	220	33	solving	solve	VERB
afs-90955	220	34	steps	step	NOUN
afs-90955	220	35	.	.	PUNCT
afs-90955	221	1	the	the	DET
afs-90955	221	2	additional	additional	ADJ
afs-90955	221	3	ram	ram	NOUN
afs-90955	221	4	in	in	ADP
afs-90955	221	5	the	the	DET
afs-90955	221	6	chm	chm	NOUN
afs-90955	221	7	approach	approach	NOUN
afs-90955	221	8	over	over	ADP
afs-90955	221	9	the	the	DET
afs-90955	221	10	i	i	PROPN
afs-90955	221	11	m	m	VERB
afs-90955	221	12	approach	approach	NOUN
afs-90955	221	13	increased	increase	VERB
afs-90955	221	14	as	as	SCONJ
afs-90955	221	15	the	the	DET
afs-90955	221	16	number	number	NOUN
afs-90955	221	17	of	of	ADP
afs-90955	221	18	genotyped	genotype	VERB
afs-90955	221	19	animals	animal	NOUN
afs-90955	221	20	increased	increase	VERB
afs-90955	221	21	.	.	PUNCT
afs-90955	222	1	when	when	SCONJ
afs-90955	222	2	all	all	DET
afs-90955	222	3	1.50	1.50	NUM
afs-90955	222	4	million	million	NUM
afs-90955	222	5	genotyped	genotype	VERB
afs-90955	222	6	animals	animal	NOUN
afs-90955	222	7	were	be	AUX
afs-90955	222	8	used	use	VERB
afs-90955	222	9	in	in	ADP
afs-90955	222	10	the	the	DET
afs-90955	222	11	computations	computation	NOUN
afs-90955	222	12	,	,	PUNCT
afs-90955	222	13	the	the	DET
afs-90955	222	14	chm	chm	NOUN
afs-90955	222	15	method	method	NOUN
afs-90955	222	16	needed	need	VERB
afs-90955	222	17	ten	ten	NUM
afs-90955	222	18	times	time	NOUN
afs-90955	222	19	more	more	ADJ
afs-90955	222	20	memory	memory	NOUN
afs-90955	222	21	than	than	ADP
afs-90955	222	22	merely	merely	ADV
afs-90955	222	23	storing	store	VERB
afs-90955	222	24	the	the	DET
afs-90955	222	25	a11	a11	PROPN
afs-90955	222	26	matrix	matrix	NOUN
afs-90955	222	27	as	as	ADP
afs-90955	222	28	in	in	ADP
afs-90955	222	29	the	the	DET
afs-90955	222	30	i	i	PROPN
afs-90955	222	31	m	m	VERB
afs-90955	222	32	approach	approach	NOUN
afs-90955	222	33	(	(	PUNCT
afs-90955	222	34	table	table	NOUN
afs-90955	222	35	3	3	NUM
afs-90955	222	36	)	)	PUNCT
afs-90955	222	37	.	.	PUNCT
afs-90955	223	1	the	the	DET
afs-90955	223	2	subsets	subset	NOUN
afs-90955	223	3	of	of	ADP
afs-90955	223	4	genotyped	genotype	VERB
afs-90955	223	5	animals	animal	NOUN
afs-90955	223	6	in	in	ADP
afs-90955	223	7	table	table	NOUN
afs-90955	223	8	3	3	NUM
afs-90955	223	9	were	be	AUX
afs-90955	223	10	a	a	DET
afs-90955	223	11	random	random	ADJ
afs-90955	223	12	sample	sample	NOUN
afs-90955	223	13	from	from	ADP
afs-90955	223	14	the	the	DET
afs-90955	223	15	1.50	1.50	NUM
afs-90955	223	16	million	million	NUM
afs-90955	223	17	genotyped	genotyped	ADJ
afs-90955	223	18	animals	animal	NOUN
afs-90955	223	19	.	.	PUNCT
afs-90955	224	1	in	in	ADP
afs-90955	224	2	practice	practice	NOUN
afs-90955	224	3	,	,	PUNCT
afs-90955	224	4	number	number	NOUN
afs-90955	224	5	of	of	ADP
afs-90955	224	6	genotyped	genotype	VERB
afs-90955	224	7	animals	animal	NOUN
afs-90955	224	8	increases	increase	VERB
afs-90955	224	9	due	due	ADJ
afs-90955	224	10	to	to	ADP
afs-90955	224	11	genotyping	genotype	VERB
afs-90955	224	12	of	of	ADP
afs-90955	224	13	young	young	ADJ
afs-90955	224	14	animals	animal	NOUN
afs-90955	224	15	.	.	PUNCT
afs-90955	225	1	most	most	ADJ
afs-90955	225	2	of	of	ADP
afs-90955	225	3	the	the	DET
afs-90955	225	4	new	new	ADJ
afs-90955	225	5	genotyped	genotype	VERB
afs-90955	225	6	animals	animal	NOUN
afs-90955	225	7	can	can	AUX
afs-90955	225	8	be	be	AUX
afs-90955	225	9	expected	expect	VERB
afs-90955	225	10	to	to	PART
afs-90955	225	11	have	have	VERB
afs-90955	225	12	at	at	ADV
afs-90955	225	13	least	least	ADJ
afs-90955	225	14	one	one	NUM
afs-90955	225	15	of	of	ADP
afs-90955	225	16	the	the	DET
afs-90955	225	17	parents	parent	NOUN
afs-90955	225	18	genotyped	genotype	VERB
afs-90955	225	19	.	.	PUNCT
afs-90955	226	1	consequently	consequently	ADV
afs-90955	226	2	,	,	PUNCT
afs-90955	226	3	the	the	DET
afs-90955	226	4	number	number	NOUN
afs-90955	226	5	of	of	ADP
afs-90955	226	6	non	non	ADJ
afs-90955	226	7	-	-	ADJ
afs-90955	226	8	zero	zero	NUM
afs-90955	226	9	elements	element	NOUN
afs-90955	226	10	in	in	ADP
afs-90955	226	11	a11	a11	PROPN
afs-90955	226	12	can	can	AUX
afs-90955	226	13	be	be	AUX
afs-90955	226	14	expected	expect	VERB
afs-90955	226	15	to	to	PART
afs-90955	226	16	increase	increase	VERB
afs-90955	226	17	slowly	slowly	ADV
afs-90955	226	18	.	.	PUNCT
afs-90955	227	1	thus	thus	ADV
afs-90955	227	2	,	,	PUNCT
afs-90955	227	3	the	the	DET
afs-90955	227	4	i	i	PRON
afs-90955	227	5	m	m	VERB
afs-90955	227	6	approach	approach	NOUN
afs-90955	227	7	will	will	AUX
afs-90955	227	8	continue	continue	VERB
afs-90955	227	9	to	to	PART
afs-90955	227	10	have	have	VERB
afs-90955	227	11	a	a	DET
afs-90955	227	12	low	low	ADJ
afs-90955	227	13	memory	memory	NOUN
afs-90955	227	14	need	need	NOUN
afs-90955	227	15	and	and	CCONJ
afs-90955	227	16	the	the	DET
afs-90955	227	17	memory	memory	NOUN
afs-90955	227	18	increase	increase	NOUN
afs-90955	227	19	in	in	ADP
afs-90955	227	20	the	the	DET
afs-90955	227	21	chm	chm	NOUN
afs-90955	227	22	approach	approach	NOUN
afs-90955	227	23	can	can	AUX
afs-90955	227	24	be	be	AUX
afs-90955	227	25	expected	expect	VERB
afs-90955	227	26	to	to	PART
afs-90955	227	27	be	be	AUX
afs-90955	227	28	tolerable	tolerable	ADJ
afs-90955	227	29	in	in	ADP
afs-90955	227	30	the	the	DET
afs-90955	227	31	future	future	NOUN
afs-90955	227	32	(	(	PUNCT
afs-90955	227	33	masuda	masuda	PROPN
afs-90955	227	34	et	et	PROPN
afs-90955	227	35	al	al	PROPN
afs-90955	227	36	.	.	PROPN
afs-90955	227	37	2016	2016	NUM
afs-90955	227	38	,	,	PUNCT
afs-90955	227	39	taskinen	taskinen	PROPN
afs-90955	227	40	et	et	PROPN
afs-90955	227	41	al	al	PROPN
afs-90955	227	42	.	.	PROPN
afs-90955	227	43	2017	2017	NUM
afs-90955	227	44	)	)	PUNCT
afs-90955	227	45	.	.	PUNCT
afs-90955	228	1	in	in	ADP
afs-90955	228	2	the	the	DET
afs-90955	228	3	analysis	analysis	NOUN
afs-90955	228	4	of	of	ADP
afs-90955	228	5	our	our	PRON
afs-90955	228	6	data	data	NOUN
afs-90955	228	7	sets	set	NOUN
afs-90955	228	8	,	,	PUNCT
afs-90955	228	9	the	the	DET
afs-90955	228	10	number	number	NOUN
afs-90955	228	11	of	of	ADP
afs-90955	228	12	non	non	ADJ
afs-90955	228	13	-	-	ADJ
afs-90955	228	14	zero	zero	NUM
afs-90955	228	15	elements	element	NOUN
afs-90955	228	16	in	in	ADP
afs-90955	228	17	a11	a11	PROPN
afs-90955	228	18	matrix	matrix	NOUN
afs-90955	228	19	was	be	AUX
afs-90955	228	20	0.97	0.97	NUM
afs-90955	228	21	million	million	NUM
afs-90955	228	22	,	,	PUNCT
afs-90955	228	23	2.62	2.62	NUM
afs-90955	228	24	million	million	NUM
afs-90955	228	25	,	,	PUNCT
afs-90955	228	26	3.52	3.52	NUM
afs-90955	228	27	million	million	NUM
afs-90955	228	28	,	,	PUNCT
afs-90955	228	29	and	and	CCONJ
afs-90955	228	30	4.14	4.14	NUM
afs-90955	228	31	million	million	NUM
afs-90955	228	32	,	,	PUNCT
afs-90955	228	33	for	for	ADP
afs-90955	228	34	the	the	DET
afs-90955	228	35	cases	case	NOUN
afs-90955	228	36	of	of	ADP
afs-90955	228	37	0.10	0.10	NUM
afs-90955	228	38	,	,	PUNCT
afs-90955	228	39	0.50	0.50	NUM
afs-90955	228	40	,	,	PUNCT
afs-90955	228	41	1.00	1.00	NUM
afs-90955	228	42	and	and	CCONJ
afs-90955	228	43	1.50	1.50	NUM
afs-90955	228	44	million	million	NUM
afs-90955	228	45	genotyped	genotype	VERB
afs-90955	228	46	animals	animal	NOUN
afs-90955	228	47	,	,	PUNCT
afs-90955	228	48	respectively	respectively	ADV
afs-90955	228	49	.	.	PUNCT
afs-90955	229	1	thus	thus	ADV
afs-90955	229	2	,	,	PUNCT
afs-90955	229	3	number	number	NOUN
afs-90955	229	4	of	of	ADP
afs-90955	229	5	non	non	ADJ
afs-90955	229	6	-	-	ADJ
afs-90955	229	7	zero	zero	NUM
afs-90955	229	8	elements	element	NOUN
afs-90955	229	9	increased	increase	VERB
afs-90955	229	10	at	at	ADP
afs-90955	229	11	a	a	DET
afs-90955	229	12	slower	slow	ADJ
afs-90955	229	13	pace	pace	NOUN
afs-90955	229	14	than	than	ADP
afs-90955	229	15	the	the	DET
afs-90955	229	16	number	number	NOUN
afs-90955	229	17	of	of	ADP
afs-90955	229	18	genotyped	genotype	VERB
afs-90955	229	19	animals	animal	NOUN
afs-90955	229	20	.	.	PUNCT
afs-90955	230	1	performance	performance	NOUN
afs-90955	230	2	of	of	ADP
afs-90955	230	3	the	the	DET
afs-90955	230	4	approaches	approach	NOUN
afs-90955	230	5	adopted	adopt	VERB
afs-90955	230	6	in	in	ADP
afs-90955	230	7	this	this	DET
afs-90955	230	8	study	study	NOUN
afs-90955	230	9	to	to	PART
afs-90955	230	10	compute	compute	VERB
afs-90955	230	11	term	term	NOUN
afs-90955	230	12	(	(	PUNCT
afs-90955	230	13	a22	a22	PROPN
afs-90955	230	14	)	)	PUNCT
afs-90955	230	15	-1	-1	ADP
afs-90955	230	16	times	time	NOUN
afs-90955	230	17	a	a	DET
afs-90955	230	18	vector	vector	NOUN
afs-90955	230	19	has	have	AUX
afs-90955	230	20	been	be	AUX
afs-90955	230	21	investigated	investigate	VERB
afs-90955	230	22	in	in	ADP
afs-90955	230	23	solving	solve	VERB
afs-90955	230	24	mixed	mixed	ADJ
afs-90955	230	25	model	model	NOUN
afs-90955	230	26	equations	equation	NOUN
afs-90955	230	27	from	from	ADP
afs-90955	230	28	a	a	DET
afs-90955	230	29	ssgblup	ssgblup	ADJ
afs-90955	230	30	model	model	NOUN
afs-90955	230	31	.	.	PUNCT
afs-90955	231	1	strandén	strandén	PROPN
afs-90955	231	2	et	et	PROPN
afs-90955	231	3	al	al	PROPN
afs-90955	231	4	.	.	PROPN
afs-90955	232	1	(	(	PUNCT
afs-90955	232	2	2017	2017	NUM
afs-90955	232	3	)	)	PUNCT
afs-90955	232	4	used	use	VERB
afs-90955	232	5	pcg	pcg	PROPN
afs-90955	232	6	iteration	iteration	NOUN
afs-90955	232	7	to	to	PART
afs-90955	232	8	solve	solve	VERB
afs-90955	232	9	ssgblup	ssgblup	NOUN
afs-90955	232	10	.	.	PUNCT
afs-90955	233	1	in	in	ADP
afs-90955	233	2	regular	regular	ADJ
afs-90955	233	3	ssgblup	ssgblup	NOUN
afs-90955	233	4	,	,	PUNCT
afs-90955	233	5	the	the	DET
afs-90955	233	6	a22	a22	PROPN
afs-90955	233	7	matrix	matrix	NOUN
afs-90955	233	8	was	be	AUX
afs-90955	233	9	computed	compute	VERB
afs-90955	233	10	and	and	CCONJ
afs-90955	233	11	inverted	invert	VERB
afs-90955	233	12	.	.	PUNCT
afs-90955	234	1	the	the	DET
afs-90955	234	2	three	three	NUM
afs-90955	234	3	approaches	approach	NOUN
afs-90955	234	4	using	use	VERB
afs-90955	234	5	formula	formula	NOUN
afs-90955	234	6	[	[	X
afs-90955	234	7	5	5	NUM
afs-90955	234	8	]	]	PUNCT
afs-90955	234	9	for	for	ADP
afs-90955	234	10	(	(	PUNCT
afs-90955	234	11	a22	a22	PROPN
afs-90955	234	12	)	)	PUNCT
afs-90955	234	13	-1	-1	PUNCT
afs-90955	234	14	were	be	AUX
afs-90955	234	15	used	use	VERB
afs-90955	234	16	to	to	PART
afs-90955	234	17	decrease	decrease	VERB
afs-90955	234	18	total	total	ADJ
afs-90955	234	19	computing	computing	NOUN
afs-90955	234	20	time	time	NOUN
afs-90955	234	21	.	.	PUNCT
afs-90955	235	1	they	they	PRON
afs-90955	235	2	found	find	VERB
afs-90955	235	3	that	that	SCONJ
afs-90955	235	4	the	the	DET
afs-90955	235	5	solver	solver	NOUN
afs-90955	235	6	computing	computing	NOUN
afs-90955	235	7	time	time	NOUN
afs-90955	235	8	increased	increase	VERB
afs-90955	235	9	,	,	PUNCT
afs-90955	235	10	but	but	CCONJ
afs-90955	235	11	preprocessing	preprocessing	NOUN
afs-90955	235	12	time	time	NOUN
afs-90955	235	13	decreased	decrease	VERB
afs-90955	235	14	,	,	PUNCT
afs-90955	235	15	when	when	SCONJ
afs-90955	235	16	formula	formula	NOUN
afs-90955	235	17	[	[	X
afs-90955	235	18	5	5	NUM
afs-90955	235	19	]	]	PUNCT
afs-90955	235	20	was	be	AUX
afs-90955	235	21	used	use	VERB
afs-90955	235	22	.	.	PUNCT
afs-90955	236	1	time	time	NOUN
afs-90955	236	2	to	to	PART
afs-90955	236	3	solve	solve	VERB
afs-90955	236	4	mme	mme	NOUN
afs-90955	236	5	increased	increase	VERB
afs-90955	236	6	by	by	ADP
afs-90955	236	7	c.	c.	PROPN
afs-90955	236	8	25	25	NUM
afs-90955	236	9	%	%	NOUN
afs-90955	236	10	by	by	ADP
afs-90955	236	11	iop	iop	PROPN
afs-90955	236	12	,	,	PUNCT
afs-90955	236	13	c.	c.	PROPN
afs-90955	236	14	11	11	NUM
afs-90955	236	15	%	%	NOUN
afs-90955	236	16	by	by	ADP
afs-90955	236	17	i	i	PROPN
afs-90955	236	18	m	m	PROPN
afs-90955	236	19	,	,	PUNCT
afs-90955	236	20	and	and	CCONJ
afs-90955	236	21	c.	c.	PROPN
afs-90955	236	22	2	2	NUM
afs-90955	236	23	%	%	NOUN
afs-90955	236	24	by	by	ADP
afs-90955	236	25	chm	chm	NOUN
afs-90955	236	26	in	in	ADP
afs-90955	236	27	comparison	comparison	NOUN
afs-90955	236	28	to	to	ADP
afs-90955	236	29	the	the	DET
afs-90955	236	30	regular	regular	ADJ
afs-90955	236	31	ssgblup	ssgblup	NOUN
afs-90955	236	32	.	.	PUNCT
afs-90955	237	1	however	however	ADV
afs-90955	237	2	,	,	PUNCT
afs-90955	237	3	the	the	DET
afs-90955	237	4	total	total	ADJ
afs-90955	237	5	computing	computing	NOUN
afs-90955	237	6	time	time	NOUN
afs-90955	237	7	decreased	decrease	VERB
afs-90955	237	8	by	by	ADP
afs-90955	237	9	almost	almost	ADV
afs-90955	237	10	30	30	NUM
afs-90955	237	11	%	%	NOUN
afs-90955	237	12	when	when	SCONJ
afs-90955	237	13	using	use	VERB
afs-90955	237	14	chm	chm	NOUN
afs-90955	237	15	because	because	SCONJ
afs-90955	237	16	there	there	PRON
afs-90955	237	17	was	be	VERB
afs-90955	237	18	no	no	DET
afs-90955	237	19	need	need	NOUN
afs-90955	237	20	to	to	PART
afs-90955	237	21	make	make	VERB
afs-90955	237	22	and	and	CCONJ
afs-90955	237	23	invert	invert	VERB
afs-90955	237	24	a22	a22	PROPN
afs-90955	237	25	.	.	PUNCT
afs-90955	237	26	advantage	advantage	NOUN
afs-90955	237	27	of	of	ADP
afs-90955	237	28	the	the	DET
afs-90955	237	29	chm	chm	NOUN
afs-90955	237	30	approach	approach	NOUN
afs-90955	237	31	is	be	AUX
afs-90955	237	32	expected	expect	VERB
afs-90955	237	33	to	to	PART
afs-90955	237	34	increase	increase	VERB
afs-90955	237	35	,	,	PUNCT
afs-90955	237	36	when	when	SCONJ
afs-90955	237	37	the	the	DET
afs-90955	237	38	number	number	NOUN
afs-90955	237	39	of	of	ADP
afs-90955	237	40	genotyped	genotype	VERB
afs-90955	237	41	animals	animal	NOUN
afs-90955	237	42	increases	increase	VERB
afs-90955	237	43	because	because	SCONJ
afs-90955	237	44	computing	compute	VERB
afs-90955	237	45	time	time	NOUN
afs-90955	237	46	for	for	ADP
afs-90955	237	47	inverting	invert	VERB
afs-90955	237	48	a22	a22	PROPN
afs-90955	237	49	increases	increase	NOUN
afs-90955	237	50	qubically	qubically	ADV
afs-90955	237	51	in	in	ADP
afs-90955	237	52	number	number	NOUN
afs-90955	237	53	of	of	ADP
afs-90955	237	54	genotyped	genotype	VERB
afs-90955	237	55	animals	animal	NOUN
afs-90955	237	56	but	but	CCONJ
afs-90955	237	57	the	the	DET
afs-90955	237	58	increase	increase	NOUN
afs-90955	237	59	in	in	ADP
afs-90955	237	60	computing	computing	NOUN
afs-90955	237	61	time	time	NOUN
afs-90955	237	62	due	due	ADP
afs-90955	237	63	to	to	ADP
afs-90955	237	64	formula	formula	NOUN
afs-90955	237	65	[	[	X
afs-90955	237	66	5	5	NUM
afs-90955	237	67	]	]	PUNCT
afs-90955	237	68	is	be	AUX
afs-90955	237	69	linear	linear	ADJ
afs-90955	237	70	(	(	PUNCT
afs-90955	237	71	masuda	masuda	PROPN
afs-90955	237	72	et	et	PROPN
afs-90955	237	73	al	al	PROPN
afs-90955	237	74	.	.	PROPN
afs-90955	237	75	2016	2016	NUM
afs-90955	237	76	)	)	PUNCT
afs-90955	237	77	.	.	PUNCT
afs-90955	238	1	in	in	ADP
afs-90955	238	2	contrast	contrast	NOUN
afs-90955	238	3	,	,	PUNCT
afs-90955	238	4	in	in	ADP
afs-90955	238	5	the	the	DET
afs-90955	238	6	base	base	ADJ
afs-90955	238	7	population	population	NOUN
afs-90955	238	8	af	af	PROPN
afs-90955	238	9	estimation	estimation	PROPN
afs-90955	238	10	,	,	PUNCT
afs-90955	238	11	total	total	ADJ
afs-90955	238	12	computing	computing	NOUN
afs-90955	238	13	time	time	NOUN
afs-90955	238	14	by	by	ADP
afs-90955	238	15	the	the	DET
afs-90955	238	16	chm	chm	NOUN
afs-90955	238	17	approach	approach	NOUN
afs-90955	238	18	was	be	AUX
afs-90955	238	19	often	often	ADV
afs-90955	238	20	more	more	ADJ
afs-90955	238	21	than	than	ADP
afs-90955	238	22	by	by	ADP
afs-90955	238	23	the	the	DET
afs-90955	238	24	iop	iop	NOUN
afs-90955	238	25	and	and	CCONJ
afs-90955	238	26	i	i	PRON
afs-90955	238	27	m	m	VERB
afs-90955	238	28	approaches	approach	NOUN
afs-90955	238	29	because	because	SCONJ
afs-90955	238	30	the	the	DET
afs-90955	238	31	preprocessing	preprocessing	NOUN
afs-90955	238	32	time	time	NOUN
afs-90955	238	33	to	to	PART
afs-90955	238	34	make	make	VERB
afs-90955	238	35	the	the	DET
afs-90955	238	36	factorization	factorization	NOUN
afs-90955	238	37	was	be	AUX
afs-90955	238	38	substantial	substantial	ADJ
afs-90955	238	39	in	in	ADP
afs-90955	238	40	comparison	comparison	NOUN
afs-90955	238	41	to	to	ADP
afs-90955	238	42	the	the	DET
afs-90955	238	43	need	need	NOUN
afs-90955	238	44	to	to	PART
afs-90955	238	45	compute	compute	VERB
afs-90955	238	46	the	the	DET
afs-90955	238	47	c	c	PROPN
afs-90955	238	48	vector	vector	NOUN
afs-90955	238	49	only	only	ADV
afs-90955	238	50	once	once	ADV
afs-90955	238	51	.	.	PUNCT
afs-90955	239	1	aldridge	aldridge	PROPN
afs-90955	239	2	et	et	PROPN
afs-90955	239	3	al	al	PROPN
afs-90955	239	4	.	.	PROPN
afs-90955	240	1	(	(	PUNCT
afs-90955	240	2	2018	2018	NUM
afs-90955	240	3	)	)	PUNCT
afs-90955	240	4	estimated	estimate	VERB
afs-90955	240	5	base	base	NOUN
afs-90955	240	6	population	population	NOUN
afs-90955	240	7	af	af	VERB
afs-90955	240	8	using	use	VERB
afs-90955	240	9	the	the	DET
afs-90955	240	10	gls	gls	ADJ
afs-90955	240	11	method	method	NOUN
afs-90955	240	12	for	for	ADP
afs-90955	240	13	a	a	DET
afs-90955	240	14	single	single	ADJ
afs-90955	240	15	population	population	NOUN
afs-90955	240	16	.	.	PUNCT
afs-90955	241	1	they	they	PRON
afs-90955	241	2	compared	compare	VERB
afs-90955	241	3	a	a	DET
afs-90955	241	4	direct	direct	ADJ
afs-90955	241	5	sparsity	sparsity	NOUN
afs-90955	241	6	preserving	preserve	VERB
afs-90955	241	7	solving	solving	NOUN
afs-90955	241	8	approach	approach	NOUN
afs-90955	241	9	(	(	PUNCT
afs-90955	241	10	gls_sparse	gls_sparse	NOUN
afs-90955	241	11	)	)	PUNCT
afs-90955	241	12	similar	similar	ADJ
afs-90955	241	13	to	to	ADP
afs-90955	241	14	our	our	PRON
afs-90955	241	15	chm	chm	NOUN
afs-90955	241	16	approach	approach	NOUN
afs-90955	241	17	to	to	ADP
afs-90955	241	18	an	an	DET
afs-90955	241	19	approach	approach	NOUN
afs-90955	241	20	where	where	SCONJ
afs-90955	241	21	the	the	DET
afs-90955	241	22	matrix	matrix	NOUN
afs-90955	241	23	was	be	AUX
afs-90955	241	24	explicitly	explicitly	ADV
afs-90955	241	25	made	make	VERB
afs-90955	241	26	and	and	CCONJ
afs-90955	241	27	inverted	inverted	ADJ
afs-90955	241	28	(	(	PUNCT
afs-90955	241	29	gls_full	gls_full	NOUN
afs-90955	241	30	)	)	PUNCT
afs-90955	241	31	.	.	PUNCT
afs-90955	242	1	the	the	DET
afs-90955	242	2	gls_sparse	gls_sparse	NOUN
afs-90955	242	3	approach	approach	NOUN
afs-90955	242	4	needed	need	VERB
afs-90955	242	5	49	49	NUM
afs-90955	242	6	seconds	second	NOUN
afs-90955	242	7	and	and	CCONJ
afs-90955	242	8	1.3	1.3	NUM
afs-90955	242	9	gb	gb	NOUN
afs-90955	242	10	ram	ram	NOUN
afs-90955	242	11	with	with	ADP
afs-90955	242	12	1,670	1,670	NUM
afs-90955	242	13	snp	snp	ADJ
afs-90955	242	14	markers	marker	NOUN
afs-90955	242	15	from	from	ADP
afs-90955	242	16	100,078	100,078	NUM
afs-90955	242	17	genotyped	genotyped	ADJ
afs-90955	242	18	animals	animal	NOUN
afs-90955	242	19	.	.	PUNCT
afs-90955	243	1	the	the	DET
afs-90955	243	2	gls_full	gls_full	ADJ
afs-90955	243	3	approach	approach	NOUN
afs-90955	243	4	needed	need	VERB
afs-90955	243	5	about	about	ADP
afs-90955	243	6	32	32	NUM
afs-90955	243	7	h	h	NOUN
afs-90955	243	8	and	and	CCONJ
afs-90955	243	9	118.2	118.2	NUM
afs-90955	243	10	gb	gb	NOUN
afs-90955	243	11	of	of	ADP
afs-90955	243	12	ram	ram	NOUN
afs-90955	243	13	.	.	PUNCT
afs-90955	244	1	when	when	SCONJ
afs-90955	244	2	the	the	DET
afs-90955	244	3	number	number	NOUN
afs-90955	244	4	of	of	ADP
afs-90955	244	5	markers	marker	NOUN
afs-90955	244	6	was	be	AUX
afs-90955	244	7	increased	increase	VERB
afs-90955	244	8	to	to	ADP
afs-90955	244	9	50,100	50,100	NUM
afs-90955	244	10	,	,	PUNCT
afs-90955	244	11	the	the	DET
afs-90955	244	12	gls_sparse	gls_sparse	NOUN
afs-90955	244	13	approach	approach	NOUN
afs-90955	244	14	took	take	VERB
afs-90955	244	15	6	6	NUM
afs-90955	244	16	minutes	minute	NOUN
afs-90955	244	17	and	and	CCONJ
afs-90955	244	18	37.6	37.6	NUM
afs-90955	244	19	gb	gb	NOUN
afs-90955	244	20	of	of	ADP
afs-90955	244	21	ram	ram	NOUN
afs-90955	244	22	.	.	PUNCT
afs-90955	245	1	these	these	DET
afs-90955	245	2	numbers	number	NOUN
afs-90955	245	3	support	support	VERB
afs-90955	245	4	the	the	DET
afs-90955	245	5	conclusion	conclusion	NOUN
afs-90955	245	6	that	that	SCONJ
afs-90955	245	7	the	the	DET
afs-90955	245	8	implemented	implement	VERB
afs-90955	245	9	implicit	implicit	ADJ
afs-90955	245	10	computing	computing	NOUN
afs-90955	245	11	approach	approach	NOUN
afs-90955	245	12	for	for	ADP
afs-90955	245	13	the	the	DET
afs-90955	245	14	a22	a22	PROPN
afs-90955	245	15	matrix	matrix	NOUN
afs-90955	245	16	is	be	AUX
afs-90955	245	17	efficient	efficient	ADJ
afs-90955	245	18	.	.	PUNCT
afs-90955	246	1	the	the	DET
afs-90955	246	2	smaller	small	ADJ
afs-90955	246	3	memory	memory	NOUN
afs-90955	246	4	need	need	NOUN
afs-90955	246	5	by	by	ADP
afs-90955	246	6	the	the	DET
afs-90955	246	7	bpop	bpop	ADJ
afs-90955	246	8	program	program	NOUN
afs-90955	246	9	than	than	SCONJ
afs-90955	246	10	the	the	DET
afs-90955	246	11	gls_sparse	gls_sparse	NOUN
afs-90955	246	12	approach	approach	NOUN
afs-90955	246	13	in	in	ADP
afs-90955	246	14	the	the	DET
afs-90955	246	15	100,000	100,000	NUM
afs-90955	246	16	genotyped	genotype	VERB
afs-90955	246	17	case	case	NOUN
afs-90955	246	18	can	can	AUX
afs-90955	246	19	be	be	AUX
afs-90955	246	20	due	due	ADJ
afs-90955	246	21	to	to	ADP
afs-90955	246	22	differences	difference	NOUN
afs-90955	246	23	in	in	ADP
afs-90955	246	24	the	the	DET
afs-90955	246	25	direct	direct	ADJ
afs-90955	246	26	solver	solver	NOUN
afs-90955	246	27	or	or	CCONJ
afs-90955	246	28	having	have	VERB
afs-90955	246	29	the	the	DET
afs-90955	246	30	m	m	PROPN
afs-90955	246	31	matrix	matrix	NOUN
afs-90955	246	32	in	in	ADP
afs-90955	246	33	memory	memory	NOUN
afs-90955	246	34	or	or	CCONJ
afs-90955	246	35	other	other	ADJ
afs-90955	246	36	reasons	reason	NOUN
afs-90955	246	37	.	.	PUNCT
afs-90955	247	1	thus	thus	ADV
afs-90955	247	2	,	,	PUNCT
afs-90955	247	3	direct	direct	ADJ
afs-90955	247	4	comparison	comparison	NOUN
afs-90955	247	5	of	of	ADP
afs-90955	247	6	programs	program	NOUN
afs-90955	247	7	should	should	AUX
afs-90955	247	8	be	be	AUX
afs-90955	247	9	treated	treat	VERB
afs-90955	247	10	with	with	ADP
afs-90955	247	11	caution	caution	NOUN
afs-90955	247	12	.	.	PUNCT
afs-90955	248	1	we	we	PRON
afs-90955	248	2	did	do	AUX
afs-90955	248	3	not	not	PART
afs-90955	248	4	consider	consider	VERB
afs-90955	248	5	any	any	DET
afs-90955	248	6	approach	approach	NOUN
afs-90955	248	7	where	where	SCONJ
afs-90955	248	8	the	the	DET
afs-90955	248	9	a22	a22	PROPN
afs-90955	248	10	matrix	matrix	NOUN
afs-90955	248	11	would	would	AUX
afs-90955	248	12	be	be	AUX
afs-90955	248	13	formed	form	VERB
afs-90955	248	14	explicitly	explicitly	ADV
afs-90955	248	15	because	because	SCONJ
afs-90955	248	16	the	the	DET
afs-90955	248	17	number	number	NOUN
afs-90955	248	18	of	of	ADP
afs-90955	248	19	genotyped	genotype	VERB
afs-90955	248	20	animals	animal	NOUN
afs-90955	248	21	in	in	ADP
afs-90955	248	22	our	our	PRON
afs-90955	248	23	data	datum	NOUN
afs-90955	248	24	was	be	AUX
afs-90955	248	25	so	so	ADV
afs-90955	248	26	large	large	ADJ
afs-90955	248	27	.	.	PUNCT
afs-90955	249	1	in	in	ADP
afs-90955	249	2	practice	practice	NOUN
afs-90955	249	3	,	,	PUNCT
afs-90955	249	4	when	when	SCONJ
afs-90955	249	5	the	the	DET
afs-90955	249	6	number	number	NOUN
afs-90955	249	7	of	of	ADP
afs-90955	249	8	genotyped	genotype	VERB
afs-90955	249	9	animals	animal	NOUN
afs-90955	249	10	increases	increase	VERB
afs-90955	249	11	sufficiently	sufficiently	ADV
afs-90955	249	12	,	,	PUNCT
afs-90955	249	13	preprocessing	preprocesse	VERB
afs-90955	249	14	time	time	NOUN
afs-90955	249	15	to	to	PART
afs-90955	249	16	make	make	VERB
afs-90955	249	17	a22	a22	PROPN
afs-90955	249	18	becomes	become	VERB
afs-90955	249	19	unfeasible	unfeasible	ADJ
afs-90955	249	20	due	due	ADP
afs-90955	249	21	to	to	ADP
afs-90955	249	22	the	the	DET
afs-90955	249	23	large	large	ADJ
afs-90955	249	24	memory	memory	NOUN
afs-90955	249	25	requirements	requirement	NOUN
afs-90955	249	26	.	.	PUNCT
afs-90955	250	1	for	for	ADP
afs-90955	250	2	example	example	NOUN
afs-90955	250	3	,	,	PUNCT
afs-90955	250	4	when	when	SCONJ
afs-90955	250	5	genotypes	genotype	NOUN
afs-90955	250	6	are	be	AUX
afs-90955	250	7	available	available	ADJ
afs-90955	250	8	from	from	ADP
afs-90955	250	9	1.5	1.5	NUM
afs-90955	250	10	million	million	NUM
afs-90955	250	11	animals	animal	NOUN
afs-90955	250	12	,	,	PUNCT
afs-90955	250	13	dense	dense	ADJ
afs-90955	250	14	square	square	ADJ
afs-90955	250	15	matrix	matrix	NOUN
afs-90955	250	16	of	of	ADP
afs-90955	250	17	the	the	DET
afs-90955	250	18	size	size	NOUN
afs-90955	250	19	1.5	1.5	NUM
afs-90955	250	20	million	million	NUM
afs-90955	250	21	stored	store	VERB
afs-90955	250	22	in	in	ADP
afs-90955	250	23	double	double	ADJ
afs-90955	250	24	precision	precision	NOUN
afs-90955	250	25	would	would	AUX
afs-90955	250	26	take	take	VERB
afs-90955	250	27	about	about	ADV
afs-90955	250	28	18	18	NUM
afs-90955	250	29	terabytes	terabyte	NOUN
afs-90955	250	30	.	.	PUNCT
afs-90955	251	1	when	when	SCONJ
afs-90955	251	2	a	a	DET
afs-90955	251	3	dense	dense	ADJ
afs-90955	251	4	lower	low	ADJ
afs-90955	251	5	triangle	triangle	NOUN
afs-90955	251	6	or	or	CCONJ
afs-90955	251	7	packed	pack	VERB
afs-90955	251	8	matrix	matrix	NOUN
afs-90955	251	9	is	be	AUX
afs-90955	251	10	used	use	VERB
afs-90955	251	11	,	,	PUNCT
afs-90955	251	12	storing	store	VERB
afs-90955	251	13	the	the	DET
afs-90955	251	14	a22	a22	NOUN
afs-90955	251	15	matrix	matrix	NOUN
afs-90955	251	16	in	in	ADP
afs-90955	251	17	single	single	ADJ
afs-90955	251	18	precision	precision	NOUN
afs-90955	251	19	would	would	AUX
afs-90955	251	20	still	still	ADV
afs-90955	251	21	require	require	VERB
afs-90955	251	22	4.5	4.5	NUM
afs-90955	251	23	terabytes	terabyte	NOUN
afs-90955	251	24	.	.	PUNCT
afs-90955	252	1	table	table	NOUN
afs-90955	252	2	3	3	NUM
afs-90955	252	3	.	.	PUNCT
afs-90955	252	4	total	total	ADJ
afs-90955	252	5	wall	wall	PROPN
afs-90955	252	6	clock	clock	PROPN
afs-90955	252	7	time	time	NOUN
afs-90955	252	8	in	in	ADP
afs-90955	252	9	minutes	minute	NOUN
afs-90955	252	10	(	(	PUNCT
afs-90955	252	11	tt	tt	PROPN
afs-90955	252	12	)	)	PUNCT
afs-90955	252	13	and	and	CCONJ
afs-90955	252	14	peak	peak	NOUN
afs-90955	252	15	memory	memory	NOUN
afs-90955	252	16	use	use	NOUN
afs-90955	252	17	in	in	ADP
afs-90955	252	18	giga	giga	PROPN
afs-90955	252	19	bytes	byte	NOUN
afs-90955	252	20	(	(	PUNCT
afs-90955	252	21	ram	ram	NOUN
afs-90955	252	22	)	)	PUNCT
afs-90955	252	23	in	in	ADP
afs-90955	252	24	single	single	ADJ
afs-90955	252	25	group	group	NOUN
afs-90955	252	26	allele	allele	PROPN
afs-90955	252	27	frequency	frequency	NOUN
afs-90955	252	28	estimation	estimation	NOUN
afs-90955	252	29	when	when	SCONJ
afs-90955	252	30	number	number	NOUN
afs-90955	252	31	of	of	ADP
afs-90955	252	32	genotyped	genotype	VERB
afs-90955	252	33	animals	animal	NOUN
afs-90955	252	34	was	be	AUX
afs-90955	252	35	100,000	100,000	NUM
afs-90955	252	36	(	(	PUNCT
afs-90955	252	37	100k	100k	NUM
afs-90955	252	38	)	)	PUNCT
afs-90955	252	39	,	,	PUNCT
afs-90955	252	40	500,000	500,000	NUM
afs-90955	252	41	(	(	PUNCT
afs-90955	252	42	500k	500k	NUM
afs-90955	252	43	)	)	PUNCT
afs-90955	252	44	,	,	PUNCT
afs-90955	252	45	1,000,000	1,000,000	NUM
afs-90955	252	46	(	(	PUNCT
afs-90955	252	47	1	1	NUM
afs-90955	252	48	m	m	NOUN
afs-90955	252	49	)	)	PUNCT
afs-90955	252	50	,	,	PUNCT
afs-90955	252	51	and	and	CCONJ
afs-90955	252	52	1,500,000	1,500,000	NUM
afs-90955	252	53	(	(	PUNCT
afs-90955	252	54	1.5	1.5	NUM
afs-90955	252	55	m	m	NOUN
afs-90955	252	56	)	)	PUNCT
afs-90955	252	57	,	,	PUNCT
afs-90955	252	58	and	and	CCONJ
afs-90955	252	59	computations	computation	NOUN
afs-90955	252	60	use	use	VERB
afs-90955	252	61	iteration	iteration	NOUN
afs-90955	252	62	on	on	ADP
afs-90955	252	63	pedigree	pedigree	ADJ
afs-90955	252	64	(	(	PUNCT
afs-90955	252	65	iop	iop	PROPN
afs-90955	252	66	)	)	PUNCT
afs-90955	252	67	,	,	PUNCT
afs-90955	252	68	iteration	iteration	NOUN
afs-90955	252	69	in	in	ADP
afs-90955	252	70	memory	memory	NOUN
afs-90955	252	71	(	(	PUNCT
afs-90955	252	72	i	i	NOUN
afs-90955	252	73	m	m	PROPN
afs-90955	252	74	)	)	PUNCT
afs-90955	252	75	,	,	PUNCT
afs-90955	252	76	or	or	CCONJ
afs-90955	252	77	sparse	sparse	VERB
afs-90955	252	78	cholesky	cholesky	ADJ
afs-90955	252	79	factorization	factorization	NOUN
afs-90955	252	80	(	(	PUNCT
afs-90955	252	81	chm	chm	NOUN
afs-90955	252	82	)	)	PUNCT
afs-90955	252	83	.	.	PUNCT
afs-90955	253	1	100k	100k	NUM
afs-90955	253	2	500k	500k	NUM
afs-90955	253	3	1	1	NUM
afs-90955	253	4	m	m	NUM
afs-90955	253	5	1.5	1.5	NUM
afs-90955	253	6	m	m	NOUN
afs-90955	253	7	approach	approach	NOUN
afs-90955	253	8	tt	tt	PROPN
afs-90955	253	9	ram	ram	VERB
afs-90955	253	10	tt	tt	PROPN
afs-90955	253	11	ram	ram	VERB
afs-90955	253	12	tt	tt	PRON
afs-90955	253	13	ram	ram	VERB
afs-90955	253	14	tt	tt	PROPN
afs-90955	253	15	ram	ram	VERB
afs-90955	253	16	iop	iop	PROPN
afs-90955	253	17	3.7	3.7	NUM
afs-90955	253	18	0.63	0.63	NUM
afs-90955	253	19	17.4	17.4	NUM
afs-90955	253	20	0.63	0.63	NUM
afs-90955	253	21	35.0	35.0	NUM
afs-90955	253	22	0.63	0.63	NUM
afs-90955	253	23	55.0	55.0	NUM
afs-90955	253	24	0.67	0.67	NUM
afs-90955	254	1	i	i	PRON
afs-90955	254	2	m	m	VERB
afs-90955	254	3	3.7	3.7	NUM
afs-90955	254	4	0.63	0.63	NUM
afs-90955	254	5	16.5	16.5	NUM
afs-90955	254	6	0.65	0.65	NUM
afs-90955	254	7	32.5	32.5	NUM
afs-90955	254	8	0.73	0.73	NUM
afs-90955	254	9	50.9	50.9	NUM
afs-90955	254	10	0.80	0.80	NUM
afs-90955	254	11	chm	chm	NOUN
afs-90955	254	12	3.8	3.8	NUM
afs-90955	254	13	0.95	0.95	NUM
afs-90955	254	14	17.5	17.5	NUM
afs-90955	254	15	3.20	3.20	NUM
afs-90955	254	16	34.8	34.8	NUM
afs-90955	254	17	5.53	5.53	NUM
afs-90955	254	18	55.9	55.9	NUM
afs-90955	254	19	7.53	7.53	NUM
afs-90955	254	20	agricultural	agricultural	ADJ
afs-90955	254	21	and	and	CCONJ
afs-90955	254	22	food	food	NOUN
afs-90955	254	23	science	science	PROPN
afs-90955	254	24	i.	i.	PROPN
afs-90955	254	25	strandén	strandén	PROPN
afs-90955	254	26	&	&	CCONJ
afs-90955	254	27	e.a	e.a	PROPN
afs-90955	254	28	.	.	PROPN
afs-90955	254	29	mäntysaari	mäntysaari	PROPN
afs-90955	254	30	(	(	PUNCT
afs-90955	254	31	2020	2020	NUM
afs-90955	254	32	)	)	PUNCT
afs-90955	254	33	29	29	NUM
afs-90955	254	34	:	:	PUNCT
afs-90955	254	35	166–176	166–176	NUM
afs-90955	254	36	173	173	NUM
afs-90955	254	37	in	in	ADP
afs-90955	254	38	this	this	DET
afs-90955	254	39	study	study	NOUN
afs-90955	254	40	,	,	PUNCT
afs-90955	254	41	benefits	benefit	NOUN
afs-90955	254	42	of	of	ADP
afs-90955	254	43	using	use	VERB
afs-90955	254	44	parallel	parallel	ADJ
afs-90955	254	45	computing	computing	NOUN
afs-90955	254	46	were	be	AUX
afs-90955	254	47	small	small	ADJ
afs-90955	254	48	(	(	PUNCT
afs-90955	254	49	table	table	NOUN
afs-90955	254	50	2	2	NUM
afs-90955	254	51	)	)	PUNCT
afs-90955	254	52	.	.	PUNCT
afs-90955	255	1	the	the	DET
afs-90955	255	2	cholmod	cholmod	PROPN
afs-90955	255	3	library	library	NOUN
afs-90955	255	4	can	can	AUX
afs-90955	255	5	be	be	AUX
afs-90955	255	6	compiled	compile	VERB
afs-90955	255	7	to	to	PART
afs-90955	255	8	use	use	VERB
afs-90955	255	9	one	one	NUM
afs-90955	255	10	cpu	cpu	NOUN
afs-90955	255	11	or	or	CCONJ
afs-90955	255	12	several	several	ADJ
afs-90955	255	13	cpus	cpu	NOUN
afs-90955	255	14	.	.	PUNCT
afs-90955	256	1	thus	thus	ADV
afs-90955	256	2	,	,	PUNCT
afs-90955	256	3	it	it	PRON
afs-90955	256	4	allows	allow	VERB
afs-90955	256	5	exploiting	exploit	VERB
afs-90955	256	6	parallel	parallel	ADJ
afs-90955	256	7	computing	computing	NOUN
afs-90955	256	8	.	.	PUNCT
afs-90955	257	1	parallel	parallel	ADJ
afs-90955	257	2	computing	computing	NOUN
afs-90955	257	3	decreased	decrease	VERB
afs-90955	257	4	time	time	NOUN
afs-90955	257	5	in	in	ADP
afs-90955	257	6	the	the	DET
afs-90955	257	7	cholmod	cholmod	PROPN
afs-90955	257	8	computing	computing	NOUN
afs-90955	257	9	steps	step	NOUN
afs-90955	257	10	but	but	CCONJ
afs-90955	257	11	,	,	PUNCT
afs-90955	257	12	as	as	SCONJ
afs-90955	257	13	already	already	ADV
afs-90955	257	14	noticed	notice	VERB
afs-90955	257	15	,	,	PUNCT
afs-90955	257	16	this	this	DET
afs-90955	257	17	step	step	NOUN
afs-90955	257	18	takes	take	VERB
afs-90955	257	19	only	only	ADV
afs-90955	257	20	a	a	DET
afs-90955	257	21	fraction	fraction	NOUN
afs-90955	257	22	of	of	ADP
afs-90955	257	23	the	the	DET
afs-90955	257	24	total	total	ADJ
afs-90955	257	25	computing	computing	NOUN
afs-90955	257	26	time	time	NOUN
afs-90955	257	27	.	.	PUNCT
afs-90955	258	1	in	in	ADP
afs-90955	258	2	addition	addition	NOUN
afs-90955	258	3	to	to	ADP
afs-90955	258	4	the	the	DET
afs-90955	258	5	parallel	parallel	ADJ
afs-90955	258	6	cholmod	cholmod	PROPN
afs-90955	258	7	,	,	PUNCT
afs-90955	258	8	we	we	PRON
afs-90955	258	9	tested	test	VERB
afs-90955	258	10	parallel	parallel	ADJ
afs-90955	258	11	computing	computing	NOUN
afs-90955	258	12	in	in	ADP
afs-90955	258	13	the	the	DET
afs-90955	258	14	af	af	PROPN
afs-90955	258	15	estimation	estimation	NOUN
afs-90955	258	16	by	by	ADP
afs-90955	258	17	using	use	VERB
afs-90955	258	18	parallel	parallel	ADJ
afs-90955	258	19	versions	version	NOUN
afs-90955	258	20	of	of	ADP
afs-90955	258	21	daxpy	daxpy	NOUN
afs-90955	258	22	and	and	CCONJ
afs-90955	258	23	dgemv	dgemv	PROPN
afs-90955	258	24	subroutines	subroutine	NOUN
afs-90955	258	25	available	available	ADJ
afs-90955	258	26	in	in	ADP
afs-90955	258	27	lapack	lapack	PROPN
afs-90955	258	28	/	/	SYM
afs-90955	258	29	blas	blas	PROPN
afs-90955	258	30	from	from	ADP
afs-90955	258	31	the	the	DET
afs-90955	258	32	intel	intel	PROPN
afs-90955	258	33	math	math	PROPN
afs-90955	258	34	kernel	kernel	PROPN
afs-90955	258	35	library	library	PROPN
afs-90955	258	36	©	©	PROPN
afs-90955	258	37	(	(	PUNCT
afs-90955	258	38	intel	intel	PROPN
afs-90955	258	39	math	math	PROPN
afs-90955	258	40	kernel	kernel	PROPN
afs-90955	258	41	library	library	PROPN
afs-90955	258	42	reference	reference	NOUN
afs-90955	258	43	manual	manual	NOUN
afs-90955	258	44	,	,	PUNCT
afs-90955	258	45	2014	2014	NUM
afs-90955	258	46	)	)	PUNCT
afs-90955	258	47	.	.	PUNCT
afs-90955	259	1	parallel	parallel	ADJ
afs-90955	259	2	computing	computing	NOUN
afs-90955	259	3	did	do	AUX
afs-90955	259	4	not	not	PART
afs-90955	259	5	give	give	VERB
afs-90955	259	6	much	much	ADJ
afs-90955	259	7	advantage	advantage	NOUN
afs-90955	259	8	here	here	ADV
afs-90955	259	9	either	either	ADV
afs-90955	259	10	.	.	PUNCT
afs-90955	260	1	in	in	ADP
afs-90955	260	2	the	the	DET
afs-90955	260	3	current	current	ADJ
afs-90955	260	4	implementation	implementation	NOUN
afs-90955	260	5	,	,	PUNCT
afs-90955	260	6	one	one	NUM
afs-90955	260	7	row	row	NOUN
afs-90955	260	8	of	of	ADP
afs-90955	260	9	m	m	PROPN
afs-90955	260	10	is	be	AUX
afs-90955	260	11	in	in	ADP
afs-90955	260	12	memory	memory	NOUN
afs-90955	260	13	at	at	ADP
afs-90955	260	14	a	a	DET
afs-90955	260	15	time	time	NOUN
afs-90955	260	16	which	which	PRON
afs-90955	260	17	leads	lead	VERB
afs-90955	260	18	to	to	ADP
afs-90955	260	19	calling	call	VERB
afs-90955	260	20	the	the	DET
afs-90955	260	21	parallel	parallel	ADJ
afs-90955	260	22	subroutines	subroutine	NOUN
afs-90955	260	23	as	as	ADP
afs-90955	260	24	many	many	ADJ
afs-90955	260	25	times	time	NOUN
afs-90955	260	26	as	as	SCONJ
afs-90955	260	27	there	there	PRON
afs-90955	260	28	are	be	VERB
afs-90955	260	29	genotyped	genotyped	ADJ
afs-90955	260	30	animals	animal	NOUN
afs-90955	260	31	.	.	PUNCT
afs-90955	261	1	benefits	benefit	NOUN
afs-90955	261	2	from	from	ADP
afs-90955	261	3	parallel	parallel	ADJ
afs-90955	261	4	computing	computing	NOUN
afs-90955	261	5	are	be	AUX
afs-90955	261	6	likely	likely	ADJ
afs-90955	261	7	to	to	PART
afs-90955	261	8	be	be	AUX
afs-90955	261	9	larger	large	ADJ
afs-90955	261	10	when	when	SCONJ
afs-90955	261	11	the	the	DET
afs-90955	261	12	full	full	ADJ
afs-90955	261	13	m	m	NOUN
afs-90955	261	14	matrix	matrix	NOUN
afs-90955	261	15	is	be	AUX
afs-90955	261	16	in	in	ADP
afs-90955	261	17	ram	ram	NOUN
afs-90955	261	18	as	as	ADP
afs-90955	261	19	in	in	ADP
afs-90955	261	20	aldridge	aldridge	PROPN
afs-90955	261	21	et	et	PROPN
afs-90955	261	22	al	al	PROPN
afs-90955	261	23	.	.	PROPN
afs-90955	262	1	(	(	PUNCT
afs-90955	262	2	2018	2018	NUM
afs-90955	262	3	)	)	PUNCT
afs-90955	262	4	.	.	PUNCT
afs-90955	263	1	then	then	ADV
afs-90955	263	2	,	,	PUNCT
afs-90955	263	3	one	one	NUM
afs-90955	263	4	matrix	matrix	NOUN
afs-90955	263	5	times	time	NOUN
afs-90955	263	6	matrix	matrix	NOUN
afs-90955	263	7	product	product	NOUN
afs-90955	263	8	using	use	VERB
afs-90955	263	9	dgemm	dgemm	NOUN
afs-90955	263	10	or	or	CCONJ
afs-90955	263	11	sgemm	sgemm	NOUN
afs-90955	263	12	subroutine	subroutine	NOUN
afs-90955	263	13	call	call	NOUN
afs-90955	263	14	can	can	AUX
afs-90955	263	15	be	be	AUX
afs-90955	263	16	used	use	VERB
afs-90955	263	17	and	and	CCONJ
afs-90955	263	18	,	,	PUNCT
afs-90955	263	19	thus	thus	ADV
afs-90955	263	20	,	,	PUNCT
afs-90955	263	21	the	the	DET
afs-90955	263	22	parallel	parallel	ADJ
afs-90955	263	23	subroutines	subroutine	NOUN
afs-90955	263	24	use	use	VERB
afs-90955	263	25	data	datum	NOUN
afs-90955	263	26	from	from	ADP
afs-90955	263	27	all	all	DET
afs-90955	263	28	animals	animal	NOUN
afs-90955	263	29	simultaneously	simultaneously	ADV
afs-90955	263	30	.	.	PUNCT
afs-90955	264	1	however	however	ADV
afs-90955	264	2	,	,	PUNCT
afs-90955	264	3	having	have	VERB
afs-90955	264	4	the	the	DET
afs-90955	264	5	m	m	PROPN
afs-90955	264	6	matrix	matrix	NOUN
afs-90955	264	7	in	in	ADP
afs-90955	264	8	ram	ram	NOUN
afs-90955	264	9	would	would	AUX
afs-90955	264	10	increase	increase	VERB
afs-90955	264	11	the	the	DET
afs-90955	264	12	peak	peak	NOUN
afs-90955	264	13	ram	ram	NOUN
afs-90955	264	14	substantially	substantially	ADV
afs-90955	264	15	.	.	PUNCT
afs-90955	265	1	the	the	DET
afs-90955	265	2	m	m	NOUN
afs-90955	265	3	matrix	matrix	NOUN
afs-90955	265	4	for	for	ADP
afs-90955	265	5	our	our	PRON
afs-90955	265	6	full	full	ADJ
afs-90955	265	7	genomic	genomic	ADJ
afs-90955	265	8	data	datum	NOUN
afs-90955	265	9	would	would	AUX
afs-90955	265	10	take	take	VERB
afs-90955	265	11	about	about	ADV
afs-90955	265	12	600	600	NUM
afs-90955	265	13	gb	gb	NOUN
afs-90955	265	14	in	in	ADP
afs-90955	265	15	double	double	ADJ
afs-90955	265	16	precision	precision	NOUN
afs-90955	265	17	,	,	PUNCT
afs-90955	265	18	which	which	PRON
afs-90955	265	19	has	have	VERB
afs-90955	265	20	to	to	PART
afs-90955	265	21	be	be	AUX
afs-90955	265	22	used	use	VERB
afs-90955	265	23	in	in	ADP
afs-90955	265	24	order	order	NOUN
afs-90955	265	25	to	to	PART
afs-90955	265	26	use	use	VERB
afs-90955	265	27	the	the	DET
afs-90955	265	28	dgemm	dgemm	NOUN
afs-90955	265	29	subroutine	subroutine	NOUN
afs-90955	265	30	.	.	PUNCT
afs-90955	266	1	if	if	SCONJ
afs-90955	266	2	single	single	ADJ
afs-90955	266	3	precision	precision	NOUN
afs-90955	266	4	subroutine	subroutine	NOUN
afs-90955	266	5	sgemm	sgemm	NOUN
afs-90955	266	6	is	be	AUX
afs-90955	266	7	considered	consider	VERB
afs-90955	266	8	to	to	PART
afs-90955	266	9	give	give	VERB
afs-90955	266	10	sufficient	sufficient	ADJ
afs-90955	266	11	numerical	numerical	ADJ
afs-90955	266	12	accuracy	accuracy	NOUN
afs-90955	266	13	,	,	PUNCT
afs-90955	266	14	then	then	ADV
afs-90955	266	15	the	the	DET
afs-90955	266	16	ram	ram	NOUN
afs-90955	266	17	need	need	NOUN
afs-90955	266	18	is	be	AUX
afs-90955	266	19	halved	halve	VERB
afs-90955	266	20	.	.	PUNCT
afs-90955	267	1	a	a	DET
afs-90955	267	2	hybrid	hybrid	ADJ
afs-90955	267	3	approach	approach	NOUN
afs-90955	267	4	would	would	AUX
afs-90955	267	5	allow	allow	VERB
afs-90955	267	6	reading	reading	NOUN
afs-90955	267	7	and	and	CCONJ
afs-90955	267	8	using	use	VERB
afs-90955	267	9	genotypes	genotype	NOUN
afs-90955	267	10	from	from	ADP
afs-90955	267	11	several	several	ADJ
afs-90955	267	12	individuals	individual	NOUN
afs-90955	267	13	at	at	ADP
afs-90955	267	14	a	a	DET
afs-90955	267	15	time	time	NOUN
afs-90955	267	16	.	.	PUNCT
afs-90955	268	1	this	this	DET
afs-90955	268	2	hybrid	hybrid	ADJ
afs-90955	268	3	approach	approach	NOUN
afs-90955	268	4	would	would	AUX
afs-90955	268	5	have	have	VERB
afs-90955	268	6	a	a	DET
afs-90955	268	7	lower	low	ADJ
afs-90955	268	8	ram	ram	NOUN
afs-90955	268	9	use	use	NOUN
afs-90955	268	10	than	than	ADP
afs-90955	268	11	storing	store	VERB
afs-90955	268	12	the	the	DET
afs-90955	268	13	full	full	ADJ
afs-90955	268	14	m	m	NOUN
afs-90955	268	15	matrix	matrix	NOUN
afs-90955	268	16	in	in	ADP
afs-90955	268	17	ram	ram	NOUN
afs-90955	268	18	and	and	CCONJ
afs-90955	268	19	,	,	PUNCT
afs-90955	268	20	perhaps	perhaps	ADV
afs-90955	268	21	,	,	PUNCT
afs-90955	268	22	more	more	ADV
afs-90955	268	23	efficient	efficient	ADJ
afs-90955	268	24	matrix	matrix	NOUN
afs-90955	268	25	times	time	NOUN
afs-90955	268	26	matrix	matrix	NOUN
afs-90955	268	27	computations	computation	NOUN
afs-90955	268	28	by	by	ADP
afs-90955	268	29	dgemm	dgemm	NOUN
afs-90955	268	30	than	than	ADP
afs-90955	268	31	in	in	ADP
afs-90955	268	32	the	the	DET
afs-90955	268	33	current	current	ADJ
afs-90955	268	34	implementation	implementation	NOUN
afs-90955	268	35	.	.	PUNCT
afs-90955	269	1	estimation	estimation	NOUN
afs-90955	269	2	of	of	ADP
afs-90955	269	3	base	base	ADJ
afs-90955	269	4	population	population	NOUN
afs-90955	269	5	af	af	VERB
afs-90955	269	6	to	to	ADP
afs-90955	269	7	groups	group	NOUN
afs-90955	269	8	decreased	decrease	VERB
afs-90955	269	9	differences	difference	NOUN
afs-90955	269	10	between	between	ADP
afs-90955	269	11	the	the	DET
afs-90955	269	12	approaches	approach	NOUN
afs-90955	269	13	.	.	PUNCT
afs-90955	270	1	table	table	NOUN
afs-90955	270	2	4	4	NUM
afs-90955	270	3	has	have	AUX
afs-90955	270	4	computing	compute	VERB
afs-90955	270	5	times	time	NOUN
afs-90955	270	6	from	from	ADP
afs-90955	270	7	estimating	estimate	VERB
afs-90955	270	8	base	base	NOUN
afs-90955	270	9	af	af	NOUN
afs-90955	270	10	for	for	ADP
afs-90955	270	11	the	the	DET
afs-90955	270	12	24	24	NUM
afs-90955	270	13	groups	group	NOUN
afs-90955	270	14	.	.	PUNCT
afs-90955	271	1	in	in	ADP
afs-90955	271	2	general	general	ADJ
afs-90955	271	3	,	,	PUNCT
afs-90955	271	4	the	the	DET
afs-90955	271	5	results	result	NOUN
afs-90955	271	6	were	be	AUX
afs-90955	271	7	similar	similar	ADJ
afs-90955	271	8	to	to	ADP
afs-90955	271	9	those	those	PRON
afs-90955	271	10	for	for	ADP
afs-90955	271	11	single	single	ADJ
afs-90955	271	12	group	group	NOUN
afs-90955	271	13	in	in	ADP
afs-90955	271	14	table	table	NOUN
afs-90955	271	15	2	2	NUM
afs-90955	271	16	.	.	PUNCT
afs-90955	272	1	however	however	ADV
afs-90955	272	2	,	,	PUNCT
afs-90955	272	3	the	the	DET
afs-90955	272	4	difference	difference	NOUN
afs-90955	272	5	in	in	ADP
afs-90955	272	6	peak	peak	NOUN
afs-90955	272	7	ram	ram	NOUN
afs-90955	272	8	was	be	AUX
afs-90955	272	9	not	not	PART
afs-90955	272	10	as	as	ADV
afs-90955	272	11	large	large	ADJ
afs-90955	272	12	between	between	ADP
afs-90955	272	13	the	the	DET
afs-90955	272	14	approaches	approach	NOUN
afs-90955	272	15	for	for	ADP
afs-90955	272	16	the	the	DET
afs-90955	272	17	multiple	multiple	ADJ
afs-90955	272	18	group	group	NOUN
afs-90955	272	19	case	case	NOUN
afs-90955	272	20	as	as	ADP
afs-90955	272	21	for	for	ADP
afs-90955	272	22	the	the	DET
afs-90955	272	23	single	single	ADJ
afs-90955	272	24	group	group	NOUN
afs-90955	272	25	case	case	NOUN
afs-90955	272	26	.	.	PUNCT
afs-90955	273	1	this	this	PRON
afs-90955	273	2	is	be	AUX
afs-90955	273	3	most	most	ADV
afs-90955	273	4	likely	likely	ADJ
afs-90955	273	5	due	due	ADP
afs-90955	273	6	to	to	ADP
afs-90955	273	7	the	the	DET
afs-90955	273	8	increase	increase	NOUN
afs-90955	273	9	in	in	ADP
afs-90955	273	10	ram	ram	NOUN
afs-90955	273	11	need	need	NOUN
afs-90955	273	12	due	due	ADP
afs-90955	273	13	to	to	ADP
afs-90955	273	14	the	the	DET
afs-90955	273	15	24	24	NUM
afs-90955	273	16	groups	group	NOUN
afs-90955	273	17	each	each	PRON
afs-90955	273	18	of	of	ADP
afs-90955	273	19	which	which	PRON
afs-90955	273	20	required	require	VERB
afs-90955	273	21	a	a	DET
afs-90955	273	22	column	column	NOUN
afs-90955	273	23	in	in	ADP
afs-90955	273	24	the	the	DET
afs-90955	273	25	q	q	NOUN
afs-90955	273	26	matrix	matrix	NOUN
afs-90955	273	27	.	.	PUNCT
afs-90955	274	1	in	in	ADP
afs-90955	274	2	other	other	ADJ
afs-90955	274	3	words	word	NOUN
afs-90955	274	4	,	,	PUNCT
afs-90955	274	5	the	the	DET
afs-90955	274	6	group	group	NOUN
afs-90955	274	7	proportions	proportion	NOUN
afs-90955	274	8	for	for	ADP
afs-90955	274	9	the	the	DET
afs-90955	274	10	genotyped	genotype	VERB
afs-90955	274	11	animals	animal	NOUN
afs-90955	274	12	and	and	CCONJ
afs-90955	274	13	their	their	PRON
afs-90955	274	14	ancestors	ancestor	NOUN
afs-90955	274	15	were	be	AUX
afs-90955	274	16	temporarily	temporarily	ADV
afs-90955	274	17	needed	need	VERB
afs-90955	274	18	in	in	ADP
afs-90955	274	19	the	the	DET
afs-90955	274	20	computation	computation	NOUN
afs-90955	274	21	of	of	ADP
afs-90955	274	22	the	the	DET
afs-90955	274	23	q	q	NOUN
afs-90955	274	24	matrix	matrix	NOUN
afs-90955	274	25	which	which	PRON
afs-90955	274	26	was	be	AUX
afs-90955	274	27	stored	store	VERB
afs-90955	274	28	in	in	ADP
afs-90955	274	29	ram	ram	NOUN
afs-90955	274	30	in	in	ADP
afs-90955	274	31	double	double	ADJ
afs-90955	274	32	precision	precision	NOUN
afs-90955	274	33	and	and	CCONJ
afs-90955	274	34	took	take	VERB
afs-90955	274	35	almost	almost	ADV
afs-90955	274	36	650	650	NUM
afs-90955	274	37	mb	mb	NOUN
afs-90955	274	38	.	.	PUNCT
afs-90955	275	1	the	the	DET
afs-90955	275	2	difference	difference	NOUN
afs-90955	275	3	in	in	ADP
afs-90955	275	4	peak	peak	NOUN
afs-90955	275	5	ram	ram	NOUN
afs-90955	275	6	between	between	ADP
afs-90955	275	7	iop	iop	PROPN
afs-90955	275	8	and	and	CCONJ
afs-90955	275	9	i	i	PRON
afs-90955	275	10	m	m	VERB
afs-90955	275	11	approaches	approach	NOUN
afs-90955	275	12	was	be	AUX
afs-90955	275	13	minimal	minimal	ADJ
afs-90955	275	14	because	because	SCONJ
afs-90955	275	15	memory	memory	NOUN
afs-90955	275	16	was	be	AUX
afs-90955	275	17	deallocated	deallocate	VERB
afs-90955	275	18	after	after	SCONJ
afs-90955	275	19	the	the	DET
afs-90955	275	20	full	full	ADJ
afs-90955	275	21	q	q	NOUN
afs-90955	275	22	matrix	matrix	NOUN
afs-90955	275	23	had	have	AUX
afs-90955	275	24	been	be	AUX
afs-90955	275	25	made	make	VERB
afs-90955	275	26	,	,	PUNCT
afs-90955	275	27	and	and	CCONJ
afs-90955	275	28	the	the	DET
afs-90955	275	29	q2	q2	NOUN
afs-90955	275	30	submatrix	submatrix	NOUN
afs-90955	275	31	of	of	ADP
afs-90955	275	32	only	only	ADV
afs-90955	275	33	the	the	DET
afs-90955	275	34	genotyped	genotype	VERB
afs-90955	275	35	animals	animal	NOUN
afs-90955	275	36	was	be	AUX
afs-90955	275	37	used	use	VERB
afs-90955	275	38	in	in	ADP
afs-90955	275	39	the	the	DET
afs-90955	275	40	base	base	NOUN
afs-90955	275	41	af	af	PROPN
afs-90955	275	42	computations	computations	PROPN
afs-90955	275	43	.	.	PUNCT
afs-90955	276	1	the	the	DET
afs-90955	276	2	additional	additional	ADJ
afs-90955	276	3	memory	memory	NOUN
afs-90955	276	4	needed	need	VERB
afs-90955	276	5	to	to	PART
afs-90955	276	6	store	store	VERB
afs-90955	276	7	a11	a11	PROPN
afs-90955	276	8	in	in	ADP
afs-90955	276	9	the	the	DET
afs-90955	276	10	i	i	PROPN
afs-90955	276	11	m	m	VERB
afs-90955	276	12	approach	approach	NOUN
afs-90955	276	13	was	be	AUX
afs-90955	276	14	so	so	ADV
afs-90955	276	15	small	small	ADJ
afs-90955	276	16	that	that	SCONJ
afs-90955	276	17	the	the	DET
afs-90955	276	18	deallocated	deallocate	VERB
afs-90955	276	19	ram	ram	NOUN
afs-90955	276	20	from	from	ADP
afs-90955	276	21	the	the	DET
afs-90955	276	22	full	full	ADJ
afs-90955	276	23	q	q	NOUN
afs-90955	276	24	memory	memory	NOUN
afs-90955	276	25	was	be	AUX
afs-90955	276	26	more	more	ADJ
afs-90955	276	27	than	than	ADP
afs-90955	276	28	enough	enough	ADJ
afs-90955	276	29	for	for	ADP
afs-90955	276	30	its	its	PRON
afs-90955	276	31	use	use	NOUN
afs-90955	276	32	.	.	PUNCT
afs-90955	277	1	conclusions	conclusion	NOUN
afs-90955	277	2	a	a	DET
afs-90955	277	3	computationally	computationally	ADV
afs-90955	277	4	efficient	efficient	ADJ
afs-90955	277	5	program	program	NOUN
afs-90955	277	6	called	call	VERB
afs-90955	277	7	bpop	bpop	NOUN
afs-90955	277	8	was	be	AUX
afs-90955	277	9	written	write	VERB
afs-90955	277	10	to	to	PART
afs-90955	277	11	estimate	estimate	VERB
afs-90955	277	12	base	base	NOUN
afs-90955	277	13	population	population	NOUN
afs-90955	278	1	af	af	AUX
afs-90955	278	2	using	use	VERB
afs-90955	278	3	a	a	DET
afs-90955	278	4	gls	gls	ADJ
afs-90955	278	5	approach	approach	NOUN
afs-90955	278	6	.	.	PUNCT
afs-90955	279	1	computationally	computationally	ADV
afs-90955	279	2	the	the	DET
afs-90955	279	3	most	most	ADV
afs-90955	279	4	demanding	demanding	ADJ
afs-90955	279	5	step	step	NOUN
afs-90955	279	6	involves	involve	VERB
afs-90955	279	7	inverse	inverse	NOUN
afs-90955	279	8	of	of	ADP
afs-90955	279	9	pedigree	pedigree	ADJ
afs-90955	279	10	relationship	relationship	NOUN
afs-90955	279	11	matrix	matrix	NOUN
afs-90955	279	12	between	between	ADP
afs-90955	279	13	genotyped	genotype	VERB
afs-90955	279	14	animals	animal	NOUN
afs-90955	279	15	,	,	PUNCT
afs-90955	279	16	(	(	PUNCT
afs-90955	279	17	a22	a22	PROPN
afs-90955	279	18	)	)	PUNCT
afs-90955	279	19	-1	-1	NOUN
afs-90955	279	20	,	,	PUNCT
afs-90955	279	21	times	time	NOUN
afs-90955	279	22	a	a	DET
afs-90955	279	23	vector	vector	NOUN
afs-90955	279	24	or	or	CCONJ
afs-90955	279	25	a	a	DET
afs-90955	279	26	matrix	matrix	NOUN
afs-90955	279	27	.	.	PUNCT
afs-90955	280	1	the	the	DET
afs-90955	280	2	a22	a22	PROPN
afs-90955	280	3	matrix	matrix	NOUN
afs-90955	280	4	is	be	AUX
afs-90955	280	5	dense	dense	ADJ
afs-90955	280	6	.	.	PUNCT
afs-90955	281	1	we	we	PRON
afs-90955	281	2	presented	present	VERB
afs-90955	281	3	and	and	CCONJ
afs-90955	281	4	implemented	implement	VERB
afs-90955	281	5	three	three	NUM
afs-90955	281	6	alternative	alternative	ADJ
afs-90955	281	7	approaches	approach	NOUN
afs-90955	281	8	which	which	PRON
afs-90955	281	9	do	do	AUX
afs-90955	281	10	not	not	PART
afs-90955	281	11	require	require	VERB
afs-90955	281	12	explicitly	explicitly	ADV
afs-90955	281	13	making	make	VERB
afs-90955	281	14	the	the	DET
afs-90955	281	15	(	(	PUNCT
afs-90955	281	16	a22	a22	PROPN
afs-90955	281	17	)	)	PUNCT
afs-90955	281	18	-1	-1	PUNCT
afs-90955	281	19	matrix	matrix	NOUN
afs-90955	281	20	.	.	PUNCT
afs-90955	282	1	these	these	DET
afs-90955	282	2	approaches	approach	NOUN
afs-90955	282	3	used	use	VERB
afs-90955	282	4	an	an	DET
afs-90955	282	5	equivalent	equivalent	ADJ
afs-90955	282	6	matrix	matrix	NOUN
afs-90955	282	7	formula	formula	NOUN
afs-90955	282	8	of	of	ADP
afs-90955	282	9	(	(	PUNCT
afs-90955	282	10	a22	a22	PROPN
afs-90955	282	11	)	)	PUNCT
afs-90955	282	12	-1	-1	PUNCT
afs-90955	282	13	involving	involve	VERB
afs-90955	282	14	sparse	sparse	ADJ
afs-90955	282	15	matrices	matrix	NOUN
afs-90955	282	16	.	.	PUNCT
afs-90955	283	1	this	this	DET
afs-90955	283	2	formulation	formulation	NOUN
afs-90955	283	3	allowed	allow	VERB
afs-90955	283	4	use	use	NOUN
afs-90955	283	5	of	of	ADP
afs-90955	283	6	marker	marker	NOUN
afs-90955	283	7	data	datum	NOUN
afs-90955	283	8	from	from	ADP
afs-90955	283	9	many	many	ADJ
afs-90955	283	10	genotyped	genotype	VERB
afs-90955	283	11	animals	animal	NOUN
afs-90955	283	12	.	.	PUNCT
afs-90955	284	1	the	the	DET
afs-90955	284	2	computing	computing	NOUN
afs-90955	284	3	step	step	NOUN
afs-90955	284	4	involving	involve	VERB
afs-90955	284	5	the	the	DET
afs-90955	284	6	reformulated	reformulate	VERB
afs-90955	284	7	(	(	PUNCT
afs-90955	284	8	a22	a22	PROPN
afs-90955	284	9	)	)	PUNCT
afs-90955	284	10	-1	-1	PUNCT
afs-90955	284	11	matrix	matrix	NOUN
afs-90955	284	12	was	be	AUX
afs-90955	284	13	very	very	ADV
afs-90955	284	14	fast	fast	ADV
afs-90955	284	15	.	.	PUNCT
afs-90955	285	1	the	the	DET
afs-90955	285	2	three	three	NUM
afs-90955	285	3	approaches	approach	NOUN
afs-90955	285	4	had	have	VERB
afs-90955	285	5	small	small	ADJ
afs-90955	285	6	differences	difference	NOUN
afs-90955	285	7	in	in	ADP
afs-90955	285	8	total	total	ADJ
afs-90955	285	9	computing	computing	NOUN
afs-90955	285	10	time	time	NOUN
afs-90955	285	11	but	but	CCONJ
afs-90955	285	12	had	have	VERB
afs-90955	285	13	larger	large	ADJ
afs-90955	285	14	differences	difference	NOUN
afs-90955	285	15	in	in	ADP
afs-90955	285	16	the	the	DET
afs-90955	285	17	needed	need	VERB
afs-90955	285	18	amount	amount	NOUN
afs-90955	285	19	of	of	ADP
afs-90955	285	20	peak	peak	NOUN
afs-90955	285	21	computer	computer	NOUN
afs-90955	285	22	memory	memory	NOUN
afs-90955	285	23	.	.	PUNCT
afs-90955	286	1	thus	thus	ADV
afs-90955	286	2	,	,	PUNCT
afs-90955	286	3	choice	choice	NOUN
afs-90955	286	4	of	of	ADP
afs-90955	286	5	the	the	DET
afs-90955	286	6	computing	computing	NOUN
afs-90955	286	7	approach	approach	NOUN
afs-90955	286	8	can	can	AUX
afs-90955	286	9	be	be	AUX
afs-90955	286	10	made	make	VERB
afs-90955	286	11	based	base	VERB
afs-90955	286	12	on	on	ADP
afs-90955	286	13	the	the	DET
afs-90955	286	14	available	available	ADJ
afs-90955	286	15	computer	computer	NOUN
afs-90955	286	16	memory	memory	NOUN
afs-90955	286	17	.	.	PUNCT
afs-90955	287	1	availability	availability	NOUN
afs-90955	287	2	and	and	CCONJ
afs-90955	287	3	requirements	requirement	NOUN
afs-90955	287	4	the	the	DET
afs-90955	287	5	program	program	NOUN
afs-90955	287	6	bpop	bpop	NOUN
afs-90955	287	7	is	be	AUX
afs-90955	287	8	provided	provide	VERB
afs-90955	287	9	free	free	ADJ
afs-90955	287	10	of	of	ADP
afs-90955	287	11	charge	charge	NOUN
afs-90955	287	12	for	for	ADP
afs-90955	287	13	the	the	DET
afs-90955	287	14	scientific	scientific	ADJ
afs-90955	287	15	community	community	NOUN
afs-90955	287	16	,	,	PUNCT
afs-90955	287	17	but	but	CCONJ
afs-90955	287	18	users	user	NOUN
afs-90955	287	19	are	be	AUX
afs-90955	287	20	required	require	VERB
afs-90955	287	21	to	to	PART
afs-90955	287	22	credit	credit	VERB
afs-90955	287	23	its	its	PRON
afs-90955	287	24	use	use	NOUN
afs-90955	287	25	in	in	ADP
afs-90955	287	26	any	any	DET
afs-90955	287	27	publication	publication	NOUN
afs-90955	287	28	.	.	PUNCT
afs-90955	288	1	commercial	commercial	ADJ
afs-90955	288	2	users	user	NOUN
afs-90955	288	3	must	must	AUX
afs-90955	288	4	contact	contact	VERB
afs-90955	288	5	the	the	DET
afs-90955	288	6	authors	author	NOUN
afs-90955	288	7	.	.	PUNCT
afs-90955	289	1	bpop	bpop	PROPN
afs-90955	289	2	executable	executable	NOUN
afs-90955	289	3	is	be	AUX
afs-90955	289	4	available	available	ADJ
afs-90955	289	5	for	for	ADP
afs-90955	289	6	linux	linux	PROPN
afs-90955	289	7	upon	upon	SCONJ
afs-90955	289	8	request	request	NOUN
afs-90955	289	9	from	from	ADP
afs-90955	289	10	the	the	DET
afs-90955	289	11	corresponding	corresponding	ADJ
afs-90955	289	12	author	author	NOUN
afs-90955	289	13	.	.	PUNCT
afs-90955	290	1	the	the	DET
afs-90955	290	2	program	program	NOUN
afs-90955	290	3	is	be	AUX
afs-90955	290	4	under	under	ADP
afs-90955	290	5	ongoing	ongoing	ADJ
afs-90955	290	6	development	development	NOUN
afs-90955	290	7	,	,	PUNCT
afs-90955	290	8	and	and	CCONJ
afs-90955	290	9	due	due	ADP
afs-90955	290	10	to	to	ADP
afs-90955	290	11	the	the	DET
afs-90955	290	12	number	number	NOUN
afs-90955	290	13	of	of	ADP
afs-90955	290	14	features	feature	NOUN
afs-90955	290	15	,	,	PUNCT
afs-90955	290	16	some	some	DET
afs-90955	290	17	combinations	combination	NOUN
afs-90955	290	18	of	of	ADP
afs-90955	290	19	options	option	NOUN
afs-90955	290	20	may	may	AUX
afs-90955	290	21	not	not	PART
afs-90955	290	22	have	have	AUX
afs-90955	290	23	been	be	AUX
afs-90955	290	24	tested	test	VERB
afs-90955	290	25	thoroughly	thoroughly	ADV
afs-90955	290	26	.	.	PUNCT
afs-90955	291	1	table	table	NOUN
afs-90955	291	2	4	4	NUM
afs-90955	291	3	.	.	PUNCT
afs-90955	291	4	average	average	ADJ
afs-90955	291	5	number	number	NOUN
afs-90955	291	6	of	of	ADP
afs-90955	291	7	pcg	pcg	PROPN
afs-90955	291	8	iterations	iteration	NOUN
afs-90955	291	9	(	(	PUNCT
afs-90955	291	10	n	n	CCONJ
afs-90955	291	11	)	)	PUNCT
afs-90955	291	12	,	,	PUNCT
afs-90955	291	13	wall	wall	NOUN
afs-90955	291	14	clock	clock	PROPN
afs-90955	291	15	time	time	NOUN
afs-90955	291	16	for	for	ADP
afs-90955	291	17	calculating	calculate	VERB
afs-90955	291	18	the	the	DET
afs-90955	291	19	c	c	NOUN
afs-90955	291	20	matrix	matrix	NOUN
afs-90955	291	21	in	in	ADP
afs-90955	291	22	formula	formula	NOUN
afs-90955	291	23	[	[	X
afs-90955	291	24	4	4	X
afs-90955	291	25	]	]	PUNCT
afs-90955	291	26	(	(	PUNCT
afs-90955	291	27	tc	tc	NOUN
afs-90955	291	28	)	)	PUNCT
afs-90955	291	29	,	,	PUNCT
afs-90955	291	30	total	total	ADJ
afs-90955	291	31	wall	wall	NOUN
afs-90955	291	32	clock	clock	PROPN
afs-90955	291	33	time	time	NOUN
afs-90955	291	34	(	(	PUNCT
afs-90955	291	35	tt	tt	NOUN
afs-90955	291	36	)	)	PUNCT
afs-90955	291	37	and	and	CCONJ
afs-90955	291	38	peak	peak	NOUN
afs-90955	291	39	memory	memory	NOUN
afs-90955	291	40	use	use	NOUN
afs-90955	291	41	(	(	PUNCT
afs-90955	291	42	ram	ram	NOUN
afs-90955	291	43	)	)	PUNCT
afs-90955	291	44	in	in	ADP
afs-90955	291	45	multi	multi	ADJ
afs-90955	291	46	group	group	NOUN
afs-90955	291	47	allele	allele	PROPN
afs-90955	291	48	frequency	frequency	NOUN
afs-90955	291	49	estimation	estimation	NOUN
afs-90955	291	50	when	when	SCONJ
afs-90955	291	51	computation	computation	NOUN
afs-90955	291	52	use	use	VERB
afs-90955	291	53	iteration	iteration	NOUN
afs-90955	291	54	on	on	ADP
afs-90955	291	55	pedigree	pedigree	ADJ
afs-90955	291	56	(	(	PUNCT
afs-90955	291	57	iop	iop	PROPN
afs-90955	291	58	)	)	PUNCT
afs-90955	291	59	,	,	PUNCT
afs-90955	291	60	iteration	iteration	NOUN
afs-90955	291	61	in	in	ADP
afs-90955	291	62	memory	memory	NOUN
afs-90955	291	63	(	(	PUNCT
afs-90955	291	64	i	i	NOUN
afs-90955	291	65	m	m	PROPN
afs-90955	291	66	)	)	PUNCT
afs-90955	291	67	,	,	PUNCT
afs-90955	291	68	or	or	CCONJ
afs-90955	291	69	sparse	sparse	VERB
afs-90955	291	70	cholesky	cholesky	ADJ
afs-90955	291	71	factorization	factorization	NOUN
afs-90955	291	72	(	(	PUNCT
afs-90955	291	73	chm	chm	NOUN
afs-90955	291	74	)	)	PUNCT
afs-90955	291	75	.	.	PUNCT
afs-90955	292	1	approach	approach	NOUN
afs-90955	292	2	n	n	PRON
afs-90955	292	3	iteration	iteration	NOUN
afs-90955	292	4	tc	tc	PROPN
afs-90955	292	5	(	(	PUNCT
afs-90955	292	6	min	min	NOUN
afs-90955	292	7	)	)	PUNCT
afs-90955	292	8	tt	tt	PROPN
afs-90955	292	9	(	(	PUNCT
afs-90955	292	10	min	min	PROPN
afs-90955	292	11	)	)	PUNCT
afs-90955	292	12	ram	ram	NOUN
afs-90955	292	13	(	(	PUNCT
afs-90955	292	14	gb	gb	NOUN
afs-90955	292	15	)	)	PUNCT
afs-90955	292	16	iop	iop	NOUN
afs-90955	292	17	300	300	NUM
afs-90955	292	18	10.5	10.5	NUM
afs-90955	292	19	89.7	89.7	NUM
afs-90955	292	20	1.68	1.68	NUM
afs-90955	292	21	i	i	PRON
afs-90955	292	22	m	m	VERB
afs-90955	292	23	286	286	NUM
afs-90955	292	24	5.3	5.3	NUM
afs-90955	292	25	85.5	85.5	NUM
afs-90955	292	26	1.68	1.68	NUM
afs-90955	292	27	chm	chm	NOUN
afs-90955	292	28	–	–	PUNCT
afs-90955	292	29	4.7	4.7	NUM
afs-90955	292	30	91.3	91.3	NUM
afs-90955	292	31	8.38	8.38	NUM
afs-90955	292	32	chm	chm	NOUN
afs-90955	292	33	,	,	PUNCT
afs-90955	292	34	parallel	parallel	ADJ
afs-90955	292	35	–	–	PUNCT
afs-90955	292	36	1.8	1.8	NUM
afs-90955	292	37	85.3	85.3	NUM
afs-90955	292	38	9.05	9.05	NUM
afs-90955	292	39	agricultural	agricultural	ADJ
afs-90955	292	40	and	and	CCONJ
afs-90955	292	41	food	food	NOUN
afs-90955	292	42	science	science	PROPN
afs-90955	292	43	i.	i.	PROPN
afs-90955	292	44	strandén	strandén	PROPN
afs-90955	292	45	&	&	CCONJ
afs-90955	292	46	e.a	e.a	PROPN
afs-90955	292	47	.	.	PROPN
afs-90955	292	48	mäntysaari	mäntysaari	PROPN
afs-90955	292	49	(	(	PUNCT
afs-90955	292	50	2020	2020	NUM
afs-90955	292	51	)	)	PUNCT
afs-90955	292	52	29	29	NUM
afs-90955	292	53	:	:	PUNCT
afs-90955	292	54	166–176	166–176	NUM
afs-90955	292	55	174	174	NUM
afs-90955	292	56	acknowledgements	acknowledgement	NOUN
afs-90955	292	57	the	the	DET
afs-90955	292	58	authors	author	NOUN
afs-90955	292	59	acknowledge	acknowledge	VERB
afs-90955	292	60	the	the	DET
afs-90955	292	61	irish	irish	ADJ
afs-90955	292	62	cattle	cattle	NOUN
afs-90955	292	63	breeding	breeding	PROPN
afs-90955	292	64	federation	federation	PROPN
afs-90955	292	65	(	(	PUNCT
afs-90955	292	66	icbf	icbf	PROPN
afs-90955	292	67	)	)	PUNCT
afs-90955	292	68	for	for	ADP
afs-90955	292	69	providing	provide	VERB
afs-90955	292	70	the	the	DET
afs-90955	292	71	beef	beef	NOUN
afs-90955	292	72	cattle	cattle	NOUN
afs-90955	292	73	data	datum	NOUN
afs-90955	292	74	.	.	PUNCT
afs-90955	293	1	references	reference	NOUN
afs-90955	293	2	aldridge	aldridge	PROPN
afs-90955	293	3	,	,	PUNCT
afs-90955	293	4	m.n	m.n	PROPN
afs-90955	293	5	.	.	PROPN
afs-90955	293	6	,	,	PUNCT
afs-90955	293	7	vandenplas	vandenplas	PROPN
afs-90955	293	8	,	,	PUNCT
afs-90955	293	9	j.	j.	PROPN
afs-90955	293	10	&	&	CCONJ
afs-90955	293	11	calus	calus	PROPN
afs-90955	293	12	,	,	PUNCT
afs-90955	293	13	m.p.l	m.p.l	ADV
afs-90955	293	14	.	.	PUNCT
afs-90955	293	15	2018	2018	NUM
afs-90955	293	16	.	.	PUNCT
afs-90955	294	1	efficient	efficient	ADJ
afs-90955	294	2	and	and	CCONJ
afs-90955	294	3	accurate	accurate	ADJ
afs-90955	294	4	computation	computation	NOUN
afs-90955	294	5	of	of	ADP
afs-90955	294	6	base	base	NOUN
afs-90955	294	7	generation	generation	NOUN
afs-90955	294	8	allele	allele	NOUN
afs-90955	294	9	frequencies	frequency	NOUN
afs-90955	294	10	.	.	PUNCT
afs-90955	295	1	journal	journal	NOUN
afs-90955	295	2	of	of	ADP
afs-90955	295	3	dairy	dairy	NOUN
afs-90955	295	4	science	science	NOUN
afs-90955	295	5	102:1364–1373	102:1364–1373	NOUN
afs-90955	295	6	.	.	PUNCT
afs-90955	296	1	https://doi.org/10.3168/jds.2018-15264	https://doi.org/10.3168/jds.2018-15264	PROPN
afs-90955	296	2	anderson	anderson	PROPN
afs-90955	296	3	,	,	PUNCT
afs-90955	296	4	e.	e.	PROPN
afs-90955	296	5	,	,	PUNCT
afs-90955	296	6	bai	bai	PROPN
afs-90955	296	7	,	,	PUNCT
afs-90955	296	8	z.	z.	PROPN
afs-90955	296	9	,	,	PUNCT
afs-90955	296	10	bischof	bischof	NOUN
afs-90955	296	11	,	,	PUNCT
afs-90955	296	12	c.	c.	PROPN
afs-90955	296	13	,	,	PUNCT
afs-90955	296	14	blackford	blackford	PROPN
afs-90955	296	15	,	,	PUNCT
afs-90955	296	16	s.	s.	PROPN
afs-90955	296	17	,	,	PUNCT
afs-90955	296	18	demmel	demmel	PROPN
afs-90955	296	19	,	,	PUNCT
afs-90955	296	20	j.	j.	PROPN
afs-90955	296	21	,	,	PUNCT
afs-90955	296	22	dongarra	dongarra	PROPN
afs-90955	296	23	,	,	PUNCT
afs-90955	296	24	j.	j.	PROPN
afs-90955	296	25	,	,	PUNCT
afs-90955	296	26	du	du	PROPN
afs-90955	296	27	croz	croz	PROPN
afs-90955	296	28	,	,	PUNCT
afs-90955	296	29	j.	j.	PROPN
afs-90955	296	30	,	,	PUNCT
afs-90955	296	31	greenbaum	greenbaum	PROPN
afs-90955	296	32	,	,	PUNCT
afs-90955	296	33	a.	a.	PROPN
afs-90955	296	34	,	,	PUNCT
afs-90955	296	35	hammarling	hammarling	PROPN
afs-90955	296	36	,	,	PUNCT
afs-90955	296	37	s.	s.	PROPN
afs-90955	296	38	,	,	PUNCT
afs-90955	296	39	mckenny	mckenny	PROPN
afs-90955	296	40	,	,	PUNCT
afs-90955	296	41	a.	a.	PROPN
afs-90955	296	42	&	&	CCONJ
afs-90955	296	43	sorensen	sorensen	PROPN
afs-90955	296	44	,	,	PUNCT
afs-90955	296	45	d.	d.	PROPN
afs-90955	296	46	1999	1999	NUM
afs-90955	296	47	.	.	PUNCT
afs-90955	297	1	lapack	lapack	PROPN
afs-90955	297	2	users	user	NOUN
afs-90955	297	3	’	'	PUNCT
afs-90955	297	4	guide	guide	NOUN
afs-90955	297	5	.	.	PUNCT
afs-90955	298	1	3rd	3rd	ADJ
afs-90955	298	2	ed	ed	NOUN
afs-90955	298	3	.	.	PUNCT
afs-90955	299	1	siam	siam	PROPN
afs-90955	299	2	.	.	PUNCT
afs-90955	299	3	philadelphia	philadelphia	PROPN
afs-90955	299	4	,	,	PUNCT
afs-90955	299	5	pa	pa	PROPN
afs-90955	299	6	,	,	PUNCT
afs-90955	299	7	usa	usa	PROPN
afs-90955	299	8	.	.	PROPN
afs-90955	299	9	https://doi.org/10.1137/1.9780898719604	https://doi.org/10.1137/1.9780898719604	PROPN
afs-90955	299	10	aguilar	aguilar	PROPN
afs-90955	299	11	,	,	PUNCT
afs-90955	299	12	i.	i.	PROPN
afs-90955	299	13	,	,	PUNCT
afs-90955	299	14	misztal	misztal	PROPN
afs-90955	299	15	,	,	PUNCT
afs-90955	299	16	i.	i.	PROPN
afs-90955	299	17	,	,	PUNCT
afs-90955	299	18	johnson	johnson	PROPN
afs-90955	299	19	,	,	PUNCT
afs-90955	299	20	d.l	d.l	PROPN
afs-90955	299	21	.	.	PROPN
afs-90955	299	22	,	,	PUNCT
afs-90955	299	23	legarra	legarra	PROPN
afs-90955	299	24	,	,	PUNCT
afs-90955	299	25	a.	a.	NOUN
afs-90955	299	26	,	,	PUNCT
afs-90955	299	27	tsuruta	tsuruta	ADV
afs-90955	299	28	,	,	PUNCT
afs-90955	299	29	s.	s.	PROPN
afs-90955	299	30	&	&	CCONJ
afs-90955	299	31	lawlor	lawlor	PROPN
afs-90955	299	32	,	,	PUNCT
afs-90955	299	33	t.j	t.j	PROPN
afs-90955	299	34	.	.	PROPN
afs-90955	299	35	2010	2010	NUM
afs-90955	299	36	.	.	PUNCT
afs-90955	300	1	hot	hot	ADJ
afs-90955	300	2	topic	topic	NOUN
afs-90955	300	3	:	:	PUNCT
afs-90955	300	4	a	a	DET
afs-90955	300	5	unified	unified	ADJ
afs-90955	300	6	approach	approach	NOUN
afs-90955	300	7	to	to	PART
afs-90955	300	8	utilize	utilize	VERB
afs-90955	300	9	phenotypic	phenotypic	NOUN
afs-90955	300	10	,	,	PUNCT
afs-90955	300	11	full	full	ADJ
afs-90955	300	12	pedigree	pedigree	NOUN
afs-90955	300	13	,	,	PUNCT
afs-90955	300	14	and	and	CCONJ
afs-90955	300	15	genomic	genomic	ADJ
afs-90955	300	16	information	information	NOUN
afs-90955	300	17	for	for	ADP
afs-90955	300	18	genetic	genetic	ADJ
afs-90955	300	19	evaluation	evaluation	NOUN
afs-90955	300	20	of	of	ADP
afs-90955	300	21	holstein	holstein	PROPN
afs-90955	300	22	final	final	ADJ
afs-90955	300	23	score	score	NOUN
afs-90955	300	24	.	.	PUNCT
afs-90955	301	1	journal	journal	NOUN
afs-90955	301	2	of	of	ADP
afs-90955	301	3	dairy	dairy	NOUN
afs-90955	301	4	science	science	NOUN
afs-90955	301	5	93:743–752	93:743–752	NUM
afs-90955	301	6	.	.	PUNCT
afs-90955	302	1	https://doi.org/10.3168/jds.2009-2730	https://doi.org/10.3168/jds.2009-2730	PROPN
afs-90955	302	2	chen	chen	PROPN
afs-90955	302	3	,	,	PUNCT
afs-90955	302	4	y.	y.	PROPN
afs-90955	302	5	,	,	PUNCT
afs-90955	302	6	davis	davis	PROPN
afs-90955	302	7	,	,	PUNCT
afs-90955	302	8	t.a	t.a	PROPN
afs-90955	302	9	.	.	PROPN
afs-90955	302	10	,	,	PUNCT
afs-90955	302	11	hager	hager	PROPN
afs-90955	302	12	,	,	PUNCT
afs-90955	302	13	w.w	w.w	PROPN
afs-90955	302	14	.	.	PROPN
afs-90955	302	15	&	&	CCONJ
afs-90955	302	16	rajamanickam	rajamanickam	PROPN
afs-90955	302	17	,	,	PUNCT
afs-90955	302	18	s.	s.	PROPN
afs-90955	302	19	2008	2008	NUM
afs-90955	302	20	.	.	PUNCT
afs-90955	303	1	algorithm	algorithm	PROPN
afs-90955	303	2	887	887	NUM
afs-90955	303	3	:	:	PUNCT
afs-90955	303	4	cholmod	cholmod	PROPN
afs-90955	303	5	,	,	PUNCT
afs-90955	303	6	supernodal	supernodal	NOUN
afs-90955	303	7	sparse	sparse	ADJ
afs-90955	303	8	cholesky	cholesky	ADJ
afs-90955	303	9	factorization	factorization	NOUN
afs-90955	303	10	and	and	CCONJ
afs-90955	303	11	update	update	VERB
afs-90955	303	12	/	/	SYM
afs-90955	303	13	downdate	downdate	NOUN
afs-90955	303	14	.	.	PUNCT
afs-90955	304	1	acm	acm	PROPN
afs-90955	304	2	transactions	transaction	NOUN
afs-90955	304	3	on	on	ADP
afs-90955	304	4	mathematical	mathematical	ADJ
afs-90955	304	5	software	software	NOUN
afs-90955	304	6	35:22	35:22	NUM
afs-90955	304	7	.	.	PUNCT
afs-90955	305	1	https://doi.org/10.1145/1391989.1391995	https://doi.org/10.1145/1391989.1391995	PROPN
afs-90955	305	2	christensen	christensen	PROPN
afs-90955	305	3	,	,	PUNCT
afs-90955	305	4	o.	o.	PROPN
afs-90955	305	5	&	&	CCONJ
afs-90955	305	6	lund	lund	PROPN
afs-90955	305	7	,	,	PUNCT
afs-90955	305	8	m.s	m.s	PROPN
afs-90955	305	9	.	.	PROPN
afs-90955	305	10	2010	2010	NUM
afs-90955	305	11	.	.	PUNCT
afs-90955	306	1	genomic	genomic	ADJ
afs-90955	306	2	prediction	prediction	NOUN
afs-90955	306	3	when	when	SCONJ
afs-90955	306	4	some	some	DET
afs-90955	306	5	animals	animal	NOUN
afs-90955	306	6	are	be	AUX
afs-90955	306	7	not	not	PART
afs-90955	306	8	genotyped	genotype	VERB
afs-90955	306	9	.	.	PUNCT
afs-90955	307	1	genetics	genetic	NOUN
afs-90955	307	2	selection	selection	NOUN
afs-90955	307	3	evolution	evolution	NOUN
afs-90955	307	4	42:2	42:2	NOUN
afs-90955	307	5	.	.	PUNCT
afs-90955	308	1	https://doi.org/10.1186/1297-9686-42-2	https://doi.org/10.1186/1297-9686-42-2	PROPN
afs-90955	308	2	christensen	christensen	PROPN
afs-90955	308	3	,	,	PUNCT
afs-90955	308	4	o.f	o.f	PROPN
afs-90955	308	5	.	.	PROPN
afs-90955	308	6	,	,	PUNCT
afs-90955	308	7	madsen	madsen	PROPN
afs-90955	308	8	,	,	PUNCT
afs-90955	308	9	p.	p.	PROPN
afs-90955	308	10	,	,	PUNCT
afs-90955	308	11	nielsen	nielsen	PROPN
afs-90955	308	12	,	,	PUNCT
afs-90955	308	13	b.	b.	PROPN
afs-90955	308	14	,	,	PUNCT
afs-90955	308	15	ostersen	ostersen	NOUN
afs-90955	308	16	,	,	PUNCT
afs-90955	308	17	t.	t.	PROPN
afs-90955	308	18	&	&	CCONJ
afs-90955	308	19	su	su	PROPN
afs-90955	308	20	,	,	PUNCT
afs-90955	308	21	g.	g.	PROPN
afs-90955	308	22	2012	2012	NUM
afs-90955	308	23	.	.	PUNCT
afs-90955	309	1	single	single	ADJ
afs-90955	309	2	-	-	PUNCT
afs-90955	309	3	step	step	NOUN
afs-90955	309	4	methods	method	NOUN
afs-90955	309	5	for	for	ADP
afs-90955	309	6	genomic	genomic	ADJ
afs-90955	309	7	evaluation	evaluation	NOUN
afs-90955	309	8	in	in	ADP
afs-90955	309	9	pigs	pig	NOUN
afs-90955	309	10	.	.	PUNCT
afs-90955	310	1	animal	animal	NOUN
afs-90955	310	2	.	.	PUNCT
afs-90955	311	1	6:1565:1571	6:1565:1571	NUM
afs-90955	311	2	.	.	PUNCT
afs-90955	312	1	https://doi.org/10.1017/s1751731112000742	https://doi.org/10.1017/s1751731112000742	PROPN
afs-90955	312	2	davis	davis	PROPN
afs-90955	312	3	,	,	PUNCT
afs-90955	312	4	t.a	t.a	PROPN
afs-90955	312	5	.	.	PROPN
afs-90955	312	6	&	&	CCONJ
afs-90955	312	7	hager	hager	PROPN
afs-90955	312	8	,	,	PUNCT
afs-90955	312	9	w.w	w.w	PROPN
afs-90955	312	10	.	.	PROPN
afs-90955	312	11	2009	2009	NUM
afs-90955	312	12	.	.	PUNCT
afs-90955	313	1	dynamic	dynamic	ADJ
afs-90955	313	2	supernodes	supernode	NOUN
afs-90955	313	3	in	in	ADP
afs-90955	313	4	sparse	sparse	ADJ
afs-90955	313	5	cholesky	cholesky	ADJ
afs-90955	313	6	update	update	NOUN
afs-90955	313	7	/	/	SYM
afs-90955	313	8	downdate	downdate	NOUN
afs-90955	313	9	and	and	CCONJ
afs-90955	313	10	triangular	triangular	NOUN
afs-90955	313	11	solves	solve	NOUN
afs-90955	313	12	.	.	PUNCT
afs-90955	314	1	acm	acm	PROPN
afs-90955	314	2	transactions	transaction	NOUN
afs-90955	314	3	on	on	ADP
afs-90955	314	4	mathematical	mathematical	ADJ
afs-90955	314	5	software	software	NOUN
afs-90955	314	6	35:27	35:27	NUM
afs-90955	314	7	.	.	PUNCT
afs-90955	315	1	https://doi.org/10.1145/1462173.1462176	https://doi.org/10.1145/1462173.1462176	NOUN
afs-90955	315	2	dongarra	dongarra	PROPN
afs-90955	315	3	,	,	PUNCT
afs-90955	315	4	j.j	j.j	PROPN
afs-90955	315	5	.	.	PROPN
afs-90955	315	6	,	,	PUNCT
afs-90955	315	7	du	du	PROPN
afs-90955	315	8	croz	croz	PROPN
afs-90955	315	9	,	,	PUNCT
afs-90955	315	10	j.	j.	PROPN
afs-90955	315	11	,	,	PUNCT
afs-90955	315	12	duff	duff	PROPN
afs-90955	315	13	,	,	PUNCT
afs-90955	315	14	i.s	i.s	PROPN
afs-90955	315	15	.	.	PROPN
afs-90955	315	16	&	&	CCONJ
afs-90955	315	17	hammarling	hammarling	PROPN
afs-90955	315	18	,	,	PUNCT
afs-90955	315	19	s.	s.	PROPN
afs-90955	315	20	1990	1990	NUM
afs-90955	315	21	.	.	PUNCT
afs-90955	316	1	a	a	DET
afs-90955	316	2	set	set	NOUN
afs-90955	316	3	of	of	ADP
afs-90955	316	4	level-3	level-3	PROPN
afs-90955	316	5	basic	basic	ADJ
afs-90955	316	6	linear	linear	PROPN
afs-90955	316	7	algebra	algebra	NOUN
afs-90955	316	8	subprograms	subprogram	NOUN
afs-90955	316	9	.	.	PUNCT
afs-90955	317	1	acm	acm	PROPN
afs-90955	317	2	transactions	transaction	NOUN
afs-90955	317	3	on	on	ADP
afs-90955	317	4	mathematical	mathematical	ADJ
afs-90955	317	5	software	software	NOUN
afs-90955	317	6	16:1–17	16:1–17	NUM
afs-90955	317	7	.	.	PUNCT
afs-90955	318	1	https://doi.org/10.1145/77626.79170	https://doi.org/10.1145/77626.79170	VERB
afs-90955	318	2	garcia	garcia	PROPN
afs-90955	318	3	-	-	PUNCT
afs-90955	318	4	baccino	baccino	PROPN
afs-90955	318	5	,	,	PUNCT
afs-90955	318	6	c.a	c.a	PROPN
afs-90955	318	7	.	.	PROPN
afs-90955	318	8	,	,	PUNCT
afs-90955	318	9	legarra	legarra	PROPN
afs-90955	318	10	,	,	PUNCT
afs-90955	318	11	a.	a.	NOUN
afs-90955	318	12	,	,	PUNCT
afs-90955	318	13	christensen	christensen	PROPN
afs-90955	318	14	,	,	PUNCT
afs-90955	318	15	o.f	o.f	PROPN
afs-90955	318	16	.	.	PROPN
afs-90955	318	17	,	,	PUNCT
afs-90955	318	18	misztal	misztal	PROPN
afs-90955	318	19	,	,	PUNCT
afs-90955	318	20	i.	i.	NOUN
afs-90955	318	21	,	,	PUNCT
afs-90955	318	22	pocrnic	pocrnic	ADJ
afs-90955	318	23	,	,	PUNCT
afs-90955	318	24	i.	i.	NOUN
afs-90955	318	25	,	,	PUNCT
afs-90955	318	26	vitezica	vitezica	PROPN
afs-90955	318	27	,	,	PUNCT
afs-90955	318	28	z.g	z.g	PROPN
afs-90955	318	29	.	.	PROPN
afs-90955	318	30	&	&	CCONJ
afs-90955	318	31	cantet	cantet	PROPN
afs-90955	318	32	,	,	PUNCT
afs-90955	318	33	r.j.c	r.j.c	ADJ
afs-90955	318	34	.	.	PROPN
afs-90955	318	35	2017	2017	NUM
afs-90955	318	36	.	.	PUNCT
afs-90955	319	1	metafounders	metafounder	NOUN
afs-90955	319	2	are	be	AUX
afs-90955	319	3	related	relate	VERB
afs-90955	319	4	to	to	ADP
afs-90955	319	5	fst	fst	NOUN
afs-90955	319	6	fixation	fixation	NOUN
afs-90955	319	7	indices	index	NOUN
afs-90955	319	8	and	and	CCONJ
afs-90955	319	9	reduce	reduce	VERB
afs-90955	319	10	bias	bias	NOUN
afs-90955	319	11	in	in	ADP
afs-90955	319	12	single	single	ADJ
afs-90955	319	13	-	-	PUNCT
afs-90955	319	14	step	step	NOUN
afs-90955	319	15	genomic	genomic	NOUN
afs-90955	319	16	evaluations	evaluation	NOUN
afs-90955	319	17	.	.	PUNCT
afs-90955	320	1	genetics	genetic	NOUN
afs-90955	320	2	selection	selection	NOUN
afs-90955	320	3	evolution	evolution	NOUN
afs-90955	320	4	49:34	49:34	NUM
afs-90955	320	5	.	.	PUNCT
afs-90955	321	1	https://doi.org/10.1186/s12711-017-0309-2	https://doi.org/10.1186/s12711-017-0309-2	NUM
afs-90955	321	2	henderson	henderson	PROPN
afs-90955	321	3	,	,	PUNCT
afs-90955	321	4	c.r	c.r	PROPN
afs-90955	321	5	.	.	PROPN
afs-90955	321	6	1976	1976	NUM
afs-90955	321	7	.	.	PUNCT
afs-90955	322	1	a	a	DET
afs-90955	322	2	simple	simple	ADJ
afs-90955	322	3	method	method	NOUN
afs-90955	322	4	for	for	ADP
afs-90955	322	5	computing	compute	VERB
afs-90955	322	6	the	the	DET
afs-90955	322	7	inverse	inverse	NOUN
afs-90955	322	8	of	of	ADP
afs-90955	322	9	a	a	DET
afs-90955	322	10	numerator	numerator	NOUN
afs-90955	322	11	relationship	relationship	NOUN
afs-90955	322	12	matrix	matrix	NOUN
afs-90955	322	13	used	use	VERB
afs-90955	322	14	in	in	ADP
afs-90955	322	15	prediction	prediction	NOUN
afs-90955	322	16	of	of	ADP
afs-90955	322	17	breeding	breeding	NOUN
afs-90955	322	18	values	value	NOUN
afs-90955	322	19	.	.	PUNCT
afs-90955	323	1	biometrics	biometric	NOUN
afs-90955	323	2	32:69–83	32:69–83	NUM
afs-90955	323	3	.	.	PUNCT
afs-90955	324	1	https://doi.org/10.2307/2529339	https://doi.org/10.2307/2529339	PROPN
afs-90955	324	2	mcpeek	mcpeek	PROPN
afs-90955	324	3	,	,	PUNCT
afs-90955	324	4	m.s	m.s	PROPN
afs-90955	324	5	.	.	PROPN
afs-90955	324	6	,	,	PUNCT
afs-90955	324	7	wu	wu	PROPN
afs-90955	324	8	,	,	PUNCT
afs-90955	324	9	x.	x.	PROPN
afs-90955	324	10	&	&	CCONJ
afs-90955	324	11	ober	ober	PROPN
afs-90955	324	12	,	,	PUNCT
afs-90955	324	13	c.	c.	PROPN
afs-90955	324	14	2004	2004	NUM
afs-90955	324	15	.	.	PUNCT
afs-90955	325	1	best	good	ADJ
afs-90955	325	2	linear	linear	ADJ
afs-90955	325	3	unbiased	unbiased	ADJ
afs-90955	325	4	allele	allele	NOUN
afs-90955	325	5	-	-	PUNCT
afs-90955	325	6	frequency	frequency	NOUN
afs-90955	325	7	estimation	estimation	NOUN
afs-90955	325	8	in	in	ADP
afs-90955	325	9	complex	complex	ADJ
afs-90955	325	10	pedigrees	pedigree	NOUN
afs-90955	325	11	.	.	PUNCT
afs-90955	326	1	biometrics	biometric	NOUN
afs-90955	326	2	60:359	60:359	NUM
afs-90955	326	3	–	–	PUNCT
afs-90955	326	4	367	367	NUM
afs-90955	326	5	.	.	PUNCT
afs-90955	327	1	https://doi.org/10.1111/j.0006-341x.2004.00180.x	https://doi.org/10.1111/j.0006-341x.2004.00180.x	PROPN
afs-90955	327	2	mäntysaari	mäntysaari	PROPN
afs-90955	327	3	,	,	PUNCT
afs-90955	327	4	e.a	e.a	PROPN
afs-90955	327	5	.	.	PROPN
afs-90955	327	6	,	,	PUNCT
afs-90955	327	7	koivula	koivula	NOUN
afs-90955	327	8	,	,	PUNCT
afs-90955	327	9	m.	m.	NOUN
afs-90955	327	10	&	&	CCONJ
afs-90955	327	11	strandén	strandén	PROPN
afs-90955	327	12	,	,	PUNCT
afs-90955	327	13	i.	i.	PROPN
afs-90955	327	14	2020	2020	NUM
afs-90955	327	15	.	.	PUNCT
afs-90955	328	1	symposium	symposium	NOUN
afs-90955	328	2	review	review	NOUN
afs-90955	328	3	:	:	PUNCT
afs-90955	328	4	single	single	ADJ
afs-90955	328	5	-	-	PUNCT
afs-90955	328	6	step	step	NOUN
afs-90955	328	7	genomic	genomic	NOUN
afs-90955	328	8	evaluations	evaluation	NOUN
afs-90955	328	9	in	in	ADP
afs-90955	328	10	dairy	dairy	NOUN
afs-90955	328	11	cattle	cattle	NOUN
afs-90955	328	12	.	.	PUNCT
afs-90955	329	1	journal	journal	NOUN
afs-90955	329	2	of	of	ADP
afs-90955	329	3	dairy	dairy	NOUN
afs-90955	329	4	science	science	NOUN
afs-90955	329	5	.	.	PUNCT
afs-90955	330	1	https://doi.org/10.3168/jds.2019-17754	https://doi.org/10.3168/jds.2019-17754	PROPN
afs-90955	330	2	masuda	masuda	PROPN
afs-90955	330	3	,	,	PUNCT
afs-90955	330	4	y.	y.	PROPN
afs-90955	330	5	,	,	PUNCT
afs-90955	330	6	misztal	misztal	PROPN
afs-90955	330	7	,	,	PUNCT
afs-90955	330	8	i.	i.	PROPN
afs-90955	330	9	,	,	PUNCT
afs-90955	330	10	tsuruta	tsuruta	ADV
afs-90955	330	11	,	,	PUNCT
afs-90955	330	12	s.	s.	PROPN
afs-90955	330	13	,	,	PUNCT
afs-90955	330	14	legarra	legarra	PROPN
afs-90955	330	15	,	,	PUNCT
afs-90955	330	16	a.	a.	NOUN
afs-90955	330	17	,	,	PUNCT
afs-90955	330	18	aguilar	aguilar	PROPN
afs-90955	330	19	,	,	PUNCT
afs-90955	330	20	i.	i.	PROPN
afs-90955	330	21	,	,	PUNCT
afs-90955	330	22	lourenco	lourenco	PROPN
afs-90955	330	23	,	,	PUNCT
afs-90955	330	24	d.a.l	d.a.l	NOUN
afs-90955	330	25	.	.	PROPN
afs-90955	330	26	,	,	PUNCT
afs-90955	330	27	fragomeni	fragomeni	PROPN
afs-90955	330	28	,	,	PUNCT
afs-90955	330	29	b.o	b.o	PROPN
afs-90955	330	30	.	.	PROPN
afs-90955	330	31	&	&	CCONJ
afs-90955	330	32	lawlor	lawlor	PROPN
afs-90955	330	33	,	,	PUNCT
afs-90955	330	34	t.j	t.j	PROPN
afs-90955	330	35	.	.	PROPN
afs-90955	330	36	2016	2016	NUM
afs-90955	330	37	.	.	PUNCT
afs-90955	331	1	implementation	implementation	NOUN
afs-90955	331	2	of	of	ADP
afs-90955	331	3	genomic	genomic	ADJ
afs-90955	331	4	recursions	recursion	NOUN
afs-90955	331	5	in	in	ADP
afs-90955	331	6	single	single	ADJ
afs-90955	331	7	-	-	PUNCT
afs-90955	331	8	step	step	NOUN
afs-90955	331	9	genomic	genomic	NOUN
afs-90955	331	10	best	good	ADJ
afs-90955	331	11	linear	linear	ADJ
afs-90955	331	12	unbiased	unbiased	ADJ
afs-90955	331	13	predictor	predictor	NOUN
afs-90955	331	14	for	for	ADP
afs-90955	331	15	us	we	PRON
afs-90955	331	16	holsteins	holstein	NOUN
afs-90955	331	17	with	with	ADP
afs-90955	331	18	a	a	DET
afs-90955	331	19	large	large	ADJ
afs-90955	331	20	number	number	NOUN
afs-90955	331	21	of	of	ADP
afs-90955	331	22	genotyped	genotype	VERB
afs-90955	331	23	animals	animal	NOUN
afs-90955	331	24	.	.	PUNCT
afs-90955	332	1	journal	journal	NOUN
afs-90955	332	2	of	of	ADP
afs-90955	332	3	dairy	dairy	NOUN
afs-90955	332	4	science	science	NOUN
afs-90955	332	5	99:1968–1974	99:1968–1974	NUM
afs-90955	332	6	.	.	PUNCT
afs-90955	333	1	https://doi.org/10.3168/jds.2015-10540	https://doi.org/10.3168/jds.2015-10540	PROPN
afs-90955	333	2	ng	ng	PROPN
afs-90955	333	3	,	,	PUNCT
afs-90955	333	4	e.	e.	PROPN
afs-90955	333	5	&	&	CCONJ
afs-90955	333	6	peyton	peyton	PROPN
afs-90955	333	7	,	,	PUNCT
afs-90955	333	8	b.	b.	PROPN
afs-90955	333	9	1993	1993	NUM
afs-90955	333	10	.	.	PUNCT
afs-90955	334	1	block	block	NOUN
afs-90955	334	2	sparse	sparse	ADJ
afs-90955	334	3	cholesky	cholesky	ADJ
afs-90955	334	4	algorithms	algorithm	NOUN
afs-90955	334	5	on	on	ADP
afs-90955	334	6	advanced	advanced	ADJ
afs-90955	334	7	uniprocessor	uniprocessor	NOUN
afs-90955	334	8	computers	computer	NOUN
afs-90955	334	9	.	.	PUNCT
afs-90955	335	1	siam	siam	PROPN
afs-90955	335	2	journal	journal	PROPN
afs-90955	335	3	of	of	ADP
afs-90955	335	4	scientific	scientific	ADJ
afs-90955	335	5	computing	computing	NOUN
afs-90955	335	6	14:1034–1056	14:1034–1056	NUM
afs-90955	335	7	.	.	PUNCT
afs-90955	336	1	https://doi.org/10.1137/0914063	https://doi.org/10.1137/0914063	ADJ
afs-90955	336	2	quaas	quaas	NOUN
afs-90955	336	3	,	,	PUNCT
afs-90955	336	4	r.l	r.l	PROPN
afs-90955	336	5	.	.	PROPN
afs-90955	336	6	1976	1976	NUM
afs-90955	336	7	.	.	PUNCT
afs-90955	337	1	computing	compute	VERB
afs-90955	337	2	the	the	DET
afs-90955	337	3	diagonal	diagonal	ADJ
afs-90955	337	4	elements	element	NOUN
afs-90955	337	5	and	and	CCONJ
afs-90955	337	6	inverse	inverse	NOUN
afs-90955	337	7	of	of	ADP
afs-90955	337	8	a	a	DET
afs-90955	337	9	large	large	ADJ
afs-90955	337	10	numerator	numerator	NOUN
afs-90955	337	11	relationship	relationship	NOUN
afs-90955	337	12	matrix	matrix	NOUN
afs-90955	337	13	.	.	PUNCT
afs-90955	338	1	biometrics	biometric	NOUN
afs-90955	338	2	32:949–953	32:949–953	NUM
afs-90955	338	3	.	.	PUNCT
afs-90955	339	1	https://doi.org/10.2307/2529279	https://doi.org/10.2307/2529279	PROPN
afs-90955	339	2	strandén	strandén	PROPN
afs-90955	339	3	,	,	PUNCT
afs-90955	339	4	i.	i.	PROPN
afs-90955	339	5	&	&	CCONJ
afs-90955	339	6	lidauer	lidauer	PROPN
afs-90955	339	7	,	,	PUNCT
afs-90955	339	8	m.	m.	NOUN
afs-90955	339	9	1999	1999	NUM
afs-90955	339	10	.	.	PUNCT
afs-90955	340	1	solving	solve	VERB
afs-90955	340	2	large	large	ADJ
afs-90955	340	3	mixed	mixed	ADJ
afs-90955	340	4	models	model	NOUN
afs-90955	340	5	using	use	VERB
afs-90955	340	6	preconditioner	preconditioner	NOUN
afs-90955	340	7	conjugate	conjugate	ADJ
afs-90955	340	8	gradient	gradient	ADJ
afs-90955	340	9	iteration	iteration	NOUN
afs-90955	340	10	.	.	PUNCT
afs-90955	341	1	journal	journal	NOUN
afs-90955	341	2	of	of	ADP
afs-90955	341	3	dairy	dairy	NOUN
afs-90955	341	4	science	science	NOUN
afs-90955	341	5	82:2779–2787	82:2779–2787	NUM
afs-90955	341	6	.	.	PUNCT
afs-90955	342	1	https://doi.org/10.3168/jds.s0022-0302(99)75535-9	https://doi.org/10.3168/jds.s0022-0302(99)75535-9	PROPN
afs-90955	342	2	strandén	strandén	PROPN
afs-90955	342	3	,	,	PUNCT
afs-90955	342	4	i.	i.	PROPN
afs-90955	342	5	,	,	PUNCT
afs-90955	342	6	matilainen	matilainen	PROPN
afs-90955	342	7	,	,	PUNCT
afs-90955	342	8	k.	k.	PROPN
afs-90955	342	9	,	,	PUNCT
afs-90955	342	10	aamand	aamand	PROPN
afs-90955	342	11	,	,	PUNCT
afs-90955	342	12	g.	g.	PROPN
afs-90955	342	13	&	&	CCONJ
afs-90955	342	14	mäntysaari	mäntysaari	PROPN
afs-90955	342	15	,	,	PUNCT
afs-90955	342	16	e.a	e.a	PROPN
afs-90955	342	17	.	.	PROPN
afs-90955	342	18	2017	2017	NUM
afs-90955	342	19	.	.	PUNCT
afs-90955	343	1	solving	solve	VERB
afs-90955	343	2	efficiently	efficiently	ADV
afs-90955	343	3	large	large	ADJ
afs-90955	343	4	single	single	ADJ
afs-90955	343	5	-	-	PUNCT
afs-90955	343	6	step	step	NOUN
afs-90955	343	7	genomic	genomic	NOUN
afs-90955	343	8	best	good	ADJ
afs-90955	343	9	linear	linear	ADJ
afs-90955	343	10	unbiased	unbiased	ADJ
afs-90955	343	11	prediction	prediction	NOUN
afs-90955	343	12	models	model	NOUN
afs-90955	343	13	.	.	PUNCT
afs-90955	344	1	journal	journal	NOUN
afs-90955	344	2	of	of	ADP
afs-90955	344	3	animal	animal	NOUN
afs-90955	344	4	breeding	breeding	NOUN
afs-90955	344	5	and	and	CCONJ
afs-90955	344	6	genetics	genetic	NOUN
afs-90955	344	7	134:264–274	134:264–274	NUM
afs-90955	344	8	.	.	PUNCT
afs-90955	345	1	https://doi.org/10.1111/jbg.12257	https://doi.org/10.1111/jbg.12257	NOUN
afs-90955	345	2	taskinen	taskinen	NOUN
afs-90955	345	3	,	,	PUNCT
afs-90955	345	4	m.	m.	NOUN
afs-90955	345	5	,	,	PUNCT
afs-90955	345	6	mäntysaari	mäntysaari	PROPN
afs-90955	345	7	,	,	PUNCT
afs-90955	345	8	e.a	e.a	PROPN
afs-90955	345	9	.	.	PROPN
afs-90955	345	10	&	&	CCONJ
afs-90955	345	11	strandén	strandén	PROPN
afs-90955	345	12	,	,	PUNCT
afs-90955	345	13	i.	i.	PROPN
afs-90955	345	14	2017	2017	NUM
afs-90955	345	15	.	.	PUNCT
afs-90955	346	1	single	single	ADJ
afs-90955	346	2	-	-	PUNCT
afs-90955	346	3	step	step	NOUN
afs-90955	346	4	snp	snp	NOUN
afs-90955	346	5	-	-	NOUN
afs-90955	346	6	blup	blup	NOUN
afs-90955	346	7	with	with	ADP
afs-90955	346	8	on	on	ADP
afs-90955	346	9	-	-	PUNCT
afs-90955	346	10	the	the	DET
afs-90955	346	11	-	-	PUNCT
afs-90955	346	12	fly	fly	NOUN
afs-90955	346	13	imputed	impute	VERB
afs-90955	346	14	genotypes	genotype	NOUN
afs-90955	346	15	and	and	CCONJ
afs-90955	346	16	residual	residual	ADJ
afs-90955	346	17	polygenic	polygenic	ADJ
afs-90955	346	18	effects	effect	NOUN
afs-90955	346	19	.	.	PUNCT
afs-90955	347	1	genetics	genetic	NOUN
afs-90955	347	2	selection	selection	NOUN
afs-90955	347	3	evolution	evolution	NOUN
afs-90955	347	4	49:36	49:36	NUM
afs-90955	347	5	.	.	PUNCT
afs-90955	348	1	https://doi.org/10.1186/s12711-017-0310-9	https://doi.org/10.1186/s12711-017-0310-9	PROPN
afs-90955	348	2	vanraden	vanraden	PROPN
afs-90955	348	3	,	,	PUNCT
afs-90955	348	4	p.m.	p.m.	NOUN
afs-90955	348	5	2008	2008	NUM
afs-90955	348	6	.	.	PUNCT
afs-90955	349	1	efficient	efficient	ADJ
afs-90955	349	2	methods	method	NOUN
afs-90955	349	3	to	to	PART
afs-90955	349	4	compute	compute	VERB
afs-90955	349	5	genomic	genomic	ADJ
afs-90955	349	6	predictions	prediction	NOUN
afs-90955	349	7	.	.	PUNCT
afs-90955	350	1	journal	journal	NOUN
afs-90955	350	2	of	of	ADP
afs-90955	350	3	dairy	dairy	NOUN
afs-90955	350	4	science	science	NOUN
afs-90955	350	5	91:4414–4423	91:4414–4423	NUM
afs-90955	350	6	.	.	PUNCT
afs-90955	351	1	https://doi.org/10.1111/jbg.12257	https://doi.org/10.1111/jbg.12257	NOUN
afs-90955	351	2	agricultural	agricultural	ADJ
afs-90955	351	3	and	and	CCONJ
afs-90955	351	4	food	food	NOUN
afs-90955	351	5	science	science	PROPN
afs-90955	351	6	i.	i.	PROPN
afs-90955	351	7	strandén	strandén	PROPN
afs-90955	351	8	&	&	CCONJ
afs-90955	351	9	e.a	e.a	PROPN
afs-90955	351	10	.	.	PROPN
afs-90955	351	11	mäntysaari	mäntysaari	PROPN
afs-90955	351	12	(	(	PUNCT
afs-90955	351	13	2020	2020	NUM
afs-90955	351	14	)	)	PUNCT
afs-90955	351	15	29	29	NUM
afs-90955	351	16	:	:	PUNCT
afs-90955	351	17	166–176	166–176	NUM
afs-90955	351	18	175	175	NUM
afs-90955	351	19	appendix	appendix	NOUN
afs-90955	351	20	:	:	PUNCT
afs-90955	351	21	solving	solve	VERB
afs-90955	351	22	y1=(a11)-1x1	y1=(a11)-1x1	NOUN
afs-90955	351	23	iteratively	iteratively	ADV
afs-90955	351	24	bpop	bpop	PROPN
afs-90955	351	25	program	program	NOUN
afs-90955	351	26	has	have	VERB
afs-90955	351	27	three	three	NUM
afs-90955	351	28	alternative	alternative	ADJ
afs-90955	351	29	approaches	approach	NOUN
afs-90955	351	30	to	to	PART
afs-90955	351	31	solve	solve	VERB
afs-90955	351	32	the	the	DET
afs-90955	351	33	equation	equation	NOUN
afs-90955	351	34	a11	a11	PROPN
afs-90955	351	35	y1=	y1=	PROPN
afs-90955	351	36	x1.in	x1.in	PROPN
afs-90955	351	37	two	two	NUM
afs-90955	351	38	of	of	ADP
afs-90955	351	39	the	the	DET
afs-90955	351	40	approaches	approach	NOUN
afs-90955	351	41	,	,	PUNCT
afs-90955	351	42	preconditioned	precondition	VERB
afs-90955	351	43	conjugate	conjugate	ADJ
afs-90955	351	44	gradient	gradient	NOUN
afs-90955	351	45	(	(	PUNCT
afs-90955	351	46	pcg	pcg	PROPN
afs-90955	351	47	)	)	PUNCT
afs-90955	351	48	iteration	iteration	NOUN
afs-90955	351	49	is	be	AUX
afs-90955	351	50	used	use	VERB
afs-90955	351	51	.	.	PUNCT
afs-90955	352	1	these	these	DET
afs-90955	352	2	two	two	NUM
afs-90955	352	3	alternatives	alternative	NOUN
afs-90955	352	4	use	use	VERB
afs-90955	352	5	either	either	CCONJ
afs-90955	352	6	a	a	DET
afs-90955	352	7	a11	a11	PROPN
afs-90955	352	8	matrix	matrix	NOUN
afs-90955	352	9	stored	store	VERB
afs-90955	352	10	in	in	ADP
afs-90955	352	11	memory	memory	NOUN
afs-90955	352	12	(	(	PUNCT
afs-90955	352	13	the	the	DET
afs-90955	352	14	i	i	NOUN
afs-90955	352	15	m	m	VERB
afs-90955	352	16	approach	approach	NOUN
afs-90955	352	17	)	)	PUNCT
afs-90955	352	18	or	or	CCONJ
afs-90955	352	19	a	a	DET
afs-90955	352	20	pedigree	pedigree	ADJ
afs-90955	352	21	list	list	NOUN
afs-90955	352	22	information	information	NOUN
afs-90955	352	23	without	without	ADP
afs-90955	352	24	explicitly	explicitly	ADV
afs-90955	352	25	making	make	VERB
afs-90955	352	26	a11	a11	PROPN
afs-90955	352	27	(	(	PUNCT
afs-90955	352	28	the	the	DET
afs-90955	352	29	iop	iop	PROPN
afs-90955	352	30	approach	approach	NOUN
afs-90955	352	31	)	)	PUNCT
afs-90955	352	32	for	for	ADP
afs-90955	352	33	the	the	DET
afs-90955	352	34	necessary	necessary	ADJ
afs-90955	352	35	computations	computation	NOUN
afs-90955	352	36	in	in	ADP
afs-90955	352	37	pcg	pcg	PROPN
afs-90955	352	38	iteration	iteration	NOUN
afs-90955	352	39	.	.	PUNCT
afs-90955	353	1	all	all	DET
afs-90955	353	2	three	three	NUM
afs-90955	353	3	approaches	approach	NOUN
afs-90955	353	4	use	use	VERB
afs-90955	353	5	the	the	DET
afs-90955	353	6	same	same	ADJ
afs-90955	353	7	rules	rule	NOUN
afs-90955	353	8	as	as	ADP
afs-90955	353	9	those	those	PRON
afs-90955	353	10	used	use	VERB
afs-90955	353	11	to	to	PART
afs-90955	353	12	make	make	VERB
afs-90955	353	13	the	the	DET
afs-90955	353	14	full	full	ADJ
afs-90955	353	15	a-1	a-1	NOUN
afs-90955	353	16	using	use	VERB
afs-90955	353	17	a	a	DET
afs-90955	353	18	pedigree	pedigree	ADJ
afs-90955	353	19	list	list	NOUN
afs-90955	353	20	(	(	PUNCT
afs-90955	353	21	henderson	henderson	PROPN
afs-90955	353	22	1976	1976	NUM
afs-90955	353	23	,	,	PUNCT
afs-90955	353	24	quaas	quaas	NOUN
afs-90955	353	25	1976	1976	NUM
afs-90955	353	26	)	)	PUNCT
afs-90955	353	27	.	.	PUNCT
afs-90955	354	1	in	in	ADP
afs-90955	354	2	the	the	DET
afs-90955	354	3	pcg	pcg	PROPN
afs-90955	354	4	method	method	NOUN
afs-90955	354	5	(	(	PUNCT
afs-90955	354	6	e.g.	e.g.	ADV
afs-90955	354	7	,	,	PUNCT
afs-90955	354	8	strandén	strandén	NOUN
afs-90955	354	9	and	and	CCONJ
afs-90955	354	10	lidauer	lidauer	NOUN
afs-90955	354	11	1999	1999	NUM
afs-90955	354	12	)	)	PUNCT
afs-90955	354	13	used	use	VERB
afs-90955	354	14	by	by	ADP
afs-90955	354	15	the	the	DET
afs-90955	354	16	i	i	PROPN
afs-90955	354	17	m	m	VERB
afs-90955	354	18	and	and	CCONJ
afs-90955	354	19	iop	iop	NOUN
afs-90955	354	20	approaches	approach	NOUN
afs-90955	354	21	,	,	PUNCT
afs-90955	354	22	each	each	DET
afs-90955	354	23	iteration	iteration	NOUN
afs-90955	354	24	requires	require	VERB
afs-90955	354	25	multiplication	multiplication	NOUN
afs-90955	354	26	of	of	ADP
afs-90955	354	27	the	the	DET
afs-90955	354	28	current	current	ADJ
afs-90955	354	29	search	search	NOUN
afs-90955	354	30	direction	direction	NOUN
afs-90955	354	31	vector	vector	NOUN
afs-90955	354	32	d1	d1	PROPN
afs-90955	354	33	by	by	ADP
afs-90955	354	34	the	the	DET
afs-90955	354	35	coefficient	coefficient	NOUN
afs-90955	354	36	matrix	matrix	NOUN
afs-90955	354	37	a11	a11	PROPN
afs-90955	354	38	.	.	PUNCT
afs-90955	355	1	thus	thus	ADV
afs-90955	355	2	,	,	PUNCT
afs-90955	355	3	every	every	DET
afs-90955	355	4	iteration	iteration	NOUN
afs-90955	355	5	of	of	ADP
afs-90955	355	6	pcg	pcg	PROPN
afs-90955	355	7	calculates	calculate	VERB
afs-90955	355	8	product	product	NOUN
afs-90955	355	9	s=	s=	PROPN
afs-90955	355	10	a11d1	a11d1	PROPN
afs-90955	355	11	.	.	PUNCT
afs-90955	356	1	in	in	ADP
afs-90955	356	2	the	the	DET
afs-90955	356	3	following	following	NOUN
afs-90955	356	4	,	,	PUNCT
afs-90955	356	5	we	we	PRON
afs-90955	356	6	will	will	AUX
afs-90955	356	7	be	be	AUX
afs-90955	356	8	described	describe	VERB
afs-90955	356	9	the	the	DET
afs-90955	356	10	computational	computational	ADJ
afs-90955	356	11	steps	step	NOUN
afs-90955	356	12	for	for	ADP
afs-90955	356	13	this	this	DET
afs-90955	356	14	product	product	NOUN
afs-90955	356	15	in	in	ADP
afs-90955	356	16	the	the	DET
afs-90955	356	17	iop	iop	NOUN
afs-90955	356	18	approach	approach	NOUN
afs-90955	356	19	.	.	PUNCT
afs-90955	357	1	the	the	DET
afs-90955	357	2	product	product	NOUN
afs-90955	357	3	s=	s=	NOUN
afs-90955	357	4	a11d1can	a11d1can	PROPN
afs-90955	357	5	be	be	AUX
afs-90955	357	6	computed	compute	VERB
afs-90955	357	7	by	by	ADP
afs-90955	357	8	considering	consider	VERB
afs-90955	357	9	the	the	DET
afs-90955	357	10	full	full	ADJ
afs-90955	357	11	a-1d	a-1d	PROPN
afs-90955	357	12	matrix	matrix	NOUN
afs-90955	357	13	product	product	NOUN
afs-90955	357	14	rules	rule	NOUN
afs-90955	357	15	,	,	PUNCT
afs-90955	357	16	where	where	SCONJ
afs-90955	357	17	d2=0	d2=0	PROPN
afs-90955	357	18	,	,	PUNCT
afs-90955	357	19	and	and	CCONJ
afs-90955	357	20	by	by	ADP
afs-90955	357	21	updating	update	VERB
afs-90955	357	22	only	only	ADV
afs-90955	357	23	those	those	DET
afs-90955	357	24	elements	element	NOUN
afs-90955	357	25	that	that	PRON
afs-90955	357	26	change	change	VERB
afs-90955	357	27	vector	vector	NOUN
afs-90955	357	28	,	,	PUNCT
afs-90955	357	29	i.e.	i.e.	X
afs-90955	357	30	,	,	PUNCT
afs-90955	357	31	non	non	ADJ
afs-90955	357	32	-	-	ADJ
afs-90955	357	33	genotyped	genotyped	ADJ
afs-90955	357	34	ancestors	ancestor	NOUN
afs-90955	357	35	to	to	ADP
afs-90955	357	36	the	the	DET
afs-90955	357	37	genotyped	genotype	VERB
afs-90955	357	38	animals	animal	NOUN
afs-90955	357	39	.	.	PUNCT
afs-90955	358	1	according	accord	VERB
afs-90955	358	2	to	to	ADP
afs-90955	358	3	the	the	DET
afs-90955	358	4	rules	rule	NOUN
afs-90955	358	5	of	of	ADP
afs-90955	358	6	making	make	VERB
afs-90955	358	7	a-1	a-1	PROPN
afs-90955	358	8	(	(	PUNCT
afs-90955	358	9	henderson	henderson	PROPN
afs-90955	358	10	1976	1976	NUM
afs-90955	358	11	,	,	PUNCT
afs-90955	358	12	quaas	quaas	NOUN
afs-90955	358	13	1976	1976	NUM
afs-90955	358	14	)	)	PUNCT
afs-90955	358	15	,	,	PUNCT
afs-90955	358	16	the	the	DET
afs-90955	358	17	product	product	NOUN
afs-90955	358	18	a-1d	a-1d	PROPN
afs-90955	358	19	can	can	AUX
afs-90955	358	20	be	be	AUX
afs-90955	358	21	computed	compute	VERB
afs-90955	358	22	by	by	ADP
afs-90955	358	23	proceeding	proceed	VERB
afs-90955	358	24	the	the	DET
afs-90955	358	25	pedigree	pedigree	NOUN
afs-90955	358	26	list	list	NOUN
afs-90955	358	27	(	(	PUNCT
afs-90955	358	28	in	in	ADP
afs-90955	358	29	any	any	DET
afs-90955	358	30	order	order	NOUN
afs-90955	358	31	)	)	PUNCT
afs-90955	358	32	and	and	CCONJ
afs-90955	358	33	updating	update	VERB
afs-90955	358	34	elements	element	NOUN
afs-90955	358	35	of	of	ADP
afs-90955	358	36	individual	individual	ADJ
afs-90955	358	37	i	i	PROPN
afs-90955	358	38	,	,	PUNCT
afs-90955	358	39	its	its	PRON
afs-90955	358	40	sire	sire	NOUN
afs-90955	358	41	s	s	NOUN
afs-90955	358	42	and	and	CCONJ
afs-90955	358	43	dam	dam	PROPN
afs-90955	358	44	d	d	PROPN
afs-90955	358	45	in	in	ADP
afs-90955	358	46	the	the	DET
afs-90955	358	47	result	result	NOUN
afs-90955	358	48	vector	vector	NOUN
afs-90955	358	49	s.	s.	PROPN
afs-90955	358	50	for	for	ADP
afs-90955	358	51	example	example	NOUN
afs-90955	358	52	,	,	PUNCT
afs-90955	358	53	when	when	SCONJ
afs-90955	358	54	both	both	DET
afs-90955	358	55	parents	parent	NOUN
afs-90955	358	56	are	be	AUX
afs-90955	358	57	known	know	VERB
afs-90955	358	58	,	,	PUNCT
afs-90955	358	59	update	update	NOUN
afs-90955	358	60	for	for	ADP
afs-90955	358	61	individual	individual	ADJ
afs-90955	358	62	i	i	PROPN
afs-90955	358	63	and	and	CCONJ
afs-90955	358	64	its	its	PRON
afs-90955	358	65	parents	parent	NOUN
afs-90955	358	66	is	be	AUX
afs-90955	358	67	where	where	SCONJ
afs-90955	358	68	fi	fi	NOUN
afs-90955	358	69	=	=	SYM
afs-90955	358	70	4/(4	4/(4	NUM
afs-90955	358	71	–	–	PUNCT
afs-90955	358	72	k	k	X
afs-90955	358	73	–	–	PUNCT
afs-90955	358	74	fs	fs	ADJ
afs-90955	358	75	–	–	PUNCT
afs-90955	358	76	fd	fd	X
afs-90955	358	77	)	)	PUNCT
afs-90955	358	78	,	,	PUNCT
afs-90955	358	79	k=2	k=2	PROPN
afs-90955	358	80	is	be	AUX
afs-90955	358	81	the	the	DET
afs-90955	358	82	number	number	NOUN
afs-90955	358	83	of	of	ADP
afs-90955	358	84	known	know	VERB
afs-90955	358	85	parents	parent	NOUN
afs-90955	358	86	to	to	ADP
afs-90955	358	87	individual	individual	PROPN
afs-90955	358	88	i	i	PROPN
afs-90955	358	89	,	,	PUNCT
afs-90955	358	90	fs	fs	PROPN
afs-90955	358	91	is	be	AUX
afs-90955	358	92	inbreeding	inbreede	VERB
afs-90955	358	93	coefficient	coefficient	NOUN
afs-90955	358	94	of	of	ADP
afs-90955	358	95	sire	sire	NOUN
afs-90955	358	96	,	,	PUNCT
afs-90955	358	97	and	and	CCONJ
afs-90955	358	98	fd	fd	PROPN
afs-90955	358	99	is	be	AUX
afs-90955	358	100	inbreeding	inbreede	VERB
afs-90955	358	101	coefficient	coefficient	NOUN
afs-90955	358	102	of	of	ADP
afs-90955	358	103	dam	dam	PROPN
afs-90955	358	104	.	.	PUNCT
afs-90955	359	1	corresponding	correspond	VERB
afs-90955	359	2	update	update	NOUN
afs-90955	359	3	formulas	formula	NOUN
afs-90955	359	4	are	be	AUX
afs-90955	359	5	available	available	ADJ
afs-90955	359	6	for	for	ADP
afs-90955	359	7	individuals	individual	NOUN
afs-90955	359	8	with	with	ADP
afs-90955	359	9	only	only	ADV
afs-90955	359	10	one	one	NUM
afs-90955	359	11	or	or	CCONJ
afs-90955	359	12	no	no	DET
afs-90955	359	13	known	know	VERB
afs-90955	359	14	parents	parent	NOUN
afs-90955	359	15	.	.	PUNCT
afs-90955	360	1	note	note	VERB
afs-90955	360	2	that	that	SCONJ
afs-90955	360	3	the	the	DET
afs-90955	360	4	computations	computation	NOUN
afs-90955	360	5	can	can	AUX
afs-90955	360	6	be	be	AUX
afs-90955	360	7	efficiently	efficiently	ADV
afs-90955	360	8	performed	perform	VERB
afs-90955	360	9	from	from	ADP
afs-90955	360	10	right	right	ADJ
afs-90955	360	11	to	to	ADP
afs-90955	360	12	left	leave	VERB
afs-90955	360	13	such	such	ADJ
afs-90955	360	14	that	that	SCONJ
afs-90955	360	15	no	no	DET
afs-90955	360	16	matrices	matrix	NOUN
afs-90955	360	17	are	be	AUX
afs-90955	360	18	stored	store	VERB
afs-90955	360	19	(	(	PUNCT
afs-90955	360	20	strandén	strandén	NOUN
afs-90955	360	21	and	and	CCONJ
afs-90955	360	22	lidauer	lidauer	NOUN
afs-90955	360	23	1999	1999	NUM
afs-90955	360	24	):	):	PUNCT
afs-90955	360	25	1	1	NUM
afs-90955	360	26	)	)	PUNCT
afs-90955	360	27	2	2	NUM
afs-90955	360	28	)	)	PUNCT
afs-90955	360	29	.	.	PUNCT
afs-90955	361	1	because	because	SCONJ
afs-90955	361	2	the	the	DET
afs-90955	361	3	iop	iop	NOUN
afs-90955	361	4	approach	approach	NOUN
afs-90955	361	5	is	be	AUX
afs-90955	361	6	used	use	VERB
afs-90955	361	7	to	to	PART
afs-90955	361	8	calculate	calculate	VERB
afs-90955	361	9	s	s	PROPN
afs-90955	361	10	=	=	NOUN
afs-90955	361	11	a11d1	a11d1	NOUN
afs-90955	361	12	,	,	PUNCT
afs-90955	361	13	not	not	PART
afs-90955	361	14	a-1d	a-1d	PROPN
afs-90955	361	15	,	,	PUNCT
afs-90955	361	16	the	the	DET
afs-90955	361	17	multiplications	multiplication	NOUN
afs-90955	361	18	of	of	ADP
afs-90955	361	19	d	d	NOUN
afs-90955	361	20	can	can	AUX
afs-90955	361	21	be	be	AUX
afs-90955	361	22	limited	limit	VERB
afs-90955	361	23	to	to	ADP
afs-90955	361	24	the	the	DET
afs-90955	361	25	nongenotyped	nongenotyped	ADJ
afs-90955	361	26	ancestors	ancestor	NOUN
afs-90955	361	27	of	of	ADP
afs-90955	361	28	the	the	DET
afs-90955	361	29	genotyped	genotype	VERB
afs-90955	361	30	animals	animal	NOUN
afs-90955	361	31	.	.	PUNCT
afs-90955	362	1	likewise	likewise	ADV
afs-90955	362	2	,	,	PUNCT
afs-90955	362	3	the	the	DET
afs-90955	362	4	update	update	NOUN
afs-90955	362	5	is	be	AUX
afs-90955	362	6	applied	apply	VERB
afs-90955	362	7	to	to	ADP
afs-90955	362	8	these	these	DET
afs-90955	362	9	non	non	ADJ
afs-90955	362	10	-	-	ADJ
afs-90955	362	11	genotyped	genotyped	ADJ
afs-90955	362	12	ancestors	ancestor	NOUN
afs-90955	362	13	as	as	ADV
afs-90955	362	14	well	well	ADV
afs-90955	362	15	.	.	PUNCT
afs-90955	363	1	figure	figure	NOUN
afs-90955	363	2	1	1	NUM
afs-90955	363	3	has	have	VERB
afs-90955	363	4	a	a	DET
afs-90955	363	5	fortran	fortran	ADJ
afs-90955	363	6	-	-	PUNCT
afs-90955	363	7	type	type	NOUN
afs-90955	363	8	pseudo	pseudo	NOUN
afs-90955	363	9	code	code	NOUN
afs-90955	363	10	for	for	ADP
afs-90955	363	11	the	the	DET
afs-90955	363	12	multiplication	multiplication	NOUN
afs-90955	363	13	s	s	NOUN
afs-90955	363	14	=	=	NOUN
afs-90955	363	15	a11d1	a11d1	NOUN
afs-90955	363	16	.	.	PUNCT
afs-90955	364	1	the	the	DET
afs-90955	364	2	‘	'	PUNCT
afs-90955	364	3	pedigree	pedigree	ADJ
afs-90955	364	4	’	'	PUNCT
afs-90955	364	5	table	table	NOUN
afs-90955	364	6	has	have	VERB
afs-90955	364	7	pedigree	pedigree	ADJ
afs-90955	364	8	information	information	NOUN
afs-90955	364	9	for	for	ADP
afs-90955	364	10	all	all	DET
afs-90955	364	11	genotyped	genotype	VERB
afs-90955	364	12	animals	animal	NOUN
afs-90955	364	13	and	and	CCONJ
afs-90955	364	14	their	their	PRON
afs-90955	364	15	ancestors	ancestor	NOUN
afs-90955	364	16	.	.	PUNCT
afs-90955	365	1	for	for	ADP
afs-90955	365	2	every	every	DET
afs-90955	365	3	individual	individual	NOUN
afs-90955	365	4	,	,	PUNCT
afs-90955	365	5	the	the	DET
afs-90955	365	6	pedigree	pedigree	NOUN
afs-90955	365	7	has	have	VERB
afs-90955	365	8	three	three	NUM
afs-90955	365	9	numbers	number	NOUN
afs-90955	365	10	:	:	PUNCT
afs-90955	365	11	individual	individual	ADJ
afs-90955	365	12	,	,	PUNCT
afs-90955	365	13	sire	sire	NOUN
afs-90955	365	14	and	and	CCONJ
afs-90955	365	15	dam	dam	NOUN
afs-90955	365	16	i	i	PROPN
afs-90955	365	17	d	d	PROPN
afs-90955	365	18	numbers	number	NOUN
afs-90955	365	19	.	.	PUNCT
afs-90955	366	1	in	in	ADP
afs-90955	366	2	the	the	DET
afs-90955	366	3	bpop	bpop	PROPN
afs-90955	366	4	program	program	NOUN
afs-90955	366	5	,	,	PUNCT
afs-90955	366	6	the	the	DET
afs-90955	366	7	full	full	ADJ
afs-90955	366	8	pedigree	pedigree	NOUN
afs-90955	366	9	has	have	AUX
afs-90955	366	10	been	be	AUX
afs-90955	366	11	pruned	prune	VERB
afs-90955	366	12	to	to	PART
afs-90955	366	13	have	have	VERB
afs-90955	366	14	the	the	DET
afs-90955	366	15	genotyped	genotype	VERB
afs-90955	366	16	animals	animal	NOUN
afs-90955	366	17	and	and	CCONJ
afs-90955	366	18	their	their	PRON
afs-90955	366	19	ancestors	ancestor	NOUN
afs-90955	366	20	.	.	PUNCT
afs-90955	367	1	furthermore	furthermore	ADV
afs-90955	367	2	,	,	PUNCT
afs-90955	367	3	the	the	DET
afs-90955	367	4	animal	animal	NOUN
afs-90955	367	5	i	i	PROPN
afs-90955	367	6	d	d	PROPN
afs-90955	367	7	codes	code	NOUN
afs-90955	367	8	have	have	AUX
afs-90955	367	9	been	be	AUX
afs-90955	367	10	renumbered	renumbered	ADJ
afs-90955	367	11	to	to	PART
afs-90955	367	12	be	be	AUX
afs-90955	367	13	consecutive	consecutive	ADJ
afs-90955	367	14	integer	integer	NOUN
afs-90955	367	15	numbers	number	NOUN
afs-90955	367	16	from	from	ADP
afs-90955	367	17	one	one	NUM
afs-90955	367	18	to	to	ADP
afs-90955	367	19	the	the	DET
afs-90955	367	20	number	number	NOUN
afs-90955	367	21	of	of	ADP
afs-90955	367	22	animals	animal	NOUN
afs-90955	367	23	n.	n.	VERB
afs-90955	367	24	there	there	PRON
afs-90955	367	25	are	be	VERB
afs-90955	367	26	three	three	NUM
afs-90955	367	27	vectors	vector	NOUN
afs-90955	367	28	.	.	PUNCT
afs-90955	368	1	vector	vector	NOUN
afs-90955	368	2	f	f	PROPN
afs-90955	368	3	has	have	VERB
afs-90955	368	4	the	the	DET
afs-90955	368	5	pre	pre	ADJ
afs-90955	368	6	-	-	ADJ
afs-90955	368	7	calculated	calculated	ADJ
afs-90955	368	8	inbreeding	inbreede	VERB
afs-90955	368	9	coefficients	coefficient	NOUN
afs-90955	368	10	,	,	PUNCT
afs-90955	368	11	vector	vector	NOUN
afs-90955	368	12	d	d	PROPN
afs-90955	368	13	has	have	VERB
afs-90955	368	14	the	the	DET
afs-90955	368	15	current	current	ADJ
afs-90955	368	16	values	value	NOUN
afs-90955	368	17	to	to	PART
afs-90955	368	18	be	be	AUX
afs-90955	368	19	multiplied	multiply	VERB
afs-90955	368	20	by	by	ADP
afs-90955	368	21	a11	a11	PROPN
afs-90955	368	22	,	,	PUNCT
afs-90955	368	23	and	and	CCONJ
afs-90955	368	24	vector	vector	NOUN
afs-90955	368	25	s	s	PART
afs-90955	368	26	will	will	AUX
afs-90955	368	27	have	have	VERB
afs-90955	368	28	the	the	DET
afs-90955	368	29	result	result	NOUN
afs-90955	368	30	of	of	ADP
afs-90955	368	31	the	the	DET
afs-90955	368	32	multiplication	multiplication	NOUN
afs-90955	368	33	.	.	PUNCT
afs-90955	369	1	supdate	supdate	NOUN
afs-90955	369	2	=	=	PROPN
afs-90955	369	3	fi	fi	NOUN
afs-90955	369	4	�	�	PROPN
afs-90955	369	5	-0.5	-0.5	PROPN
afs-90955	369	6	-0.5	-0.5	X
afs-90955	369	7	1	1	NUM
afs-90955	369	8	�	�	PROPN
afs-90955	369	9	[	[	X
afs-90955	369	10	-0.5	-0.5	X
afs-90955	369	11	-0.5	-0.5	X
afs-90955	369	12	1	1	NUM
afs-90955	369	13	]	]	X
afs-90955	369	14	�	�	X
afs-90955	369	15	ds	ds	PROPN
afs-90955	369	16	dd	dd	NOUN
afs-90955	369	17	di	di	X
afs-90955	369	18	�	�	PROPN
afs-90955	369	19	w	w	PROPN
afs-90955	369	20	1	1	NUM
afs-90955	369	21	)	)	PUNCT
afs-90955	369	22	c=[-0.5	c=[-0.5	NUM
afs-90955	369	23	-0.5	-0.5	PROPN
afs-90955	369	24	1	1	NUM
afs-90955	369	25	]	]	X
afs-90955	369	26	�	�	X
afs-90955	369	27	ds	ds	PROPN
afs-90955	369	28	dd	dd	NOUN
afs-90955	369	29	di	di	X
afs-90955	369	30	�	�	PROPN
afs-90955	369	31	1	1	NUM
afs-90955	369	32	)	)	PUNCT
afs-90955	369	33	𝐬𝐬𝐬𝐬𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢	𝐬𝐬𝐬𝐬𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢	NOUN
afs-90955	370	1	=	=	SYM
afs-90955	370	2	�	�	PROPN
afs-90955	370	3	−0.5𝑐𝑐𝑐𝑐𝑓𝑓𝑓𝑓𝑖𝑖𝑖𝑖	−0.5𝑐𝑐𝑐𝑐𝑓𝑓𝑓𝑓𝑖𝑖𝑖𝑖	NOUN
afs-90955	370	4	−0.5𝑐𝑐𝑐𝑐𝑓𝑓𝑓𝑓𝑖𝑖𝑖𝑖	−0.5𝑐𝑐𝑐𝑐𝑓𝑓𝑓𝑓𝑖𝑖𝑖𝑖	NOUN
afs-90955	370	5	𝑐𝑐𝑐𝑐𝑓𝑓𝑓𝑓𝑖𝑖𝑖𝑖	𝑐𝑐𝑐𝑐𝑓𝑓𝑓𝑓𝑖𝑖𝑖𝑖	NOUN
afs-90955	370	6	�	�	PROPN
afs-90955	370	7	.	.	PROPN
afs-90955	370	8	agricultural	agricultural	ADJ
afs-90955	370	9	and	and	CCONJ
afs-90955	370	10	food	food	NOUN
afs-90955	370	11	science	science	PROPN
afs-90955	370	12	i.	i.	PROPN
afs-90955	370	13	strandén	strandén	PROPN
afs-90955	370	14	&	&	CCONJ
afs-90955	370	15	e.a	e.a	PROPN
afs-90955	370	16	.	.	PROPN
afs-90955	370	17	mäntysaari	mäntysaari	PROPN
afs-90955	370	18	(	(	PUNCT
afs-90955	370	19	2020	2020	NUM
afs-90955	370	20	)	)	PUNCT
afs-90955	370	21	29	29	NUM
afs-90955	370	22	:	:	PUNCT
afs-90955	370	23	166–176	166–176	NUM
afs-90955	370	24	176	176	NUM
afs-90955	370	25	s	s	X
afs-90955	370	26	=	=	SYM
afs-90955	370	27	0	0	PROPN
afs-90955	370	28	do	do	AUX
afs-90955	370	29	i=1,n	i=1,n	PROPN
afs-90955	370	30	(	(	PUNCT
afs-90955	370	31	i	i	PROPN
afs-90955	370	32	d	d	PROPN
afs-90955	370	33	,	,	PUNCT
afs-90955	370	34	sire	sire	NOUN
afs-90955	370	35	,	,	PUNCT
afs-90955	370	36	dam	dam	NOUN
afs-90955	370	37	)	)	PUNCT
afs-90955	370	38	=	=	SYM
afs-90955	370	39	pedigree(i	pedigree(i	NOUN
afs-90955	370	40	)	)	PUNCT
afs-90955	370	41	!	!	PUNCT
afs-90955	371	1	i	i	PRON
afs-90955	371	2	d	d	PROPN
afs-90955	371	3	,	,	PUNCT
afs-90955	371	4	its	its	PRON
afs-90955	371	5	sire	sire	NOUN
afs-90955	371	6	and	and	CCONJ
afs-90955	371	7	dam	dam	NOUN
afs-90955	371	8	numbers	number	NOUN
afs-90955	371	9	!	!	PUNCT
afs-90955	372	1	step	step	NOUN
afs-90955	372	2	1	1	NUM
afs-90955	372	3	):	):	PUNCT
afs-90955	372	4	compute	compute	NOUN
afs-90955	372	5	multiplier	multipli	ADJ
afs-90955	372	6	c	c	PROPN
afs-90955	372	7	k	k	PROPN
afs-90955	372	8	=	=	NOUN
afs-90955	372	9	0	0	PUNCT
afs-90955	372	10	!	!	PUNCT
afs-90955	373	1	number	number	NOUN
afs-90955	373	2	of	of	ADP
afs-90955	373	3	known	know	VERB
afs-90955	373	4	parents	parent	NOUN
afs-90955	373	5	f	f	NOUN
afs-90955	373	6	=	=	SYM
afs-90955	373	7	0	0	PROPN
afs-90955	373	8	!	!	PUNCT
afs-90955	374	1	sum	sum	NOUN
afs-90955	374	2	of	of	ADP
afs-90955	374	3	parent	parent	NOUN
afs-90955	374	4	inbreeding	inbreede	VERB
afs-90955	374	5	coefficients	coefficient	NOUN
afs-90955	374	6	c	c	NOUN
afs-90955	374	7	=	=	SYM
afs-90955	374	8	0	0	PROPN
afs-90955	374	9	!	!	PUNCT
afs-90955	375	1	result	result	VERB
afs-90955	375	2	from	from	ADP
afs-90955	375	3	the	the	DET
afs-90955	375	4	first	first	ADJ
afs-90955	375	5	step	step	NOUN
afs-90955	375	6	multiplication	multiplication	NOUN
afs-90955	375	7	if	if	SCONJ
afs-90955	375	8	(	(	PUNCT
afs-90955	375	9	sire	sire	NOUN
afs-90955	375	10	>	>	X
afs-90955	375	11	0	0	NUM
afs-90955	375	12	)	)	PUNCT
afs-90955	375	13	then	then	ADV
afs-90955	375	14	!	!	PUNCT
afs-90955	376	1	sire	sire	NOUN
afs-90955	376	2	known	know	VERB
afs-90955	376	3	?	?	PUNCT
afs-90955	377	1	k	k	X
afs-90955	378	1	=	=	PUNCT
afs-90955	378	2	k	k	PROPN
afs-90955	379	1	+	+	PUNCT
afs-90955	379	2	1	1	NUM
afs-90955	379	3	f	f	NOUN
afs-90955	379	4	=	=	SYM
afs-90955	379	5	f	f	PROPN
afs-90955	380	1	+	+	CCONJ
afs-90955	380	2	f	f	PROPN
afs-90955	380	3	sire	sire	NOUN
afs-90955	380	4	if	if	SCONJ
afs-90955	380	5	(	(	PUNCT
afs-90955	380	6	sire	sire	NOUN
afs-90955	380	7	in	in	ADP
afs-90955	380	8	a11	a11	PROPN
afs-90955	380	9	)	)	PUNCT
afs-90955	380	10	c	c	NOUN
afs-90955	381	1	=	=	SYM
afs-90955	381	2	c	c	PROPN
afs-90955	381	3	–	–	PUNCT
afs-90955	381	4	0.5*d	0.5*d	NUM
afs-90955	381	5	sire	sire	NOUN
afs-90955	381	6	end	end	VERB
afs-90955	381	7	if	if	SCONJ
afs-90955	381	8	if	if	SCONJ
afs-90955	381	9	(	(	PUNCT
afs-90955	381	10	dam	dam	NOUN
afs-90955	381	11	>	>	X
afs-90955	381	12	0	0	NUM
afs-90955	381	13	)	)	PUNCT
afs-90955	381	14	then	then	ADV
afs-90955	381	15	!	!	PUNCT
afs-90955	382	1	dam	dam	NOUN
afs-90955	382	2	known	know	VERB
afs-90955	382	3	?	?	PUNCT
afs-90955	383	1	k	k	X
afs-90955	384	1	=	=	PUNCT
afs-90955	384	2	k	k	PROPN
afs-90955	385	1	+	+	PUNCT
afs-90955	385	2	1	1	NUM
afs-90955	385	3	f	f	NOUN
afs-90955	385	4	=	=	SYM
afs-90955	385	5	f	f	PROPN
afs-90955	385	6	+	+	CCONJ
afs-90955	385	7	f	f	PROPN
afs-90955	385	8	dam	dam	NOUN
afs-90955	385	9	if	if	SCONJ
afs-90955	385	10	(	(	PUNCT
afs-90955	385	11	dam	dam	NOUN
afs-90955	385	12	in	in	ADP
afs-90955	385	13	a11	a11	PROPN
afs-90955	385	14	)	)	PUNCT
afs-90955	385	15	c	c	X
afs-90955	386	1	=	=	SYM
afs-90955	386	2	c	c	PROPN
afs-90955	386	3	–	–	PUNCT
afs-90955	386	4	0.5*d	0.5*d	NUM
afs-90955	386	5	dam	dam	NOUN
afs-90955	386	6	end	end	VERB
afs-90955	386	7	if	if	SCONJ
afs-90955	386	8	if	if	SCONJ
afs-90955	386	9	(	(	PUNCT
afs-90955	386	10	i	i	NOUN
afs-90955	386	11	d	d	PROPN
afs-90955	386	12	in	in	ADP
afs-90955	386	13	a11	a11	PROPN
afs-90955	386	14	)	)	PUNCT
afs-90955	386	15	c	c	X
afs-90955	387	1	=	=	PUNCT
afs-90955	387	2	c	c	PROPN
afs-90955	388	1	+	+	CCONJ
afs-90955	388	2	d	d	X
afs-90955	388	3	i	i	PROPN
afs-90955	388	4	d	d	PROPN
afs-90955	388	5	!	!	PUNCT
afs-90955	389	1	step	step	NOUN
afs-90955	389	2	2	2	NUM
afs-90955	389	3	):	):	PUNCT
afs-90955	389	4	update	update	NOUN
afs-90955	389	5	vector	vector	NOUN
afs-90955	389	6	s	s	X
afs-90955	390	1	if	if	SCONJ
afs-90955	390	2	(	(	PUNCT
afs-90955	390	3	c	c	NOUN
afs-90955	390	4	is	be	AUX
afs-90955	390	5	nonzero	nonzero	ADJ
afs-90955	390	6	)	)	PUNCT
afs-90955	390	7	then	then	ADV
afs-90955	390	8	d	d	X
afs-90955	390	9	=	=	SYM
afs-90955	390	10	4/(4	4/(4	NUM
afs-90955	390	11	-	-	PUNCT
afs-90955	390	12	k	k	NOUN
afs-90955	390	13	-	-	PUNCT
afs-90955	390	14	f	f	NOUN
afs-90955	390	15	)	)	PUNCT
afs-90955	390	16	if	if	SCONJ
afs-90955	390	17	(	(	PUNCT
afs-90955	390	18	sire	sire	NOUN
afs-90955	390	19	in	in	ADP
afs-90955	390	20	a11	a11	PROPN
afs-90955	390	21	)	)	PUNCT
afs-90955	390	22	s	s	PART
afs-90955	390	23	sire	sire	NOUN
afs-90955	390	24	=	=	SYM
afs-90955	390	25	s	s	AUX
afs-90955	390	26	sire	sire	NOUN
afs-90955	390	27	–	–	PUNCT
afs-90955	390	28	0.5*d*c	0.5*d*c	NUM
afs-90955	390	29	if	if	SCONJ
afs-90955	390	30	(	(	PUNCT
afs-90955	390	31	dam	dam	NOUN
afs-90955	390	32	in	in	ADP
afs-90955	390	33	a11	a11	PROPN
afs-90955	390	34	)	)	PUNCT
afs-90955	390	35	s	s	PART
afs-90955	390	36	dam	dam	NOUN
afs-90955	390	37	=	=	SYM
afs-90955	390	38	s	s	PART
afs-90955	390	39	dam	dam	NOUN
afs-90955	390	40	–	–	PUNCT
afs-90955	390	41	0.5*d*c	0.5*d*c	NUM
afs-90955	390	42	if	if	SCONJ
afs-90955	390	43	(	(	PUNCT
afs-90955	390	44	i	i	PROPN
afs-90955	390	45	d	d	PROPN
afs-90955	390	46	in	in	ADP
afs-90955	390	47	a11	a11	PROPN
afs-90955	390	48	)	)	PUNCT
afs-90955	390	49	s	s	PART
afs-90955	391	1	i	i	NOUN
afs-90955	391	2	d	d	PROPN
afs-90955	391	3	=	=	SYM
afs-90955	391	4	s	s	PROPN
afs-90955	391	5	i	i	PROPN
afs-90955	391	6	d	d	PROPN
afs-90955	391	7	+	+	CCONJ
afs-90955	391	8	d*c	d*c	PROPN
afs-90955	391	9	end	end	NOUN
afs-90955	391	10	if	if	SCONJ
afs-90955	391	11	end	end	NOUN
afs-90955	391	12	do	do	VERB
afs-90955	391	13	fig	fig	NOUN
afs-90955	391	14	.	.	PUNCT
afs-90955	392	1	1	1	X
afs-90955	392	2	.	.	X
afs-90955	392	3	pseudo	pseudo	NOUN
afs-90955	392	4	code	code	NOUN
afs-90955	392	5	example	example	NOUN
afs-90955	392	6	of	of	ADP
afs-90955	392	7	calculation	calculation	NOUN
afs-90955	392	8	of	of	ADP
afs-90955	392	9	product	product	NOUN
afs-90955	392	10	s	s	PART
afs-90955	392	11	=	=	NOUN
afs-90955	392	12	a11d1	a11d1	NOUN