id	sid	tid	token	lemma	pos
cusj-5696	1	1	microsoft	microsoft	PROPN
cusj-5696	1	2	word	word	NOUN
cusj-5696	1	3	42-160-1-ed.docx	42-160-1-ed.docx	NOUN
cusj-5696	1	4	1	1	NUM
cusj-5696	1	5	genome	genome	NOUN
cusj-5696	1	6	analysis	analysis	NOUN
cusj-5696	1	7	cfhmm	cfhmm	NOUN
cusj-5696	1	8	:	:	PUNCT
cusj-5696	1	9	heterogeneous	heterogeneous	ADJ
cusj-5696	1	10	tumor	tumor	NOUN
cusj-5696	1	11	cnv	cnv	NOUN
cusj-5696	1	12	classification	classification	NOUN
cusj-5696	1	13	by	by	ADP
cusj-5696	1	14	hidden	hide	VERB
cusj-5696	1	15	markov	markov	NOUN
cusj-5696	1	16	aleksandar	aleksandar	PROPN
cusj-5696	1	17	obradovic1	obradovic1	PROPN
cusj-5696	1	18	,	,	PUNCT
cusj-5696	1	19	*	*	PUNCT
cusj-5696	1	20	,	,	PUNCT
cusj-5696	1	21	hongjian	hongjian	NOUN
cusj-5696	1	22	qi2	qi2	ADV
cusj-5696	1	23	1department	1department	NUM
cusj-5696	1	24	of	of	ADP
cusj-5696	1	25	computer	computer	NOUN
cusj-5696	1	26	science	science	NOUN
cusj-5696	1	27	,	,	PUNCT
cusj-5696	1	28	columbia	columbia	PROPN
cusj-5696	1	29	university	university	PROPN
cusj-5696	1	30	azo2104@columbia.edu	azo2104@columbia.edu	PROPN
cusj-5696	2	1	2department	2department	NUM
cusj-5696	2	2	of	of	ADP
cusj-5696	2	3	computer	computer	NOUN
cusj-5696	2	4	science	science	NOUN
cusj-5696	2	5	,	,	PUNCT
cusj-5696	2	6	columbia	columbia	PROPN
cusj-5696	2	7	university	university	PROPN
cusj-5696	2	8	hq2130@columbia.edu	hq2130@columbia.edu	PROPN
cusj-5696	2	9	abstract	abstract	ADJ
cusj-5696	2	10	summary	summary	NOUN
cusj-5696	2	11	:	:	PUNCT
cusj-5696	2	12	we	we	PRON
cusj-5696	2	13	here	here	ADV
cusj-5696	2	14	develop	develop	VERB
cusj-5696	2	15	and	and	CCONJ
cusj-5696	2	16	implement	implement	VERB
cusj-5696	2	17	a	a	DET
cusj-5696	2	18	clonal	clonal	ADJ
cusj-5696	2	19	fraction	fraction	NOUN
cusj-5696	2	20	hidden	hide	VERB
cusj-5696	2	21	markov	markov	NOUN
cusj-5696	2	22	model	model	NOUN
cusj-5696	2	23	(	(	PUNCT
cusj-5696	2	24	cfhmm	cfhmm	NOUN
cusj-5696	2	25	)	)	PUNCT
cusj-5696	2	26	,	,	PUNCT
cusj-5696	2	27	to	to	PART
cusj-5696	2	28	leverage	leverage	VERB
cusj-5696	2	29	positional	positional	ADJ
cusj-5696	2	30	information	information	NOUN
cusj-5696	2	31	in	in	ADP
cusj-5696	2	32	classifying	classify	VERB
cusj-5696	2	33	tumor	tumor	NOUN
cusj-5696	2	34	cnvs	cnvs	NOUN
cusj-5696	2	35	and	and	CCONJ
cusj-5696	2	36	their	their	PRON
cusj-5696	2	37	corresponding	corresponding	ADJ
cusj-5696	2	38	clonal	clonal	ADJ
cusj-5696	2	39	fraction	fraction	NOUN
cusj-5696	2	40	from	from	ADP
cusj-5696	2	41	log	log	NOUN
cusj-5696	2	42	-	-	PUNCT
cusj-5696	2	43	ratio	ratio	NOUN
cusj-5696	2	44	-	-	PUNCT
cusj-5696	2	45	normalized	normalize	VERB
cusj-5696	2	46	tumor	tumor	NOUN
cusj-5696	2	47	/	/	SYM
cusj-5696	2	48	normal	normal	ADJ
cusj-5696	2	49	sequencing	sequence	VERB
cusj-5696	2	50	data	datum	NOUN
cusj-5696	2	51	.	.	PUNCT
cusj-5696	3	1	in	in	ADP
cusj-5696	3	2	simulated	simulated	ADJ
cusj-5696	3	3	data	datum	NOUN
cusj-5696	3	4	,	,	PUNCT
cusj-5696	3	5	this	this	DET
cusj-5696	3	6	approach	approach	NOUN
cusj-5696	3	7	shows	show	VERB
cusj-5696	3	8	accurate	accurate	ADJ
cusj-5696	3	9	calling	calling	NOUN
cusj-5696	3	10	of	of	ADP
cusj-5696	3	11	cnvs	cnvs	NOUN
cusj-5696	3	12	for	for	ADP
cusj-5696	3	13	high	high	ADJ
cusj-5696	3	14	-	-	PUNCT
cusj-5696	3	15	fraction	fraction	NOUN
cusj-5696	3	16	mutations	mutation	NOUN
cusj-5696	3	17	,	,	PUNCT
cusj-5696	3	18	and	and	CCONJ
cusj-5696	3	19	improvement	improvement	NOUN
cusj-5696	3	20	in	in	ADP
cusj-5696	3	21	calling	call	VERB
cusj-5696	3	22	over	over	ADP
cusj-5696	3	23	a	a	DET
cusj-5696	3	24	naïve	naïve	ADJ
cusj-5696	3	25	clustering	clustering	NOUN
cusj-5696	3	26	benchmark	benchmark	NOUN
cusj-5696	3	27	across	across	ADP
cusj-5696	3	28	the	the	DET
cusj-5696	3	29	board	board	NOUN
cusj-5696	3	30	,	,	PUNCT
cusj-5696	3	31	as	as	ADV
cusj-5696	3	32	well	well	ADV
cusj-5696	3	33	as	as	ADP
cusj-5696	3	34	useful	useful	ADJ
cusj-5696	3	35	purity	purity	NOUN
cusj-5696	3	36	estimation	estimation	NOUN
cusj-5696	3	37	for	for	ADP
cusj-5696	3	38	dominant	dominant	ADJ
cusj-5696	3	39	clones	clone	NOUN
cusj-5696	3	40	.	.	PUNCT
cusj-5696	4	1	availability	availability	NOUN
cusj-5696	4	2	and	and	CCONJ
cusj-5696	4	3	implementation	implementation	NOUN
cusj-5696	4	4	:	:	PUNCT
cusj-5696	4	5	source	source	NOUN
cusj-5696	4	6	code	code	NOUN
cusj-5696	4	7	and	and	CCONJ
cusj-5696	4	8	documentation	documentation	NOUN
cusj-5696	4	9	is	be	AUX
cusj-5696	4	10	freely	freely	ADV
cusj-5696	4	11	available	available	ADJ
cusj-5696	4	12	at	at	ADP
cusj-5696	4	13	https://github.com/7lagrange/fcnv	https://github.com/7lagrange/fcnv	NOUN
cusj-5696	4	14	implemented	implement	VERB
cusj-5696	4	15	in	in	ADP
cusj-5696	4	16	r	r	NOUN
cusj-5696	4	17	,	,	PUNCT
cusj-5696	4	18	with	with	SCONJ
cusj-5696	4	19	all	all	DET
cusj-5696	4	20	major	major	ADJ
cusj-5696	4	21	operating	operate	VERB
cusj-5696	4	22	systems	system	NOUN
cusj-5696	4	23	supported	support	VERB
cusj-5696	4	24	.	.	PUNCT
cusj-5696	5	1	contact	contact	NOUN
cusj-5696	5	2	:	:	PUNCT
cusj-5696	5	3	azo2104@columbia.edu	azo2104@columbia.edu	PROPN
cusj-5696	6	1	supplementary	supplementary	ADJ
cusj-5696	6	2	information	information	NOUN
cusj-5696	6	3	:	:	PUNCT
cusj-5696	6	4	additional	additional	ADJ
cusj-5696	6	5	tables	table	NOUN
cusj-5696	6	6	and	and	CCONJ
cusj-5696	6	7	figures	figure	NOUN
cusj-5696	6	8	available	available	ADJ
cusj-5696	6	9	at	at	ADP
cusj-5696	6	10	https://docs.google.com/document/d/1ohbjwaz20jxx3tc64basuzp	https://docs.google.com/document/d/1ohbjwaz20jxx3tc64basuzp	PROPN
cusj-5696	6	11	wmpne_ybfwfmju9jb0mu	wmpne_ybfwfmju9jb0mu	ADP
cusj-5696	6	12	/	/	SYM
cusj-5696	6	13	edit?usp	edit?usp	NOUN
cusj-5696	6	14	=	=	NOUN
cusj-5696	6	15	sharing	share	VERB
cusj-5696	6	16	1	1	NUM
cusj-5696	6	17	introduction	introduction	NOUN
cusj-5696	6	18	copy	copy	NOUN
cusj-5696	6	19	number	number	NOUN
cusj-5696	6	20	variations	variation	NOUN
cusj-5696	6	21	(	(	PUNCT
cusj-5696	6	22	cnvs	cnvs	NOUN
cusj-5696	6	23	)	)	PUNCT
cusj-5696	6	24	are	be	AUX
cusj-5696	6	25	duplications	duplication	NOUN
cusj-5696	6	26	or	or	CCONJ
cusj-5696	6	27	deletions	deletion	NOUN
cusj-5696	6	28	of	of	ADP
cusj-5696	6	29	genome	genome	NOUN
cusj-5696	6	30	segments	segment	NOUN
cusj-5696	6	31	,	,	PUNCT
cusj-5696	6	32	of	of	ADP
cusj-5696	6	33	length	length	NOUN
cusj-5696	6	34	greater	great	ADJ
cusj-5696	6	35	than	than	ADP
cusj-5696	6	36	one	one	NUM
cusj-5696	6	37	kilobase	kilobase	NOUN
cusj-5696	6	38	by	by	ADP
cusj-5696	6	39	convention	convention	PROPN
cusj-5696	6	40	,	,	PUNCT
cusj-5696	6	41	which	which	PRON
cusj-5696	6	42	occur	occur	VERB
cusj-5696	6	43	normally	normally	ADV
cusj-5696	6	44	in	in	ADP
cusj-5696	6	45	the	the	DET
cusj-5696	6	46	genome	genome	NOUN
cusj-5696	6	47	but	but	CCONJ
cusj-5696	6	48	have	have	AUX
cusj-5696	6	49	also	also	ADV
cusj-5696	6	50	been	be	AUX
cusj-5696	6	51	highly	highly	ADV
cusj-5696	6	52	implicated	implicate	VERB
cusj-5696	6	53	in	in	ADP
cusj-5696	6	54	tumor	tumor	NOUN
cusj-5696	6	55	genomes	genome	NOUN
cusj-5696	6	56	(	(	PUNCT
cusj-5696	6	57	zhang	zhang	PROPN
cusj-5696	6	58	)	)	PUNCT
cusj-5696	6	59	.	.	PUNCT
cusj-5696	7	1	it	it	PRON
cusj-5696	7	2	is	be	AUX
cusj-5696	7	3	therefore	therefore	ADV
cusj-5696	7	4	important	important	ADJ
cusj-5696	7	5	to	to	PART
cusj-5696	7	6	accurately	accurately	ADV
cusj-5696	7	7	classify	classify	VERB
cusj-5696	7	8	cnvs	cnvs	NOUN
cusj-5696	7	9	in	in	ADP
cusj-5696	7	10	tumor	tumor	NOUN
cusj-5696	7	11	genome	genome	NOUN
cusj-5696	7	12	data	datum	NOUN
cusj-5696	7	13	.	.	PUNCT
cusj-5696	8	1	this	this	PRON
cusj-5696	8	2	can	can	AUX
cusj-5696	8	3	be	be	AUX
cusj-5696	8	4	done	do	VERB
cusj-5696	8	5	by	by	ADP
cusj-5696	8	6	modeling	model	VERB
cusj-5696	8	7	next	next	ADJ
cusj-5696	8	8	-	-	PUNCT
cusj-5696	8	9	generation	generation	NOUN
cusj-5696	8	10	sequencing	sequence	VERB
cusj-5696	8	11	data	datum	NOUN
cusj-5696	8	12	,	,	PUNCT
cusj-5696	8	13	where	where	SCONJ
cusj-5696	8	14	a	a	DET
cusj-5696	8	15	natural	natural	ADJ
cusj-5696	8	16	model	model	NOUN
cusj-5696	8	17	to	to	PART
cusj-5696	8	18	apply	apply	VERB
cusj-5696	8	19	is	be	AUX
cusj-5696	8	20	the	the	DET
cusj-5696	8	21	hidden	hide	VERB
cusj-5696	8	22	markov	markov	NOUN
cusj-5696	8	23	model	model	NOUN
cusj-5696	8	24	,	,	PUNCT
cusj-5696	8	25	with	with	ADP
cusj-5696	8	26	transition	transition	NOUN
cusj-5696	8	27	matrix	matrix	NOUN
cusj-5696	8	28	of	of	ADP
cusj-5696	8	29	copy	copy	NOUN
cusj-5696	8	30	number	number	NOUN
cusj-5696	8	31	or	or	CCONJ
cusj-5696	8	32	cnv	cnv	PROPN
cusj-5696	8	33	states	state	NOUN
cusj-5696	8	34	and	and	CCONJ
cusj-5696	8	35	emission	emission	NOUN
cusj-5696	8	36	of	of	ADP
cusj-5696	8	37	normalized	normalize	VERB
cusj-5696	8	38	read	read	NOUN
cusj-5696	8	39	-	-	PUNCT
cusj-5696	8	40	counts	count	NOUN
cusj-5696	8	41	(	(	PUNCT
cusj-5696	8	42	zhao	zhao	NOUN
cusj-5696	8	43	)	)	PUNCT
cusj-5696	8	44	.	.	PUNCT
cusj-5696	9	1	however	however	ADV
cusj-5696	9	2	,	,	PUNCT
cusj-5696	9	3	admixture	admixture	NOUN
cusj-5696	9	4	of	of	ADP
cusj-5696	9	5	normal	normal	ADJ
cusj-5696	9	6	cells	cell	NOUN
cusj-5696	9	7	in	in	ADP
cusj-5696	9	8	a	a	DET
cusj-5696	9	9	tumor	tumor	NOUN
cusj-5696	9	10	sample	sample	NOUN
cusj-5696	9	11	(	(	PUNCT
cusj-5696	9	12	gusnanto	gusnanto	NOUN
cusj-5696	9	13	)	)	PUNCT
cusj-5696	9	14	and	and	CCONJ
cusj-5696	9	15	heterogeneity	heterogeneity	NOUN
cusj-5696	9	16	of	of	ADP
cusj-5696	9	17	distinct	distinct	ADJ
cusj-5696	9	18	clones	clone	NOUN
cusj-5696	9	19	within	within	ADP
cusj-5696	9	20	a	a	DET
cusj-5696	9	21	tumor	tumor	NOUN
cusj-5696	9	22	(	(	PUNCT
cusj-5696	9	23	oesper	oesper	ADJ
cusj-5696	9	24	)	)	PUNCT
cusj-5696	9	25	complicate	complicate	VERB
cusj-5696	9	26	analysis	analysis	NOUN
cusj-5696	9	27	,	,	PUNCT
cusj-5696	9	28	such	such	ADJ
cusj-5696	9	29	that	that	DET
cusj-5696	9	30	apparent	apparent	ADJ
cusj-5696	9	31	copynumber	copynumber	NOUN
cusj-5696	9	32	for	for	ADP
cusj-5696	9	33	any	any	DET
cusj-5696	9	34	given	give	VERB
cusj-5696	9	35	genome	genome	NOUN
cusj-5696	9	36	region	region	NOUN
cusj-5696	9	37	may	may	AUX
cusj-5696	9	38	appear	appear	VERB
cusj-5696	9	39	fractional	fractional	ADJ
cusj-5696	9	40	and	and	CCONJ
cusj-5696	9	41	be	be	AUX
cusj-5696	9	42	misclassified	misclassifie	VERB
cusj-5696	9	43	.	.	PUNCT
cusj-5696	10	1	this	this	PRON
cusj-5696	10	2	,	,	PUNCT
cusj-5696	10	3	in	in	ADP
cusj-5696	10	4	addition	addition	NOUN
cusj-5696	10	5	to	to	ADP
cusj-5696	10	6	the	the	DET
cusj-5696	10	7	loss	loss	NOUN
cusj-5696	10	8	of	of	ADP
cusj-5696	10	9	prior	prior	ADJ
cusj-5696	10	10	location	location	NOUN
cusj-5696	10	11	-	-	PUNCT
cusj-5696	10	12	specific	specific	ADJ
cusj-5696	10	13	variability	variability	NOUN
cusj-5696	10	14	information	information	NOUN
cusj-5696	10	15	that	that	PRON
cusj-5696	10	16	can	can	AUX
cusj-5696	10	17	occur	occur	VERB
cusj-5696	10	18	after	after	ADP
cusj-5696	10	19	tumor	tumor	NOUN
cusj-5696	10	20	/	/	SYM
cusj-5696	10	21	normal	normal	ADJ
cusj-5696	10	22	normalization	normalization	NOUN
cusj-5696	10	23	,	,	PUNCT
cusj-5696	10	24	is	be	AUX
cusj-5696	10	25	an	an	DET
cusj-5696	10	26	issue	issue	NOUN
cusj-5696	10	27	that	that	PRON
cusj-5696	10	28	must	must	AUX
cusj-5696	10	29	be	be	AUX
cusj-5696	10	30	addressed	address	VERB
cusj-5696	10	31	for	for	ADP
cusj-5696	10	32	improved	improved	ADJ
cusj-5696	10	33	application	application	NOUN
cusj-5696	10	34	of	of	ADP
cusj-5696	10	35	a	a	DET
cusj-5696	10	36	hidden	hide	VERB
cusj-5696	10	37	markov	markov	NOUN
cusj-5696	10	38	approach	approach	NOUN
cusj-5696	10	39	to	to	ADP
cusj-5696	10	40	cnv	cnv	PROPN
cusj-5696	10	41	classification	classification	NOUN
cusj-5696	10	42	.	.	PUNCT
cusj-5696	11	1	in	in	ADP
cusj-5696	11	2	our	our	PRON
cusj-5696	11	3	cfhmm	cfhmm	NOUN
cusj-5696	11	4	model	model	NOUN
cusj-5696	11	5	,	,	PUNCT
cusj-5696	11	6	we	we	PRON
cusj-5696	11	7	implement	implement	VERB
cusj-5696	11	8	a	a	DET
cusj-5696	11	9	15	15	NUM
cusj-5696	11	10	-	-	PUNCT
cusj-5696	11	11	state	state	NOUN
cusj-5696	11	12	model	model	NOUN
cusj-5696	11	13	,	,	PUNCT
cusj-5696	11	14	with	with	ADP
cusj-5696	11	15	a	a	DET
cusj-5696	11	16	commonly	commonly	ADV
cusj-5696	11	17	used	use	VERB
cusj-5696	11	18	5	5	NUM
cusj-5696	11	19	-	-	PUNCT
cusj-5696	11	20	copy	copy	NOUN
cusj-5696	11	21	-	-	PUNCT
cusj-5696	11	22	number	number	NOUN
cusj-5696	11	23	(	(	PUNCT
cusj-5696	11	24	0,1,2,3,4	0,1,2,3,4	NUM
cusj-5696	11	25	)	)	PUNCT
cusj-5696	11	26	set	set	VERB
cusj-5696	11	27	for	for	ADP
cusj-5696	11	28	tumor	tumor	NOUN
cusj-5696	11	29	and	and	CCONJ
cusj-5696	11	30	extremes	extreme	NOUN
cusj-5696	11	31	-	-	PUNCT
cusj-5696	11	32	removed	remove	VERB
cusj-5696	11	33	3	3	NUM
cusj-5696	11	34	-	-	PUNCT
cusj-5696	11	35	copy	copy	NOUN
cusj-5696	11	36	-	-	PUNCT
cusj-5696	11	37	number	number	NOUN
cusj-5696	11	38	(	(	PUNCT
cusj-5696	11	39	1,2,3	1,2,3	NOUN
cusj-5696	11	40	)	)	PUNCT
cusj-5696	11	41	set	set	VERB
cusj-5696	11	42	for	for	ADP
cusj-5696	11	43	normal	normal	ADJ
cusj-5696	11	44	cells	cell	NOUN
cusj-5696	11	45	,	,	PUNCT
cusj-5696	11	46	where	where	SCONJ
cusj-5696	11	47	a	a	DET
cusj-5696	11	48	normal	normal	ADJ
cusj-5696	11	49	diploid	diploid	ADJ
cusj-5696	11	50	state	state	NOUN
cusj-5696	11	51	of	of	ADP
cusj-5696	11	52	2	2	NUM
cusj-5696	11	53	is	be	AUX
cusj-5696	11	54	the	the	DET
cusj-5696	11	55	most	most	ADV
cusj-5696	11	56	common	common	ADJ
cusj-5696	11	57	.	.	PUNCT
cusj-5696	12	1	we	we	PRON
cusj-5696	12	2	derive	derive	VERB
cusj-5696	12	3	an	an	DET
cusj-5696	12	4	average	average	ADJ
cusj-5696	12	5	purity	purity	NOUN
cusj-5696	12	6	prior	prior	ADV
cusj-5696	12	7	from	from	ADP
cusj-5696	12	8	raw	raw	ADJ
cusj-5696	12	9	log	log	NOUN
cusj-5696	12	10	-	-	PUNCT
cusj-5696	12	11	ratios	ratio	NOUN
cusj-5696	12	12	,	,	PUNCT
cusj-5696	12	13	from	from	ADP
cusj-5696	12	14	which	which	PRON
cusj-5696	12	15	a	a	DET
cusj-5696	12	16	set	set	NOUN
cusj-5696	12	17	of	of	ADP
cusj-5696	12	18	15	15	NUM
cusj-5696	12	19	strong	strong	ADJ
cusj-5696	12	20	emission	emission	NOUN
cusj-5696	12	21	distribution	distribution	NOUN
cusj-5696	12	22	priors	prior	NOUN
cusj-5696	12	23	are	be	AUX
cusj-5696	12	24	constructed	construct	VERB
cusj-5696	12	25	that	that	PRON
cusj-5696	12	26	preserve	preserve	VERB
cusj-5696	12	27	variability	variability	NOUN
cusj-5696	12	28	information	information	NOUN
cusj-5696	12	29	for	for	ADP
cusj-5696	12	30	a	a	DET
cusj-5696	12	31	given	give	VERB
cusj-5696	12	32	tumor	tumor	NOUN
cusj-5696	12	33	/	/	SYM
cusj-5696	12	34	normal	normal	ADJ
cusj-5696	12	35	state	state	NOUN
cusj-5696	12	36	-	-	PUNCT
cusj-5696	12	37	pair	pair	NOUN
cusj-5696	12	38	.	.	PUNCT
cusj-5696	13	1	*	*	PUNCT
cusj-5696	13	2	to	to	PART
cusj-5696	13	3	whom	whom	PRON
cusj-5696	13	4	correspondence	correspondence	NOUN
cusj-5696	13	5	should	should	AUX
cusj-5696	13	6	be	be	AUX
cusj-5696	13	7	addressed	address	VERB
cusj-5696	13	8	.	.	PUNCT
cusj-5696	14	1	cfhmm	cfhmm	NOUN
cusj-5696	14	2	runs	run	VERB
cusj-5696	14	3	modified	modify	VERB
cusj-5696	14	4	unsupervised	unsupervised	ADJ
cusj-5696	14	5	viterbi	viterbi	NOUN
cusj-5696	14	6	training	training	NOUN
cusj-5696	14	7	on	on	ADP
cusj-5696	14	8	the	the	DET
cusj-5696	14	9	data	datum	NOUN
cusj-5696	14	10	to	to	PART
cusj-5696	14	11	give	give	VERB
cusj-5696	14	12	posterior	posterior	ADJ
cusj-5696	14	13	state	state	NOUN
cusj-5696	14	14	classifications	classification	NOUN
cusj-5696	14	15	that	that	SCONJ
cusj-5696	14	16	,	,	PUNCT
cusj-5696	14	17	if	if	SCONJ
cusj-5696	14	18	accurate	accurate	ADJ
cusj-5696	14	19	,	,	PUNCT
cusj-5696	14	20	may	may	AUX
cusj-5696	14	21	also	also	ADV
cusj-5696	14	22	provide	provide	VERB
cusj-5696	14	23	clonal	clonal	ADJ
cusj-5696	14	24	fraction	fraction	NOUN
cusj-5696	14	25	information	information	NOUN
cusj-5696	14	26	for	for	ADP
cusj-5696	14	27	each	each	DET
cusj-5696	14	28	cnv	cnv	PROPN
cusj-5696	14	29	mutation	mutation	NOUN
cusj-5696	14	30	.	.	PUNCT
cusj-5696	15	1	2	2	NUM
cusj-5696	15	2	methods	method	NOUN
cusj-5696	15	3	we	we	PRON
cusj-5696	15	4	evaluate	evaluate	VERB
cusj-5696	15	5	the	the	DET
cusj-5696	15	6	accuracy	accuracy	NOUN
cusj-5696	15	7	of	of	ADP
cusj-5696	15	8	our	our	PRON
cusj-5696	15	9	model	model	NOUN
cusj-5696	15	10	on	on	ADP
cusj-5696	15	11	simulated	simulate	VERB
cusj-5696	15	12	wholegenome	wholegenome	NOUN
cusj-5696	15	13	-	-	PUNCT
cusj-5696	15	14	sequencing	sequence	VERB
cusj-5696	15	15	data	datum	NOUN
cusj-5696	15	16	for	for	ADP
cusj-5696	15	17	which	which	PRON
cusj-5696	15	18	the	the	DET
cusj-5696	15	19	hidden	hidden	ADJ
cusj-5696	15	20	tumor	tumor	NOUN
cusj-5696	15	21	and	and	CCONJ
cusj-5696	15	22	normal	normal	ADJ
cusj-5696	15	23	copy	copy	NOUN
cusj-5696	15	24	-	-	PUNCT
cusj-5696	15	25	number	number	NOUN
cusj-5696	15	26	states	state	NOUN
cusj-5696	15	27	are	be	AUX
cusj-5696	15	28	known	know	VERB
cusj-5696	15	29	.	.	PUNCT
cusj-5696	16	1	the	the	DET
cusj-5696	16	2	tumor	tumor	NOUN
cusj-5696	16	3	and	and	CCONJ
cusj-5696	16	4	normal	normal	ADJ
cusj-5696	16	5	genomes	genome	NOUN
cusj-5696	16	6	are	be	AUX
cusj-5696	16	7	segmented	segment	VERB
cusj-5696	16	8	into	into	ADP
cusj-5696	16	9	kilobase	kilobase	NOUN
cusj-5696	16	10	-	-	PUNCT
cusj-5696	16	11	length	length	NOUN
cusj-5696	16	12	bins	bin	NOUN
cusj-5696	16	13	for	for	ADP
cusj-5696	16	14	which	which	PRON
cusj-5696	16	15	copy	copy	NOUN
cusj-5696	16	16	number	number	NOUN
cusj-5696	16	17	is	be	AUX
cusj-5696	16	18	generated	generate	VERB
cusj-5696	16	19	by	by	ADP
cusj-5696	16	20	markov	markov	NOUN
cusj-5696	16	21	chain	chain	NOUN
cusj-5696	16	22	with	with	ADP
cusj-5696	16	23	adjustable	adjustable	ADJ
cusj-5696	16	24	parameters	parameter	NOUN
cusj-5696	16	25	favoring	favor	VERB
cusj-5696	16	26	remaining	remain	VERB
cusj-5696	16	27	at	at	ADP
cusj-5696	16	28	the	the	DET
cusj-5696	16	29	same	same	ADJ
cusj-5696	16	30	copy	copy	NOUN
cusj-5696	16	31	number	number	NOUN
cusj-5696	16	32	from	from	ADP
cusj-5696	16	33	one	one	NUM
cusj-5696	16	34	bin	bin	NOUN
cusj-5696	16	35	to	to	ADP
cusj-5696	16	36	the	the	DET
cusj-5696	16	37	next	next	ADJ
cusj-5696	16	38	and	and	CCONJ
cusj-5696	16	39	providing	provide	VERB
cusj-5696	16	40	equiprobable	equiprobable	ADJ
cusj-5696	16	41	transition	transition	NOUN
cusj-5696	16	42	to	to	ADP
cusj-5696	16	43	any	any	DET
cusj-5696	16	44	other	other	ADJ
cusj-5696	16	45	copy	copy	NOUN
cusj-5696	16	46	number	number	NOUN
cusj-5696	16	47	.	.	PUNCT
cusj-5696	17	1	60	60	NUM
cusj-5696	17	2	million	million	NUM
cusj-5696	17	3	reads	read	NOUN
cusj-5696	17	4	,	,	PUNCT
cusj-5696	17	5	corresponding	correspond	VERB
cusj-5696	17	6	to	to	ADP
cusj-5696	17	7	10x	10x	NOUN
cusj-5696	17	8	deep	deep	ADJ
cusj-5696	17	9	sequencing	sequencing	NOUN
cusj-5696	17	10	in	in	ADP
cusj-5696	17	11	(	(	PUNCT
cusj-5696	17	12	myers	myer	NOUN
cusj-5696	17	13	)	)	PUNCT
cusj-5696	17	14	are	be	AUX
cusj-5696	17	15	randomly	randomly	ADV
cusj-5696	17	16	distributed	distribute	VERB
cusj-5696	17	17	into	into	ADP
cusj-5696	17	18	these	these	DET
cusj-5696	17	19	bins	bin	NOUN
cusj-5696	17	20	with	with	ADP
cusj-5696	17	21	probability	probability	NOUN
cusj-5696	17	22	weighted	weight	VERB
cusj-5696	17	23	by	by	ADP
cusj-5696	17	24	copy	copy	NOUN
cusj-5696	17	25	number	number	NOUN
cusj-5696	17	26	.	.	PUNCT
cusj-5696	18	1	clonal	clonal	ADJ
cusj-5696	18	2	fraction	fraction	PROPN
cusj-5696	18	3	k	k	PROPN
cusj-5696	18	4	in	in	ADP
cusj-5696	18	5	the	the	DET
cusj-5696	18	6	tissue	tissue	NOUN
cusj-5696	18	7	for	for	ADP
cusj-5696	18	8	a	a	DET
cusj-5696	18	9	given	give	VERB
cusj-5696	18	10	bin	bin	NOUN
cusj-5696	18	11	is	be	AUX
cusj-5696	18	12	randomly	randomly	ADV
cusj-5696	18	13	selected	select	VERB
cusj-5696	18	14	from	from	ADP
cusj-5696	18	15	a	a	DET
cusj-5696	18	16	parameter	parameter	NOUN
cusj-5696	18	17	list	list	NOUN
cusj-5696	18	18	of	of	ADP
cusj-5696	18	19	options	option	NOUN
cusj-5696	18	20	,	,	PUNCT
cusj-5696	18	21	where	where	SCONJ
cusj-5696	18	22	we	we	PRON
cusj-5696	18	23	ran	run	VERB
cusj-5696	18	24	several	several	ADJ
cusj-5696	18	25	tests	test	NOUN
cusj-5696	18	26	with	with	ADP
cusj-5696	18	27	two	two	NUM
cusj-5696	18	28	-	-	PUNCT
cusj-5696	18	29	tumor	tumor	NOUN
cusj-5696	18	30	-	-	PUNCT
cusj-5696	18	31	clone	clone	NOUN
cusj-5696	18	32	data	datum	NOUN
cusj-5696	18	33	and	and	CCONJ
cusj-5696	18	34	one	one	NUM
cusj-5696	18	35	with	with	ADP
cusj-5696	18	36	three	three	NUM
cusj-5696	18	37	-	-	PUNCT
cusj-5696	18	38	tumorclone	tumorclone	NOUN
cusj-5696	18	39	data	datum	NOUN
cusj-5696	18	40	.	.	PUNCT
cusj-5696	19	1	log	log	NOUN
cusj-5696	19	2	-	-	PUNCT
cusj-5696	19	3	normalization	normalization	NOUN
cusj-5696	19	4	proceeds	proceed	NOUN
cusj-5696	19	5	from	from	ADP
cusj-5696	19	6	read	read	NOUN
cusj-5696	19	7	-	-	PUNCT
cusj-5696	19	8	count	count	NOUN
cusj-5696	19	9	data	datum	NOUN
cusj-5696	19	10	as	as	ADP
cusj-5696	19	11	:	:	PUNCT
cusj-5696	19	12	(	(	PUNCT
cusj-5696	19	13	1	1	X
cusj-5696	19	14	)	)	PUNCT
cusj-5696	19	15	where	where	SCONJ
cusj-5696	19	16	,	,	PUNCT
cusj-5696	19	17	conversely	conversely	ADV
cusj-5696	19	18	:	:	PUNCT
cusj-5696	19	19	(	(	PUNCT
cusj-5696	19	20	2	2	X
cusj-5696	19	21	)	)	PUNCT
cusj-5696	19	22	the	the	DET
cusj-5696	19	23	purity	purity	NOUN
cusj-5696	19	24	prior	prior	ADV
cusj-5696	19	25	k	k	PROPN
cusj-5696	19	26	for	for	SCONJ
cusj-5696	19	27	input	input	NOUN
cusj-5696	19	28	into	into	ADP
cusj-5696	19	29	cfhmm	cfhmm	NOUN
cusj-5696	19	30	is	be	AUX
cusj-5696	19	31	taken	take	VERB
cusj-5696	19	32	as	as	ADP
cusj-5696	19	33	the	the	DET
cusj-5696	19	34	mean	mean	NOUN
cusj-5696	19	35	of	of	ADP
cusj-5696	19	36	values	value	NOUN
cusj-5696	19	37	from	from	ADP
cusj-5696	19	38	equation	equation	NOUN
cusj-5696	19	39	2	2	NUM
cusj-5696	19	40	,	,	PUNCT
cusj-5696	19	41	assuming	assume	VERB
cusj-5696	19	42	normal	normal	ADJ
cusj-5696	19	43	state	state	NOUN
cusj-5696	19	44	2	2	NUM
cusj-5696	19	45	and	and	CCONJ
cusj-5696	19	46	using	use	VERB
cusj-5696	19	47	only	only	ADJ
cusj-5696	19	48	extreme	extreme	ADJ
cusj-5696	19	49	log	log	NOUN
cusj-5696	19	50	-	-	PUNCT
cusj-5696	19	51	ratios	ratio	NOUN
cusj-5696	19	52	over	over	ADP
cusj-5696	19	53	the	the	DET
cusj-5696	19	54	equation	equation	NOUN
cusj-5696	19	55	1	1	NUM
cusj-5696	19	56	values	value	NOUN
cusj-5696	19	57	for	for	ADP
cusj-5696	19	58	pure	pure	ADJ
cusj-5696	19	59	(	(	PUNCT
cusj-5696	19	60	k=1	k=1	NOUN
cusj-5696	19	61	)	)	PUNCT
cusj-5696	19	62	tumor	tumor	NOUN
cusj-5696	19	63	state	state	NOUN
cusj-5696	19	64	3	3	NUM
cusj-5696	19	65	,	,	PUNCT
cusj-5696	19	66	or	or	CCONJ
cusj-5696	19	67	under	under	ADP
cusj-5696	19	68	the	the	DET
cusj-5696	19	69	threshold	threshold	NOUN
cusj-5696	19	70	for	for	ADP
cusj-5696	19	71	pure	pure	ADJ
cusj-5696	19	72	tumor	tumor	NOUN
cusj-5696	19	73	state	state	NOUN
cusj-5696	19	74	1	1	NUM
cusj-5696	19	75	.	.	PUNCT
cusj-5696	20	1	with	with	ADP
cusj-5696	20	2	this	this	DET
cusj-5696	20	3	prior	prior	NOUN
cusj-5696	20	4	,	,	PUNCT
cusj-5696	20	5	since	since	SCONJ
cusj-5696	20	6	the	the	DET
cusj-5696	20	7	read	read	NOUN
cusj-5696	20	8	-	-	PUNCT
cusj-5696	20	9	counts	count	NOUN
cusj-5696	20	10	are	be	AUX
cusj-5696	20	11	poisson	poisson	NOUN
cusj-5696	20	12	distributed	distribute	VERB
cusj-5696	20	13	,	,	PUNCT
cusj-5696	20	14	the	the	DET
cusj-5696	20	15	lognormalized	lognormalize	VERB
cusj-5696	20	16	emission	emission	NOUN
cusj-5696	20	17	data	datum	NOUN
cusj-5696	20	18	can	can	AUX
cusj-5696	20	19	be	be	AUX
cusj-5696	20	20	normally	normally	ADV
cusj-5696	20	21	approximated	approximate	VERB
cusj-5696	20	22	in	in	ADP
cusj-5696	20	23	a	a	DET
cusj-5696	20	24	way	way	NOUN
cusj-5696	20	25	that	that	PRON
cusj-5696	20	26	preserves	preserve	VERB
cusj-5696	20	27	variability	variability	NOUN
cusj-5696	20	28	information	information	NOUN
cusj-5696	20	29	dependent	dependent	ADJ
cusj-5696	20	30	on	on	ADP
cusj-5696	20	31	location	location	NOUN
cusj-5696	20	32	along	along	ADP
cusj-5696	20	33	the	the	DET
cusj-5696	20	34	genome	genome	NOUN
cusj-5696	20	35	as	as	ADP
cusj-5696	20	36	:	:	PUNCT
cusj-5696	20	37	(	(	PUNCT
cusj-5696	20	38	3	3	X
cusj-5696	20	39	)	)	PUNCT
cusj-5696	20	40	where	where	SCONJ
cusj-5696	20	41	p1	p1	NOUN
cusj-5696	20	42	and	and	CCONJ
cusj-5696	20	43	p2	p2	PROPN
cusj-5696	20	44	are	be	AUX
cusj-5696	20	45	tumor	tumor	NOUN
cusj-5696	20	46	and	and	CCONJ
cusj-5696	20	47	normal	normal	ADJ
cusj-5696	20	48	state	state	NOUN
cusj-5696	20	49	,	,	PUNCT
cusj-5696	20	50	respectively	respectively	ADV
cusj-5696	20	51	,	,	PUNCT
cusj-5696	20	52	and	and	CCONJ
cusj-5696	20	53	n	n	PRON
cusj-5696	20	54	is	be	AUX
cusj-5696	20	55	the	the	DET
cusj-5696	20	56	number	number	NOUN
cusj-5696	20	57	of	of	ADP
cusj-5696	20	58	reads	read	NOUN
cusj-5696	20	59	.	.	PUNCT
cusj-5696	21	1	from	from	ADP
cusj-5696	21	2	here	here	ADV
cusj-5696	21	3	,	,	PUNCT
cusj-5696	21	4	a	a	DET
cusj-5696	21	5	hidden	hide	VERB
cusj-5696	21	6	markov	markov	NOUN
cusj-5696	21	7	model	model	NOUN
cusj-5696	21	8	is	be	AUX
cusj-5696	21	9	created	create	VERB
cusj-5696	21	10	with	with	ADP
cusj-5696	21	11	a	a	DET
cusj-5696	21	12	15	15	NUM
cusj-5696	21	13	-	-	PUNCT
cusj-5696	21	14	state	state	NOUN
cusj-5696	21	15	transition	transition	NOUN
cusj-5696	21	16	matrix	matrix	NOUN
cusj-5696	21	17	and	and	CCONJ
cusj-5696	21	18	modified	modify	VERB
cusj-5696	21	19	for	for	ADP
cusj-5696	21	20	continuousemission	continuousemission	NOUN
cusj-5696	21	21	such	such	ADJ
cusj-5696	21	22	that	that	SCONJ
cusj-5696	21	23	the	the	DET
cusj-5696	21	24	emission	emission	NOUN
cusj-5696	21	25	matrix	matrix	NOUN
cusj-5696	21	26	contains	contain	VERB
cusj-5696	21	27	a	a	DET
cusj-5696	21	28	mean	mean	NOUN
cusj-5696	21	29	and	and	CCONJ
cusj-5696	21	30	variance	variance	NOUN
cusj-5696	21	31	for	for	ADP
cusj-5696	21	32	each	each	PRON
cusj-5696	21	33	of	of	ADP
cusj-5696	21	34	the	the	DET
cusj-5696	21	35	15	15	NUM
cusj-5696	21	36	-	-	PUNCT
cusj-5696	21	37	states	state	NOUN
cusj-5696	21	38	.	.	PUNCT
cusj-5696	22	1	the	the	DET
cusj-5696	22	2	viterbi	viterbi	ADJ
cusj-5696	22	3	algorithm	algorithm	NOUN
cusj-5696	22	4	is	be	AUX
cusj-5696	22	5	then	then	ADV
cusj-5696	22	6	:	:	PUNCT
cusj-5696	22	7	(	(	PUNCT
cusj-5696	22	8	4	4	X
cusj-5696	22	9	)	)	PUNCT
cusj-5696	22	10	with	with	ADP
cusj-5696	22	11	probability	probability	NOUN
cusj-5696	22	12	of	of	ADP
cusj-5696	22	13	state	state	NOUN
cusj-5696	22	14	m	m	VERB
cusj-5696	22	15	at	at	ADP
cusj-5696	22	16	position	position	NOUN
cusj-5696	22	17	n	n	ADP
cusj-5696	22	18	captured	capture	VERB
cusj-5696	22	19	in	in	ADP
cusj-5696	22	20	xm(n	xm(n	NUM
cusj-5696	22	21	)	)	PUNCT
cusj-5696	22	22	,	,	PUNCT
cusj-5696	22	23	state	state	NOUN
cusj-5696	22	24	transition	transition	NOUN
cusj-5696	22	25	probability	probability	NOUN
cusj-5696	22	26	captured	capture	VERB
cusj-5696	22	27	in	in	ADP
cusj-5696	22	28	t	t	PROPN
cusj-5696	22	29	,	,	PUNCT
cusj-5696	22	30	and	and	CCONJ
cusj-5696	22	31	log	log	NOUN
cusj-5696	22	32	-	-	PUNCT
cusj-5696	22	33	ratio	ratio	NOUN
cusj-5696	22	34	emission	emission	NOUN
cusj-5696	22	35	distributions	distribution	NOUN
cusj-5696	22	36	captured	capture	VERB
cusj-5696	22	37	with	with	ADP
cusj-5696	22	38	mean	mean	ADJ
cusj-5696	22	39	and	and	CCONJ
cusj-5696	22	40	standard	standard	ADJ
cusj-5696	22	41	deviation	deviation	NOUN
cusj-5696	22	42	in	in	ADP
cusj-5696	22	43	e.	e.	PROPN
cusj-5696	22	44	this	this	PRON
cusj-5696	22	45	is	be	AUX
cusj-5696	22	46	applied	apply	VERB
cusj-5696	22	47	for	for	ADP
cusj-5696	22	48	classification	classification	NOUN
cusj-5696	22	49	in	in	ADP
cusj-5696	22	50	unsupervised	unsupervised	ADJ
cusj-5696	22	51	training	training	NOUN
cusj-5696	22	52	with	with	ADP
cusj-5696	22	53	a	a	DET
cusj-5696	22	54	modified	modify	VERB
cusj-5696	22	55	version	version	NOUN
cusj-5696	22	56	of	of	ADP
cusj-5696	22	57	the	the	DET
cusj-5696	22	58	standard	standard	ADJ
cusj-5696	22	59	iterative	iterative	NOUN
cusj-5696	22	60	viterbi	viterbi	NOUN
cusj-5696	22	61	algorithm	algorithm	NOUN
cusj-5696	22	62	(	(	PUNCT
cusj-5696	22	63	durbin	durbin	NOUN
cusj-5696	22	64	)	)	PUNCT
cusj-5696	22	65	,	,	PUNCT
cusj-5696	22	66	where	where	SCONJ
cusj-5696	22	67	the	the	DET
cusj-5696	22	68	maximization	maximization	NOUN
cusj-5696	22	69	step	step	NOUN
cusj-5696	22	70	in	in	ADP
cusj-5696	22	71	em	em	PRON
cusj-5696	22	72	for	for	ADP
cusj-5696	22	73	the	the	DET
cusj-5696	22	74	continuous	continuous	ADJ
cusj-5696	22	75	-	-	PUNCT
cusj-5696	22	76	emission	emission	NOUN
cusj-5696	22	77	-	-	PUNCT
cusj-5696	22	78	matrix	matrix	NOUN
cusj-5696	22	79	e	e	NOUN
cusj-5696	22	80	uses	use	VERB
cusj-5696	22	81	bayesian	bayesian	NOUN
cusj-5696	22	82	update	update	NOUN
cusj-5696	22	83	(	(	PUNCT
cusj-5696	22	84	lynch	lynch	PROPN
cusj-5696	22	85	)	)	PUNCT
cusj-5696	22	86	on	on	ADP
cusj-5696	22	87	the	the	DET
cusj-5696	22	88	normal	normal	ADJ
cusj-5696	22	89	distributions	distribution	NOUN
cusj-5696	22	90	:	:	PUNCT
cusj-5696	22	91	a.obradovic	a.obradovic	ADJ
cusj-5696	22	92	,	,	PUNCT
cusj-5696	22	93	h.qi	h.qi	PROPN
cusj-5696	22	94	2	2	NUM
cusj-5696	22	95	(	(	PUNCT
cusj-5696	22	96	5	5	NUM
cusj-5696	22	97	)	)	PUNCT
cusj-5696	22	98	after	after	ADP
cusj-5696	22	99	15	15	NUM
cusj-5696	22	100	-	-	PUNCT
cusj-5696	22	101	state	state	NOUN
cusj-5696	22	102	classification	classification	NOUN
cusj-5696	22	103	,	,	PUNCT
cusj-5696	22	104	a	a	DET
cusj-5696	22	105	posterior	posterior	ADJ
cusj-5696	22	106	purity	purity	NOUN
cusj-5696	22	107	estimate	estimate	NOUN
cusj-5696	22	108	for	for	ADP
cusj-5696	22	109	each	each	DET
cusj-5696	22	110	bin	bin	NOUN
cusj-5696	22	111	where	where	SCONJ
cusj-5696	22	112	tumor	tumor	NOUN
cusj-5696	22	113	state	state	NOUN
cusj-5696	22	114	is	be	AUX
cusj-5696	22	115	not	not	PART
cusj-5696	22	116	equal	equal	ADJ
cusj-5696	22	117	to	to	ADP
cusj-5696	22	118	normal	normal	ADJ
cusj-5696	22	119	state	state	NOUN
cusj-5696	22	120	can	can	AUX
cusj-5696	22	121	be	be	AUX
cusj-5696	22	122	derived	derive	VERB
cusj-5696	22	123	from	from	ADP
cusj-5696	22	124	equation	equation	NOUN
cusj-5696	22	125	2	2	NUM
cusj-5696	22	126	,	,	PUNCT
cusj-5696	22	127	and	and	CCONJ
cusj-5696	22	128	this	this	DET
cusj-5696	22	129	distribution	distribution	NOUN
cusj-5696	22	130	can	can	AUX
cusj-5696	22	131	be	be	AUX
cusj-5696	22	132	plotted	plot	VERB
cusj-5696	22	133	to	to	PART
cusj-5696	22	134	visualize	visualize	VERB
cusj-5696	22	135	clonal	clonal	ADJ
cusj-5696	22	136	fraction	fraction	NOUN
cusj-5696	22	137	,	,	PUNCT
cusj-5696	22	138	as	as	ADV
cusj-5696	22	139	well	well	ADV
cusj-5696	22	140	as	as	ADP
cusj-5696	22	141	k	k	NOUN
cusj-5696	22	142	-	-	PUNCT
cusj-5696	22	143	means	means	NOUN
cusj-5696	22	144	-	-	PUNCT
cusj-5696	22	145	clustered	clustered	ADJ
cusj-5696	22	146	to	to	ADP
cusj-5696	22	147	group	group	NOUN
cusj-5696	22	148	mutations	mutation	NOUN
cusj-5696	22	149	belonging	belong	VERB
cusj-5696	22	150	to	to	ADP
cusj-5696	22	151	the	the	DET
cusj-5696	22	152	same	same	ADJ
cusj-5696	22	153	clone	clone	NOUN
cusj-5696	22	154	sub	sub	NOUN
cusj-5696	22	155	-	-	NOUN
cusj-5696	22	156	population	population	NOUN
cusj-5696	22	157	.	.	PUNCT
cusj-5696	23	1	this	this	PRON
cusj-5696	23	2	is	be	AUX
cusj-5696	23	3	compared	compare	VERB
cusj-5696	23	4	in	in	ADP
cusj-5696	23	5	simulated	simulated	ADJ
cusj-5696	23	6	data	datum	NOUN
cusj-5696	23	7	to	to	ADP
cusj-5696	23	8	the	the	DET
cusj-5696	23	9	known	know	VERB
cusj-5696	23	10	fractions	fraction	NOUN
cusj-5696	23	11	and	and	CCONJ
cusj-5696	23	12	the	the	DET
cusj-5696	23	13	accuracy	accuracy	NOUN
cusj-5696	23	14	is	be	AUX
cusj-5696	23	15	evaluated	evaluate	VERB
cusj-5696	23	16	.	.	PUNCT
cusj-5696	24	1	for	for	ADP
cusj-5696	24	2	cnv	cnv	PROPN
cusj-5696	24	3	-	-	PUNCT
cusj-5696	24	4	state	state	NOUN
cusj-5696	24	5	classification	classification	NOUN
cusj-5696	24	6	,	,	PUNCT
cusj-5696	24	7	the	the	DET
cusj-5696	24	8	15	15	NUM
cusj-5696	24	9	-	-	PUNCT
cusj-5696	24	10	state	state	NOUN
cusj-5696	24	11	model	model	NOUN
cusj-5696	24	12	is	be	AUX
cusj-5696	24	13	compressed	compress	VERB
cusj-5696	24	14	by	by	ADP
cusj-5696	24	15	grouping	group	VERB
cusj-5696	24	16	of	of	ADP
cusj-5696	24	17	equivalent	equivalent	ADJ
cusj-5696	24	18	states	state	NOUN
cusj-5696	24	19	into	into	ADP
cusj-5696	24	20	a	a	DET
cusj-5696	24	21	6	6	NUM
cusj-5696	24	22	-	-	PUNCT
cusj-5696	24	23	state	state	NOUN
cusj-5696	24	24	model	model	NOUN
cusj-5696	24	25	(	(	PUNCT
cusj-5696	24	26	see	see	VERB
cusj-5696	24	27	table	table	NOUN
cusj-5696	24	28	1	1	NUM
cusj-5696	24	29	)	)	PUNCT
cusj-5696	24	30	.	.	PUNCT
cusj-5696	25	1	table	table	NOUN
cusj-5696	25	2	1	1	NUM
cusj-5696	25	3	.	.	PUNCT
cusj-5696	26	1	state	state	NOUN
cusj-5696	26	2	compression	compression	NOUN
cusj-5696	26	3	table	table	NOUN
cusj-5696	26	4	.	.	PUNCT
cusj-5696	27	1	state	state	NOUN
cusj-5696	27	2	1	1	NUM
cusj-5696	27	3	2	2	NUM
cusj-5696	27	4	3	3	NUM
cusj-5696	27	5	4	4	NUM
cusj-5696	27	6	5	5	NUM
cusj-5696	27	7	6	6	NUM
cusj-5696	27	8	t	t	NOUN
cusj-5696	27	9	/	/	SYM
cusj-5696	27	10	n	n	NUM
cusj-5696	27	11	0/1	0/1	NUM
cusj-5696	27	12	,	,	PUNCT
cusj-5696	27	13	0/2	0/2	NUM
cusj-5696	27	14	,	,	PUNCT
cusj-5696	27	15	0/3	0/3	NUM
cusj-5696	27	16	1/2	1/2	NUM
cusj-5696	27	17	,	,	PUNCT
cusj-5696	27	18	1/3	1/3	NUM
cusj-5696	27	19	,	,	PUNCT
cusj-5696	27	20	2/3	2/3	NUM
cusj-5696	27	21	1/1	1/1	NUM
cusj-5696	27	22	,	,	PUNCT
cusj-5696	27	23	2/2	2/2	NUM
cusj-5696	27	24	,	,	PUNCT
cusj-5696	27	25	3/3	3/3	NUM
cusj-5696	27	26	,	,	PUNCT
cusj-5696	27	27	4/4	4/4	NUM
cusj-5696	27	28	3/2	3/2	NUM
cusj-5696	27	29	,	,	PUNCT
cusj-5696	27	30	4/3	4/3	NUM
cusj-5696	27	31	4/2	4/2	NUM
cusj-5696	27	32	,	,	PUNCT
cusj-5696	27	33	2/1	2/1	NUM
cusj-5696	27	34	3/1	3/1	NUM
cusj-5696	27	35	,	,	PUNCT
cusj-5696	27	36	4/1	4/1	NUM
cusj-5696	27	37	15	15	NUM
cusj-5696	27	38	-	-	PUNCT
cusj-5696	27	39	state	state	NOUN
cusj-5696	27	40	tumor	tumor	NOUN
cusj-5696	27	41	-	-	PUNCT
cusj-5696	27	42	normal	normal	ADJ
cusj-5696	27	43	model	model	NOUN
cusj-5696	27	44	is	be	AUX
cusj-5696	27	45	reduced	reduce	VERB
cusj-5696	27	46	by	by	ADP
cusj-5696	27	47	posterior	posterior	ADJ
cusj-5696	27	48	resolution	resolution	NOUN
cusj-5696	27	49	of	of	ADP
cusj-5696	27	50	ambiguities	ambiguity	NOUN
cusj-5696	27	51	to	to	ADP
cusj-5696	27	52	6	6	NUM
cusj-5696	27	53	distinct	distinct	ADJ
cusj-5696	27	54	cnv	cnv	NOUN
cusj-5696	27	55	states	state	NOUN
cusj-5696	27	56	.	.	PUNCT
cusj-5696	28	1	1	1	NUM
cusj-5696	28	2	-	-	PUNCT
cusj-5696	28	3	full	full	ADJ
cusj-5696	28	4	deletion	deletion	NOUN
cusj-5696	28	5	,	,	PUNCT
cusj-5696	28	6	2	2	NUM
cusj-5696	28	7	-	-	PUNCT
cusj-5696	28	8	partial	partial	ADJ
cusj-5696	28	9	deletion	deletion	NOUN
cusj-5696	28	10	,	,	PUNCT
cusj-5696	28	11	3	3	NUM
cusj-5696	28	12	-	-	PUNCT
cusj-5696	28	13	normal	normal	ADJ
cusj-5696	28	14	,	,	PUNCT
cusj-5696	28	15	4partial	4partial	ADJ
cusj-5696	28	16	amplification	amplification	NOUN
cusj-5696	28	17	,	,	PUNCT
cusj-5696	28	18	5	5	NUM
cusj-5696	28	19	-	-	PUNCT
cusj-5696	28	20	homozygous	homozygous	ADJ
cusj-5696	28	21	amplification	amplification	NOUN
cusj-5696	28	22	,	,	PUNCT
cusj-5696	28	23	6	6	NUM
cusj-5696	28	24	-	-	PUNCT
cusj-5696	28	25	large	large	ADJ
cusj-5696	28	26	amplification	amplification	NOUN
cusj-5696	28	27	.	.	PUNCT
cusj-5696	29	1	as	as	ADP
cusj-5696	29	2	a	a	DET
cusj-5696	29	3	benchmark	benchmark	NOUN
cusj-5696	29	4	for	for	ADP
cusj-5696	29	5	accuracy	accuracy	NOUN
cusj-5696	29	6	of	of	ADP
cusj-5696	29	7	cnv	cnv	PROPN
cusj-5696	29	8	state	state	NOUN
cusj-5696	29	9	classification	classification	NOUN
cusj-5696	29	10	,	,	PUNCT
cusj-5696	29	11	a	a	DET
cusj-5696	29	12	naïve	naïve	ADJ
cusj-5696	29	13	thresholding	thresholding	NOUN
cusj-5696	29	14	method	method	NOUN
cusj-5696	29	15	is	be	AUX
cusj-5696	29	16	used	use	VERB
cusj-5696	29	17	,	,	PUNCT
cusj-5696	29	18	where	where	SCONJ
cusj-5696	29	19	thresholds	threshold	NOUN
cusj-5696	29	20	are	be	AUX
cusj-5696	29	21	drawn	draw	VERB
cusj-5696	29	22	at	at	ADP
cusj-5696	29	23	the	the	DET
cusj-5696	29	24	log	log	NOUN
cusj-5696	29	25	-	-	PUNCT
cusj-5696	29	26	ratio	ratio	NOUN
cusj-5696	29	27	values	value	NOUN
cusj-5696	29	28	from	from	ADP
cusj-5696	29	29	equation	equation	NOUN
cusj-5696	29	30	1	1	NUM
cusj-5696	29	31	with	with	ADP
cusj-5696	29	32	purity	purity	NOUN
cusj-5696	29	33	prior	prior	ADV
cusj-5696	29	34	k	k	PROPN
cusj-5696	29	35	and	and	CCONJ
cusj-5696	29	36	t	t	PROPN
cusj-5696	29	37	/	/	SYM
cusj-5696	29	38	n	n	PROPN
cusj-5696	29	39	states	state	NOUN
cusj-5696	29	40	0/2	0/2	NUM
cusj-5696	29	41	,	,	PUNCT
cusj-5696	29	42	2/3	2/3	NUM
cusj-5696	29	43	,	,	PUNCT
cusj-5696	29	44	4/3	4/3	NUM
cusj-5696	29	45	,	,	PUNCT
cusj-5696	29	46	4/2	4/2	NUM
cusj-5696	29	47	,	,	PUNCT
cusj-5696	29	48	and	and	CCONJ
cusj-5696	29	49	3/1	3/1	NUM
cusj-5696	29	50	,	,	PUNCT
cusj-5696	29	51	and	and	CCONJ
cusj-5696	29	52	a	a	DET
cusj-5696	29	53	genome	genome	NOUN
cusj-5696	29	54	location	location	NOUN
cusj-5696	29	55	is	be	AUX
cusj-5696	29	56	classified	classify	VERB
cusj-5696	29	57	into	into	ADP
cusj-5696	29	58	one	one	NUM
cusj-5696	29	59	of	of	ADP
cusj-5696	29	60	the	the	DET
cusj-5696	29	61	six	six	NUM
cusj-5696	29	62	compressed	compressed	ADJ
cusj-5696	29	63	states	state	NOUN
cusj-5696	29	64	as	as	ADP
cusj-5696	29	65	whatever	whatever	DET
cusj-5696	29	66	interval	interval	NOUN
cusj-5696	29	67	of	of	ADP
cusj-5696	29	68	these	these	DET
cusj-5696	29	69	thresholds	threshold	NOUN
cusj-5696	29	70	its	its	PRON
cusj-5696	29	71	log	log	NOUN
cusj-5696	29	72	-	-	PUNCT
cusj-5696	29	73	ratio	ratio	NOUN
cusj-5696	29	74	falls	fall	VERB
cusj-5696	29	75	inside	inside	ADP
cusj-5696	29	76	of	of	ADP
cusj-5696	29	77	.	.	PUNCT
cusj-5696	30	1	there	there	PRON
cusj-5696	30	2	is	be	VERB
cusj-5696	30	3	no	no	DET
cusj-5696	30	4	equivalent	equivalent	ADJ
cusj-5696	30	5	benchmark	benchmark	NOUN
cusj-5696	30	6	for	for	ADP
cusj-5696	30	7	posterior	posterior	ADJ
cusj-5696	30	8	purity	purity	NOUN
cusj-5696	30	9	from	from	ADP
cusj-5696	30	10	the	the	DET
cusj-5696	30	11	hmm	hmm	NOUN
cusj-5696	30	12	model	model	NOUN
cusj-5696	30	13	,	,	PUNCT
cusj-5696	30	14	as	as	SCONJ
cusj-5696	30	15	this	this	PRON
cusj-5696	30	16	is	be	AUX
cusj-5696	30	17	the	the	DET
cusj-5696	30	18	primary	primary	ADJ
cusj-5696	30	19	innovation	innovation	NOUN
cusj-5696	30	20	of	of	ADP
cusj-5696	30	21	our	our	PRON
cusj-5696	30	22	method	method	NOUN
cusj-5696	30	23	,	,	PUNCT
cusj-5696	30	24	so	so	SCONJ
cusj-5696	30	25	it	it	PRON
cusj-5696	30	26	is	be	AUX
cusj-5696	30	27	evaluated	evaluate	VERB
cusj-5696	30	28	on	on	ADP
cusj-5696	30	29	its	its	PRON
cusj-5696	30	30	own	own	ADJ
cusj-5696	30	31	.	.	PUNCT
cusj-5696	31	1	3	3	NUM
cusj-5696	31	2	results	result	VERB
cusj-5696	31	3	simulated	simulate	VERB
cusj-5696	31	4	data	datum	NOUN
cusj-5696	31	5	was	be	AUX
cusj-5696	31	6	run	run	VERB
cusj-5696	31	7	for	for	ADP
cusj-5696	31	8	ten	ten	NUM
cusj-5696	31	9	matched	match	VERB
cusj-5696	31	10	tumor	tumor	NOUN
cusj-5696	31	11	-	-	PUNCT
cusj-5696	31	12	normal	normal	ADJ
cusj-5696	31	13	genomes	genome	NOUN
cusj-5696	31	14	,	,	PUNCT
cusj-5696	31	15	with	with	SCONJ
cusj-5696	31	16	all	all	DET
cusj-5696	31	17	parameters	parameter	NOUN
cusj-5696	31	18	but	but	CCONJ
cusj-5696	31	19	purity	purity	NOUN
cusj-5696	31	20	kept	keep	VERB
cusj-5696	31	21	constant	constant	ADJ
cusj-5696	31	22	at	at	ADP
cusj-5696	31	23	default	default	NOUN
cusj-5696	31	24	value	value	NOUN
cusj-5696	31	25	.	.	PUNCT
cusj-5696	32	1	the	the	DET
cusj-5696	32	2	first	first	ADJ
cusj-5696	32	3	trial	trial	NOUN
cusj-5696	32	4	was	be	AUX
cusj-5696	32	5	homogeneous	homogeneous	ADJ
cusj-5696	32	6	tumor	tumor	NOUN
cusj-5696	32	7	admixed	admix	VERB
cusj-5696	32	8	with	with	ADP
cusj-5696	32	9	normal	normal	ADJ
cusj-5696	32	10	cells	cell	NOUN
cusj-5696	32	11	at	at	ADP
cusj-5696	32	12	0.9	0.9	NUM
cusj-5696	32	13	clonal	clonal	ADJ
cusj-5696	32	14	fraction	fraction	NOUN
cusj-5696	32	15	.	.	PUNCT
cusj-5696	33	1	each	each	PRON
cusj-5696	33	2	of	of	ADP
cusj-5696	33	3	the	the	DET
cusj-5696	33	4	next	next	ADJ
cusj-5696	33	5	eight	eight	NUM
cusj-5696	33	6	trials	trial	NOUN
cusj-5696	33	7	contained	contain	VERB
cusj-5696	33	8	two	two	NUM
cusj-5696	33	9	equiprobable	equiprobable	ADJ
cusj-5696	33	10	purity	purity	NOUN
cusj-5696	33	11	values	value	NOUN
cusj-5696	33	12	,	,	PUNCT
cusj-5696	33	13	with	with	ADP
cusj-5696	33	14	a	a	DET
cusj-5696	33	15	dominant	dominant	ADJ
cusj-5696	33	16	0.9	0.9	NUM
cusj-5696	33	17	fraction	fraction	NOUN
cusj-5696	33	18	clone	clone	NOUN
cusj-5696	33	19	and	and	CCONJ
cusj-5696	33	20	a	a	DET
cusj-5696	33	21	secondary	secondary	ADJ
cusj-5696	33	22	subset	subset	NOUN
cusj-5696	33	23	of	of	ADP
cusj-5696	33	24	fraction	fraction	NOUN
cusj-5696	33	25	ranging	range	VERB
cusj-5696	33	26	from	from	ADP
cusj-5696	33	27	0.85	0.85	NUM
cusj-5696	33	28	to	to	ADP
cusj-5696	33	29	0.5	0.5	NUM
cusj-5696	33	30	at	at	ADP
cusj-5696	33	31	intervals	interval	NOUN
cusj-5696	33	32	of	of	ADP
cusj-5696	33	33	0.05	0.05	NUM
cusj-5696	33	34	.	.	PUNCT
cusj-5696	34	1	a	a	DET
cusj-5696	34	2	final	final	ADJ
cusj-5696	34	3	heterogeneous	heterogeneous	ADJ
cusj-5696	34	4	tumor	tumor	NOUN
cusj-5696	34	5	trial	trial	NOUN
cusj-5696	34	6	was	be	AUX
cusj-5696	34	7	run	run	VERB
cusj-5696	34	8	with	with	ADP
cusj-5696	34	9	three	three	NUM
cusj-5696	34	10	equiprobable	equiprobable	ADJ
cusj-5696	34	11	mutation	mutation	NOUN
cusj-5696	34	12	fractions	fraction	NOUN
cusj-5696	34	13	of	of	ADP
cusj-5696	34	14	0.9	0.9	NUM
cusj-5696	34	15	,	,	PUNCT
cusj-5696	34	16	0.7	0.7	NUM
cusj-5696	34	17	,	,	PUNCT
cusj-5696	34	18	and	and	CCONJ
cusj-5696	34	19	0.5	0.5	NUM
cusj-5696	34	20	.	.	PUNCT
cusj-5696	35	1	in	in	ADP
cusj-5696	35	2	terms	term	NOUN
cusj-5696	35	3	of	of	ADP
cusj-5696	35	4	state	state	NOUN
cusj-5696	35	5	classification	classification	NOUN
cusj-5696	35	6	accuracy	accuracy	NOUN
cusj-5696	35	7	,	,	PUNCT
cusj-5696	35	8	each	each	DET
cusj-5696	35	9	trial	trial	NOUN
cusj-5696	35	10	showed	show	VERB
cusj-5696	35	11	correct	correct	ADJ
cusj-5696	35	12	classification	classification	NOUN
cusj-5696	35	13	for	for	ADP
cusj-5696	35	14	clones	clone	NOUN
cusj-5696	35	15	represented	represent	VERB
cusj-5696	35	16	in	in	ADP
cusj-5696	35	17	0.7	0.7	NUM
cusj-5696	35	18	or	or	CCONJ
cusj-5696	35	19	higher	high	ADJ
cusj-5696	35	20	proportion	proportion	NOUN
cusj-5696	35	21	of	of	ADP
cusj-5696	35	22	the	the	DET
cusj-5696	35	23	tumor	tumor	NOUN
cusj-5696	35	24	sample	sample	NOUN
cusj-5696	35	25	with	with	ADP
cusj-5696	35	26	accuracy	accuracy	NOUN
cusj-5696	35	27	over	over	ADP
cusj-5696	35	28	99.9	99.9	NUM
cusj-5696	35	29	%	%	NOUN
cusj-5696	35	30	.	.	PUNCT
cusj-5696	36	1	this	this	PRON
cusj-5696	36	2	is	be	AUX
cusj-5696	36	3	significantly	significantly	ADV
cusj-5696	36	4	higher	high	ADJ
cusj-5696	36	5	than	than	ADP
cusj-5696	36	6	the	the	DET
cusj-5696	36	7	approximately	approximately	ADV
cusj-5696	36	8	70	70	NUM
cusj-5696	36	9	%	%	NOUN
cusj-5696	36	10	accuracy	accuracy	NOUN
cusj-5696	36	11	seen	see	VERB
cusj-5696	36	12	in	in	ADP
cusj-5696	36	13	the	the	DET
cusj-5696	36	14	naïve	naïve	ADJ
cusj-5696	36	15	thresholding	thresholding	NOUN
cusj-5696	36	16	benchmark	benchmark	NOUN
cusj-5696	36	17	.	.	PUNCT
cusj-5696	37	1	both	both	DET
cusj-5696	37	2	methods	method	NOUN
cusj-5696	37	3	,	,	PUNCT
cusj-5696	37	4	however	however	ADV
cusj-5696	37	5	,	,	PUNCT
cusj-5696	37	6	lose	lose	VERB
cusj-5696	37	7	accuracy	accuracy	NOUN
cusj-5696	37	8	for	for	ADP
cusj-5696	37	9	rarer	rare	ADJ
cusj-5696	37	10	cnv	cnv	NOUN
cusj-5696	37	11	mutations	mutation	NOUN
cusj-5696	37	12	,	,	PUNCT
cusj-5696	37	13	although	although	SCONJ
cusj-5696	37	14	our	our	PRON
cusj-5696	37	15	cfhmm	cfhmm	NOUN
cusj-5696	37	16	method	method	NOUN
cusj-5696	37	17	remains	remain	VERB
cusj-5696	37	18	more	more	ADV
cusj-5696	37	19	accurate	accurate	ADJ
cusj-5696	37	20	than	than	ADP
cusj-5696	37	21	the	the	DET
cusj-5696	37	22	benchmark	benchmark	NOUN
cusj-5696	37	23	across	across	ADP
cusj-5696	37	24	the	the	DET
cusj-5696	37	25	board	board	NOUN
cusj-5696	37	26	(	(	PUNCT
cusj-5696	37	27	see	see	VERB
cusj-5696	37	28	fig	fig	NOUN
cusj-5696	37	29	.	.	PUNCT
cusj-5696	38	1	1	1	NUM
cusj-5696	38	2	)	)	PUNCT
cusj-5696	38	3	.	.	PUNCT
cusj-5696	39	1	accuracy	accuracy	NOUN
cusj-5696	39	2	of	of	ADP
cusj-5696	39	3	posterior	posterior	ADJ
cusj-5696	39	4	purity	purity	NOUN
cusj-5696	39	5	estimates	estimate	NOUN
cusj-5696	39	6	(	(	PUNCT
cusj-5696	39	7	+	+	ADJ
cusj-5696	39	8	/	/	SYM
cusj-5696	39	9	0.01	0.01	NUM
cusj-5696	39	10	of	of	ADP
cusj-5696	39	11	true	true	ADJ
cusj-5696	39	12	value	value	NOUN
cusj-5696	39	13	)	)	PUNCT
cusj-5696	39	14	was	be	AUX
cusj-5696	39	15	also	also	ADV
cusj-5696	39	16	better	well	ADJ
cusj-5696	39	17	for	for	ADP
cusj-5696	39	18	high	high	ADJ
cusj-5696	39	19	-	-	PUNCT
cusj-5696	39	20	fraction	fraction	NOUN
cusj-5696	39	21	cnvs	cnvs	NOUN
cusj-5696	39	22	,	,	PUNCT
cusj-5696	39	23	showing	show	VERB
cusj-5696	39	24	around	around	ADP
cusj-5696	39	25	80	80	NUM
cusj-5696	39	26	%	%	NOUN
cusj-5696	39	27	accuracy	accuracy	NOUN
cusj-5696	39	28	in	in	ADP
cusj-5696	39	29	all	all	DET
cusj-5696	39	30	trials	trial	NOUN
cusj-5696	39	31	for	for	ADP
cusj-5696	39	32	the	the	DET
cusj-5696	39	33	dominant	dominant	ADJ
cusj-5696	39	34	clone	clone	NOUN
cusj-5696	39	35	and	and	CCONJ
cusj-5696	39	36	accuracy	accuracy	NOUN
cusj-5696	39	37	decreasing	decrease	VERB
cusj-5696	39	38	to	to	ADP
cusj-5696	39	39	56	56	NUM
cusj-5696	39	40	%	%	NOUN
cusj-5696	39	41	for	for	ADP
cusj-5696	39	42	0.5	0.5	NUM
cusj-5696	39	43	purity	purity	NOUN
cusj-5696	39	44	.	.	PUNCT
cusj-5696	40	1	posterior	posterior	ADJ
cusj-5696	40	2	purity	purity	NOUN
cusj-5696	40	3	estimates	estimate	NOUN
cusj-5696	40	4	show	show	VERB
cusj-5696	40	5	clear	clear	ADJ
cusj-5696	40	6	peaks	peak	NOUN
cusj-5696	40	7	at	at	ADP
cusj-5696	40	8	the	the	DET
cusj-5696	40	9	true	true	ADJ
cusj-5696	40	10	purities	purity	NOUN
cusj-5696	40	11	for	for	ADP
cusj-5696	40	12	k	k	X
cusj-5696	40	13	greater	great	ADJ
cusj-5696	40	14	than	than	ADP
cusj-5696	40	15	or	or	CCONJ
cusj-5696	40	16	equal	equal	ADJ
cusj-5696	40	17	to	to	ADP
cusj-5696	40	18	0.7	0.7	NUM
cusj-5696	40	19	,	,	PUNCT
cusj-5696	40	20	usefully	usefully	ADV
cusj-5696	40	21	depicting	depict	VERB
cusj-5696	40	22	tumor	tumor	NOUN
cusj-5696	40	23	heterogeneity	heterogeneity	NOUN
cusj-5696	40	24	,	,	PUNCT
cusj-5696	40	25	but	but	CCONJ
cusj-5696	40	26	retaining	retain	VERB
cusj-5696	40	27	only	only	ADV
cusj-5696	40	28	the	the	DET
cusj-5696	40	29	dominant	dominant	ADJ
cusj-5696	40	30	-	-	PUNCT
cusj-5696	40	31	clone	clone	NOUN
cusj-5696	40	32	peaks	peak	NOUN
cusj-5696	40	33	for	for	ADP
cusj-5696	40	34	tumors	tumor	NOUN
cusj-5696	40	35	with	with	ADP
cusj-5696	40	36	rarer	rarer	ADV
cusj-5696	40	37	admixed	admix	VERB
cusj-5696	40	38	mutations	mutation	NOUN
cusj-5696	40	39	,	,	PUNCT
cusj-5696	40	40	such	such	ADJ
cusj-5696	40	41	as	as	ADP
cusj-5696	40	42	the	the	DET
cusj-5696	40	43	3	3	NUM
cusj-5696	40	44	-	-	PUNCT
cusj-5696	40	45	state	state	NOUN
cusj-5696	40	46	trial	trial	NOUN
cusj-5696	40	47	tumor	tumor	NOUN
cusj-5696	40	48	,	,	PUNCT
cusj-5696	40	49	where	where	SCONJ
cusj-5696	40	50	states	state	NOUN
cusj-5696	40	51	0.9	0.9	NUM
cusj-5696	40	52	and	and	CCONJ
cusj-5696	40	53	0.7	0.7	NUM
cusj-5696	40	54	were	be	AUX
cusj-5696	40	55	well	well	ADV
cusj-5696	40	56	-	-	PUNCT
cusj-5696	40	57	described	describe	VERB
cusj-5696	40	58	and	and	CCONJ
cusj-5696	40	59	classified	classify	VERB
cusj-5696	40	60	with	with	ADP
cusj-5696	40	61	high	high	ADJ
cusj-5696	40	62	accuracy	accuracy	NOUN
cusj-5696	40	63	,	,	PUNCT
cusj-5696	40	64	but	but	CCONJ
cusj-5696	40	65	0.5	0.5	NUM
cusj-5696	40	66	was	be	AUX
cusj-5696	40	67	not	not	PART
cusj-5696	40	68	(	(	PUNCT
cusj-5696	40	69	see	see	VERB
cusj-5696	40	70	table	table	NOUN
cusj-5696	40	71	2	2	NUM
cusj-5696	40	72	)	)	PUNCT
cusj-5696	40	73	.	.	PUNCT
cusj-5696	41	1	table	table	NOUN
cusj-5696	42	1	2	2	NUM
cusj-5696	42	2	.	.	X
cusj-5696	42	3	three	three	NUM
cusj-5696	42	4	-	-	PUNCT
cusj-5696	42	5	state	state	NOUN
cusj-5696	42	6	0.9	0.9	NUM
cusj-5696	42	7	,	,	PUNCT
cusj-5696	42	8	0.7	0.7	NUM
cusj-5696	42	9	,	,	PUNCT
cusj-5696	42	10	0.5	0.5	NUM
cusj-5696	42	11	purity	purity	NOUN
cusj-5696	42	12	trial	trial	NOUN
cusj-5696	42	13	purity	purity	NOUN
cusj-5696	42	14	states	state	NOUN
cusj-5696	42	15	hmm	hmm	INTJ
cusj-5696	42	16	state	state	NOUN
cusj-5696	42	17	accuracy	accuracy	NOUN
cusj-5696	42	18	thresholding	thresholde	VERB
cusj-5696	42	19	state	state	NOUN
cusj-5696	42	20	accuracy	accuracy	NOUN
cusj-5696	42	21	hmm	hmm	INTJ
cusj-5696	42	22	purity	purity	NOUN
cusj-5696	42	23	accuracy	accuracy	NOUN
cusj-5696	42	24	.9	.9	NUM
cusj-5696	43	1	0.9995894	0.9995894	NUM
cusj-5696	43	2	0.6706574	0.6706574	NUM
cusj-5696	43	3	0.8174977	0.8174977	NUM
cusj-5696	43	4	.7	.7	NUM
cusj-5696	43	5	0.9992959	0.9992959	NUM
cusj-5696	43	6	0.5384039	0.5384039	NUM
cusj-5696	43	7	0.7150379	0.7150379	NUM
cusj-5696	43	8	.5	.5	NUM
cusj-5696	44	1	0.649813	0.649813	NUM
cusj-5696	44	2	0.3955961	0.3955961	NUM
cusj-5696	44	3	0.4992132	0.4992132	NUM
cusj-5696	44	4	accuracy	accuracy	NOUN
cusj-5696	44	5	is	be	AUX
cusj-5696	44	6	shown	show	VERB
cusj-5696	44	7	per	per	ADP
cusj-5696	44	8	purity	purity	NOUN
cusj-5696	44	9	state	state	NOUN
cusj-5696	44	10	for	for	ADP
cusj-5696	44	11	the	the	DET
cusj-5696	44	12	hmm	hmm	NOUN
cusj-5696	44	13	classification	classification	NOUN
cusj-5696	44	14	,	,	PUNCT
cusj-5696	44	15	thresholding	thresholde	VERB
cusj-5696	44	16	classification	classification	NOUN
cusj-5696	44	17	,	,	PUNCT
cusj-5696	44	18	and	and	CCONJ
cusj-5696	44	19	hmm	hmm	ADV
cusj-5696	44	20	-	-	PUNCT
cusj-5696	44	21	derived	derive	VERB
cusj-5696	44	22	purity	purity	NOUN
cusj-5696	44	23	.	.	PUNCT
cusj-5696	45	1	areas	area	NOUN
cusj-5696	45	2	for	for	ADP
cusj-5696	45	3	future	future	ADJ
cusj-5696	45	4	work	work	NOUN
cusj-5696	45	5	include	include	VERB
cusj-5696	45	6	the	the	DET
cusj-5696	45	7	implementation	implementation	NOUN
cusj-5696	45	8	of	of	ADP
cusj-5696	45	9	baum	baum	PROPN
cusj-5696	45	10	-	-	PUNCT
cusj-5696	45	11	welch	welch	PROPN
cusj-5696	45	12	rather	rather	ADV
cusj-5696	45	13	than	than	ADP
cusj-5696	45	14	viterbi	viterbi	ADJ
cusj-5696	45	15	training	training	NOUN
cusj-5696	45	16	for	for	ADP
cusj-5696	45	17	hmm	hmm	INTJ
cusj-5696	45	18	learning	learn	VERB
cusj-5696	45	19	(	(	PUNCT
cusj-5696	45	20	durbin	durbin	ADJ
cusj-5696	45	21	)	)	PUNCT
cusj-5696	45	22	,	,	PUNCT
cusj-5696	45	23	in	in	ADP
cusj-5696	45	24	order	order	NOUN
cusj-5696	45	25	to	to	PART
cusj-5696	45	26	ensure	ensure	VERB
cusj-5696	45	27	globally	globally	ADV
cusj-5696	45	28	optimal	optimal	ADJ
cusj-5696	45	29	solution	solution	NOUN
cusj-5696	45	30	,	,	PUNCT
cusj-5696	45	31	as	as	ADV
cusj-5696	45	32	well	well	ADV
cusj-5696	45	33	as	as	ADP
cusj-5696	45	34	the	the	DET
cusj-5696	45	35	application	application	NOUN
cusj-5696	45	36	of	of	ADP
cusj-5696	45	37	the	the	DET
cusj-5696	45	38	algorithm	algorithm	NOUN
cusj-5696	45	39	to	to	ADP
cusj-5696	45	40	real	real	ADJ
cusj-5696	45	41	matched	match	VERB
cusj-5696	45	42	cancer	cancer	NOUN
cusj-5696	45	43	sequencing	sequence	VERB
cusj-5696	45	44	datasets	dataset	NOUN
cusj-5696	45	45	for	for	ADP
cusj-5696	45	46	further	further	ADJ
cusj-5696	45	47	validation	validation	NOUN
cusj-5696	45	48	.	.	PUNCT
cusj-5696	46	1	in	in	ADP
cusj-5696	46	2	addition	addition	NOUN
cusj-5696	46	3	,	,	PUNCT
cusj-5696	46	4	the	the	DET
cusj-5696	46	5	breakdown	breakdown	NOUN
cusj-5696	46	6	of	of	ADP
cusj-5696	46	7	the	the	DET
cusj-5696	46	8	method	method	NOUN
cusj-5696	46	9	for	for	ADP
cusj-5696	46	10	lowfraction	lowfraction	NOUN
cusj-5696	46	11	cnvs	cnvs	NOUN
cusj-5696	46	12	is	be	AUX
cusj-5696	46	13	a	a	DET
cusj-5696	46	14	limitation	limitation	NOUN
cusj-5696	46	15	than	than	SCONJ
cusj-5696	46	16	should	should	AUX
cusj-5696	46	17	be	be	AUX
cusj-5696	46	18	addressed	address	VERB
cusj-5696	46	19	,	,	PUNCT
cusj-5696	46	20	possibly	possibly	ADV
cusj-5696	46	21	by	by	ADP
cusj-5696	46	22	iterative	iterative	ADJ
cusj-5696	46	23	exclusion	exclusion	NOUN
cusj-5696	46	24	of	of	ADP
cusj-5696	46	25	classified	classified	ADJ
cusj-5696	46	26	dominant	dominant	ADJ
cusj-5696	46	27	mutation	mutation	NOUN
cusj-5696	46	28	sites	site	NOUN
cusj-5696	46	29	,	,	PUNCT
cusj-5696	46	30	so	so	SCONJ
cusj-5696	46	31	that	that	SCONJ
cusj-5696	46	32	the	the	DET
cusj-5696	46	33	new	new	ADJ
cusj-5696	46	34	prior	prior	NOUN
cusj-5696	46	35	on	on	ADP
cusj-5696	46	36	subsequent	subsequent	ADJ
cusj-5696	46	37	runs	run	NOUN
cusj-5696	46	38	of	of	ADP
cusj-5696	46	39	the	the	DET
cusj-5696	46	40	algorithm	algorithm	NOUN
cusj-5696	46	41	is	be	AUX
cusj-5696	46	42	pulled	pull	VERB
cusj-5696	46	43	toward	toward	ADP
cusj-5696	46	44	lower	low	ADJ
cusj-5696	46	45	purity	purity	NOUN
cusj-5696	46	46	,	,	PUNCT
cusj-5696	46	47	so	so	ADV
cusj-5696	46	48	long	long	ADV
cusj-5696	46	49	as	as	SCONJ
cusj-5696	46	50	the	the	DET
cusj-5696	46	51	limitation	limitation	NOUN
cusj-5696	46	52	for	for	ADP
cusj-5696	46	53	the	the	DET
cusj-5696	46	54	markov	markov	NOUN
cusj-5696	46	55	assumption	assumption	NOUN
cusj-5696	46	56	presented	present	VERB
cusj-5696	46	57	by	by	ADP
cusj-5696	46	58	resulting	result	VERB
cusj-5696	46	59	holes	hole	NOUN
cusj-5696	46	60	in	in	ADP
cusj-5696	46	61	the	the	DET
cusj-5696	46	62	data	datum	NOUN
cusj-5696	46	63	can	can	AUX
cusj-5696	46	64	be	be	AUX
cusj-5696	46	65	addressed	address	VERB
cusj-5696	46	66	.	.	PUNCT
cusj-5696	47	1	acknowledgements	acknowledgement	NOUN
cusj-5696	47	2	we	we	PRON
cusj-5696	47	3	wish	wish	VERB
cusj-5696	47	4	to	to	PART
cusj-5696	47	5	thank	thank	VERB
cusj-5696	47	6	dr	dr	PROPN
cusj-5696	47	7	.	.	PROPN
cusj-5696	47	8	itsik	itsik	PROPN
cusj-5696	47	9	pe’er	pe’er	NOUN
cusj-5696	47	10	and	and	CCONJ
cusj-5696	47	11	the	the	DET
cusj-5696	47	12	students	student	NOUN
cusj-5696	47	13	of	of	ADP
cusj-5696	47	14	cbmfw4761	cbmfw4761	PROPN
cusj-5696	47	15	for	for	ADP
cusj-5696	47	16	providing	provide	VERB
cusj-5696	47	17	feedback	feedback	NOUN
cusj-5696	47	18	and	and	CCONJ
cusj-5696	47	19	advisement	advisement	NOUN
cusj-5696	47	20	on	on	ADP
cusj-5696	47	21	project	project	NOUN
cusj-5696	47	22	design	design	NOUN
cusj-5696	47	23	.	.	PUNCT
cusj-5696	48	1	references	reference	NOUN
cusj-5696	48	2	durbin	durbin	PROPN
cusj-5696	48	3	,	,	PUNCT
cusj-5696	48	4	richard	richard	PROPN
cusj-5696	48	5	,	,	PUNCT
cusj-5696	48	6	ed	ed	NOUN
cusj-5696	48	7	.	.	PUNCT
cusj-5696	49	1	biological	biological	ADJ
cusj-5696	49	2	sequence	sequence	NOUN
cusj-5696	49	3	analysis	analysis	NOUN
cusj-5696	49	4	:	:	PUNCT
cusj-5696	49	5	probabilistic	probabilistic	ADJ
cusj-5696	49	6	models	model	NOUN
cusj-5696	49	7	of	of	ADP
cusj-5696	49	8	proteins	protein	NOUN
cusj-5696	49	9	and	and	CCONJ
cusj-5696	49	10	nucleic	nucleic	ADJ
cusj-5696	49	11	acids	acid	NOUN
cusj-5696	49	12	.	.	PUNCT
cusj-5696	50	1	cambridge	cambridge	PROPN
cusj-5696	50	2	university	university	PROPN
cusj-5696	50	3	press	press	NOUN
cusj-5696	50	4	,	,	PUNCT
cusj-5696	50	5	1998	1998	NUM
cusj-5696	50	6	.	.	PUNCT
cusj-5696	51	1	gusnanto	gusnanto	NOUN
cusj-5696	51	2	,	,	PUNCT
cusj-5696	51	3	arief	arief	NOUN
cusj-5696	51	4	,	,	PUNCT
cusj-5696	51	5	et	et	PROPN
cusj-5696	51	6	al	al	PROPN
cusj-5696	51	7	.	.	PUNCT
cusj-5696	52	1	"	"	PUNCT
cusj-5696	52	2	correcting	correct	VERB
cusj-5696	52	3	for	for	ADP
cusj-5696	52	4	cancer	cancer	NOUN
cusj-5696	52	5	genome	genome	NOUN
cusj-5696	52	6	size	size	NOUN
cusj-5696	52	7	and	and	CCONJ
cusj-5696	52	8	tumour	tumour	NOUN
cusj-5696	52	9	cell	cell	NOUN
cusj-5696	52	10	content	content	NOUN
cusj-5696	52	11	enables	enable	VERB
cusj-5696	52	12	better	well	ADJ
cusj-5696	52	13	estimation	estimation	NOUN
cusj-5696	52	14	of	of	ADP
cusj-5696	52	15	copy	copy	NOUN
cusj-5696	52	16	number	number	NOUN
cusj-5696	52	17	alterations	alteration	NOUN
cusj-5696	52	18	from	from	ADP
cusj-5696	52	19	next	next	ADJ
cusj-5696	52	20	-	-	PUNCT
cusj-5696	52	21	generation	generation	NOUN
cusj-5696	52	22	sequence	sequence	NOUN
cusj-5696	52	23	data	datum	NOUN
cusj-5696	52	24	.	.	PUNCT
cusj-5696	52	25	"	"	PUNCT
cusj-5696	53	1	bioinformatics	bioinformatic	NOUN
cusj-5696	53	2	28.1	28.1	NUM
cusj-5696	53	3	(	(	PUNCT
cusj-5696	53	4	2012	2012	NUM
cusj-5696	53	5	):	):	PUNCT
cusj-5696	53	6	40	40	NUM
cusj-5696	53	7	-	-	SYM
cusj-5696	53	8	47	47	NUM
cusj-5696	53	9	.	.	PUNCT
cusj-5696	54	1	lynch	lynch	PROPN
cusj-5696	54	2	,	,	PUNCT
cusj-5696	54	3	scott	scott	PROPN
cusj-5696	54	4	m.	m.	NOUN
cusj-5696	54	5	introduction	introduction	NOUN
cusj-5696	54	6	to	to	ADP
cusj-5696	54	7	applied	apply	VERB
cusj-5696	54	8	bayesian	bayesian	NOUN
cusj-5696	54	9	statistics	statistic	NOUN
cusj-5696	54	10	and	and	CCONJ
cusj-5696	54	11	estimation	estimation	NOUN
cusj-5696	54	12	for	for	ADP
cusj-5696	54	13	social	social	ADJ
cusj-5696	54	14	scientists	scientist	NOUN
cusj-5696	54	15	.	.	PUNCT
cusj-5696	55	1	springer	springer	NOUN
cusj-5696	55	2	science	science	PROPN
cusj-5696	55	3	&	&	CCONJ
cusj-5696	55	4	business	business	NOUN
cusj-5696	55	5	media	medium	NOUN
cusj-5696	55	6	,	,	PUNCT
cusj-5696	55	7	2007	2007	NUM
cusj-5696	55	8	.	.	PUNCT
cusj-5696	56	1	myers	myer	NOUN
cusj-5696	56	2	,	,	PUNCT
cusj-5696	56	3	gene	gene	NOUN
cusj-5696	56	4	.	.	PUNCT
cusj-5696	57	1	"	"	PUNCT
cusj-5696	57	2	whole	whole	ADJ
cusj-5696	57	3	-	-	PUNCT
cusj-5696	57	4	genome	genome	NOUN
cusj-5696	57	5	dna	dna	NOUN
cusj-5696	57	6	sequencing	sequencing	NOUN
cusj-5696	57	7	.	.	PUNCT
cusj-5696	57	8	"	"	PUNCT
cusj-5696	58	1	computing	compute	VERB
cusj-5696	58	2	in	in	ADP
cusj-5696	58	3	science	science	NOUN
cusj-5696	58	4	and	and	CCONJ
cusj-5696	58	5	engineering	engineering	NOUN
cusj-5696	58	6	1.3	1.3	NUM
cusj-5696	58	7	(	(	PUNCT
cusj-5696	58	8	1999	1999	NUM
cusj-5696	58	9	):	):	PUNCT
cusj-5696	58	10	33	33	NUM
cusj-5696	58	11	-	-	SYM
cusj-5696	58	12	43	43	NUM
cusj-5696	58	13	oesper	oesper	NOUN
cusj-5696	58	14	,	,	PUNCT
cusj-5696	58	15	layla	layla	PROPN
cusj-5696	58	16	,	,	PUNCT
cusj-5696	58	17	gryte	gryte	NOUN
cusj-5696	58	18	satas	sata	NOUN
cusj-5696	58	19	,	,	PUNCT
cusj-5696	58	20	and	and	CCONJ
cusj-5696	58	21	benjamin	benjamin	PROPN
cusj-5696	58	22	j.	j.	PROPN
cusj-5696	58	23	raphael	raphael	PROPN
cusj-5696	58	24	.	.	PUNCT
cusj-5696	59	1	"	"	PUNCT
cusj-5696	59	2	quantifying	quantify	VERB
cusj-5696	59	3	tumor	tumor	NOUN
cusj-5696	59	4	heterogeneity	heterogeneity	NOUN
cusj-5696	59	5	in	in	ADP
cusj-5696	59	6	whole	whole	ADJ
cusj-5696	59	7	-	-	PUNCT
cusj-5696	59	8	genome	genome	NOUN
cusj-5696	59	9	and	and	CCONJ
cusj-5696	59	10	whole	whole	ADJ
cusj-5696	59	11	-	-	PUNCT
cusj-5696	59	12	exome	exome	NOUN
cusj-5696	59	13	sequencing	sequence	VERB
cusj-5696	59	14	data	datum	NOUN
cusj-5696	59	15	.	.	PUNCT
cusj-5696	60	1	"bioinformatics	"bioinformatics	PROPN
cusj-5696	60	2	30.24	30.24	NUM
cusj-5696	60	3	(	(	PUNCT
cusj-5696	60	4	2014	2014	NUM
cusj-5696	60	5	):	):	PUNCT
cusj-5696	60	6	3532	3532	NUM
cusj-5696	60	7	-	-	SYM
cusj-5696	60	8	3540	3540	NUM
cusj-5696	60	9	.	.	PUNCT
cusj-5696	61	1	zhang	zhang	PROPN
cusj-5696	61	2	,	,	PUNCT
cusj-5696	61	3	nancy	nancy	PROPN
cusj-5696	61	4	r.	r.	PROPN
cusj-5696	61	5	"	"	PUNCT
cusj-5696	61	6	dna	dna	PROPN
cusj-5696	61	7	copy	copy	VERB
cusj-5696	61	8	number	number	NOUN
cusj-5696	61	9	profiling	profiling	NOUN
cusj-5696	61	10	in	in	ADP
cusj-5696	61	11	normal	normal	ADJ
cusj-5696	61	12	and	and	CCONJ
cusj-5696	61	13	tumor	tumor	NOUN
cusj-5696	61	14	genomes	genome	NOUN
cusj-5696	61	15	.	.	PUNCT
cusj-5696	61	16	"	"	PUNCT
cusj-5696	61	17	frontiers	frontier	NOUN
cusj-5696	61	18	in	in	ADP
cusj-5696	61	19	computational	computational	ADJ
cusj-5696	61	20	and	and	CCONJ
cusj-5696	61	21	systems	system	NOUN
cusj-5696	61	22	biology	biology	NOUN
cusj-5696	61	23	.	.	PUNCT
cusj-5696	62	1	springer	springer	PROPN
cusj-5696	62	2	london	london	PROPN
cusj-5696	62	3	,	,	PUNCT
cusj-5696	62	4	2010	2010	NUM
cusj-5696	62	5	.	.	PUNCT
cusj-5696	63	1	259	259	NUM
cusj-5696	63	2	-	-	SYM
cusj-5696	63	3	281	281	NUM
cusj-5696	63	4	.	.	PUNCT
cusj-5696	64	1	zhao	zhao	PROPN
cusj-5696	64	2	,	,	PUNCT
cusj-5696	64	3	min	min	PROPN
cusj-5696	64	4	,	,	PUNCT
cusj-5696	64	5	et	et	PROPN
cusj-5696	64	6	al	al	PROPN
cusj-5696	64	7	.	.	PUNCT
cusj-5696	65	1	"	"	PUNCT
cusj-5696	65	2	computational	computational	ADJ
cusj-5696	65	3	tools	tool	NOUN
cusj-5696	65	4	for	for	ADP
cusj-5696	65	5	copy	copy	NOUN
cusj-5696	65	6	number	number	NOUN
cusj-5696	65	7	variation	variation	NOUN
cusj-5696	65	8	(	(	PUNCT
cusj-5696	65	9	cnv	cnv	NOUN
cusj-5696	65	10	)	)	PUNCT
cusj-5696	65	11	detection	detection	NOUN
cusj-5696	65	12	using	use	VERB
cusj-5696	65	13	next	next	ADJ
cusj-5696	65	14	-	-	PUNCT
cusj-5696	65	15	generation	generation	NOUN
cusj-5696	65	16	sequencing	sequence	VERB
cusj-5696	65	17	data	datum	NOUN
cusj-5696	65	18	:	:	PUNCT
cusj-5696	65	19	features	feature	NOUN
cusj-5696	65	20	and	and	CCONJ
cusj-5696	65	21	perspectives	perspective	NOUN
cusj-5696	65	22	.	.	PUNCT
cusj-5696	66	1	"bmc	"bmc	PUNCT
cusj-5696	67	1	bioinformatics	bioinformatics	NOUN
cusj-5696	67	2	14.suppl	14.suppl	NUM
cusj-5696	67	3	11	11	NUM
cusj-5696	67	4	(	(	PUNCT
cusj-5696	67	5	2013	2013	NUM
cusj-5696	67	6	):	):	PUNCT
cusj-5696	67	7	s1	s1	PROPN
cusj-5696	67	8	.	.	PUNCT
cusj-5696	67	9	fig	fig	PROPN
cusj-5696	67	10	1	1	NUM
cusj-5696	67	11	.	.	PUNCT
cusj-5696	68	1	cfhmm	cfhmm	NOUN
cusj-5696	68	2	v	v	NUM
cusj-5696	68	3	threshold	threshold	NOUN
cusj-5696	68	4	accuracy	accuracy	NOUN
cusj-5696	68	5	for	for	ADP
cusj-5696	68	6	dominant	dominant	ADJ
cusj-5696	68	7	and	and	CCONJ
cusj-5696	68	8	rare	rare	ADJ
cusj-5696	68	9	clones	clone	NOUN
cusj-5696	68	10	.	.	PUNCT