HATCHet2: clone- and haplotype-specific copy number inference from bulk tumor sequencing data

Matthew A. Myers; Brian J. Arnold; Vineet Bansal; Metin Balaban; Katelyn M. Mullen; Simone Zaccaria; Benjamin J. Raphael

doi:10.1186/s13059-024-03267-x

HATCHet2: clone- and haplotype-specific copy number inference from bulk tumor sequencing data

Matthew A. Myers, Brian J. Arnold, Vineet Bansal, Metin Balaban, Katelyn M. Mullen, Simone Zaccaria, Benjamin J. Raphael

Research output: Contribution to journal › Article › peer-review

Abstract

Bulk DNA sequencing of multiple samples from the same tumor is becoming common, yet most methods to infer copy-number aberrations (CNAs) from this data analyze individual samples independently. We introduce HATCHet2, an algorithm to identify haplotype- and clone-specific CNAs simultaneously from multiple bulk samples. HATCHet2 extends the earlier HATCHet method by improving identification of focal CNAs and introducing a novel statistic, the minor haplotype B-allele frequency (mhBAF), that enables identification of mirrored-subclonal CNAs. We demonstrate HATCHet2’s improved accuracy using simulations and a single-cell sequencing dataset. HATCHet2 analysis of 10 prostate cancer patients reveals previously unreported mirrored-subclonal CNAs affecting cancer genes.

Original language	American English
Article number	130
Journal	Genome biology
Volume	25
Issue number	1
DOIs	https://doi.org/10.1186/s13059-024-03267-x
State	Published - Dec 2024
Externally published	Yes

ASJC Scopus subject areas

Ecology, Evolution, Behavior and Systematics
Genetics
Cell Biology

Keywords

Allele-specific
Cancer
Clone
Copy-number aberrations
DNA sequencing
Genomics
Haplotype
Tumor heterogeneity

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10.1186/s13059-024-03267-x

Cite this

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title = "HATCHet2: clone- and haplotype-specific copy number inference from bulk tumor sequencing data",

abstract = "Bulk DNA sequencing of multiple samples from the same tumor is becoming common, yet most methods to infer copy-number aberrations (CNAs) from this data analyze individual samples independently. We introduce HATCHet2, an algorithm to identify haplotype- and clone-specific CNAs simultaneously from multiple bulk samples. HATCHet2 extends the earlier HATCHet method by improving identification of focal CNAs and introducing a novel statistic, the minor haplotype B-allele frequency (mhBAF), that enables identification of mirrored-subclonal CNAs. We demonstrate HATCHet2{\textquoteright}s improved accuracy using simulations and a single-cell sequencing dataset. HATCHet2 analysis of 10 prostate cancer patients reveals previously unreported mirrored-subclonal CNAs affecting cancer genes.",

keywords = "Allele-specific, Cancer, Clone, Copy-number aberrations, DNA sequencing, Genomics, Haplotype, Tumor heterogeneity",

author = "Myers, {Matthew A.} and Arnold, {Brian J.} and Vineet Bansal and Metin Balaban and Mullen, {Katelyn M.} and Simone Zaccaria and Raphael, {Benjamin J.}",

note = "Publisher Copyright: {\textcopyright} The Author(s) 2024.",

year = "2024",

month = dec,

doi = "10.1186/s13059-024-03267-x",

language = "American English",

volume = "25",

journal = "Genome biology",

issn = "1474-7596",

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T2 - clone- and haplotype-specific copy number inference from bulk tumor sequencing data

AU - Myers, Matthew A.

AU - Arnold, Brian J.

AU - Bansal, Vineet

AU - Balaban, Metin

AU - Mullen, Katelyn M.

AU - Zaccaria, Simone

AU - Raphael, Benjamin J.

N1 - Publisher Copyright: © The Author(s) 2024.

PY - 2024/12

Y1 - 2024/12

N2 - Bulk DNA sequencing of multiple samples from the same tumor is becoming common, yet most methods to infer copy-number aberrations (CNAs) from this data analyze individual samples independently. We introduce HATCHet2, an algorithm to identify haplotype- and clone-specific CNAs simultaneously from multiple bulk samples. HATCHet2 extends the earlier HATCHet method by improving identification of focal CNAs and introducing a novel statistic, the minor haplotype B-allele frequency (mhBAF), that enables identification of mirrored-subclonal CNAs. We demonstrate HATCHet2’s improved accuracy using simulations and a single-cell sequencing dataset. HATCHet2 analysis of 10 prostate cancer patients reveals previously unreported mirrored-subclonal CNAs affecting cancer genes.

AB - Bulk DNA sequencing of multiple samples from the same tumor is becoming common, yet most methods to infer copy-number aberrations (CNAs) from this data analyze individual samples independently. We introduce HATCHet2, an algorithm to identify haplotype- and clone-specific CNAs simultaneously from multiple bulk samples. HATCHet2 extends the earlier HATCHet method by improving identification of focal CNAs and introducing a novel statistic, the minor haplotype B-allele frequency (mhBAF), that enables identification of mirrored-subclonal CNAs. We demonstrate HATCHet2’s improved accuracy using simulations and a single-cell sequencing dataset. HATCHet2 analysis of 10 prostate cancer patients reveals previously unreported mirrored-subclonal CNAs affecting cancer genes.

KW - Allele-specific

KW - Cancer

KW - Clone

KW - Copy-number aberrations

KW - DNA sequencing

KW - Genomics

KW - Haplotype

KW - Tumor heterogeneity

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SN - 1474-7596

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JO - Genome biology

JF - Genome biology

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M1 - 130

ER -

HATCHet2: clone- and haplotype-specific copy number inference from bulk tumor sequencing data

Abstract

ASJC Scopus subject areas

Keywords

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