Haplotype-aware segmentation with HapASeg increases accuracy of detecting homolog-specific somatic copy number alterations

Somatic copy number alterations (sCNAs) drive cancer initiation, progression, resistance, and metastasis. Furthering our understanding of sCNAs requires substantially larger cohorts. Most tumors available for sequencing are preserved with formalin-fixed, paraffin-embedding (FFPE), which causes DNA cross-linking that distorts coverage profiles and challenges current sCNA estimation methods. Traditional methods denoise data using large panels of similar normal samples, which are impractical to obtain for FFPE cohorts. Here, HapASeg overcomes this limitation by leveraging haplotype phasing and unique covariates to accurately estimate sCNA segments across FFPE, fresh frozen, whole genome sequencing and whole exome sequencing sample types, outperforming current methods without requiring panel-of-normal correction.

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Publication Details

Journal
Genome biology
Published
2026-02-14
DOI
https://doi.org/10.1186/s13059-026-03971-w
Primary Topic
Cancer Genomics and Diagnostics
Type
article
Field-Weighted Citation Impact
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article

Haplotype-aware segmentation with HapASeg increases accuracy of detecting homolog-specific somatic copy number alterations

Oliver Priebe, Julian Hess, Conor Messer, Ron Solan et al.
Genome biology
Cancer Genomics and Diagnostics
article

Haplotype-aware segmentation with HapASeg increases accuracy of detecting homolog-specific somatic copy number alterations

Oliver Priebe, Julian Hess, Conor Messer, Ron Solan, Claudia Chu
article en

Abstract

Somatic copy number alterations (sCNAs) drive cancer initiation, progression, resistance, and metastasis. Furthering our understanding of sCNAs requires substantially larger cohorts. Most tumors available for sequencing are preserved with formalin-fixed, paraffin-embedding (FFPE), which causes DNA cross-linking that distorts coverage profiles and challenges current sCNA estimation methods. Traditional methods denoise data using large panels of similar normal samples, which are impractical to obtain for FFPE cohorts. Here, HapASeg overcomes this limitation by leveraging haplotype phasing and unique covariates to accurately estimate sCNA segments across FFPE, fresh frozen, whole genome sequencing and whole exome sequencing sample types, outperforming current methods without requiring panel-of-normal correction.

Genome biologyVol. 27(1)
Broad Institute (US), Harvard University Press (US), Profectus Biosciences (United States) (US), Center for Cancer Research (US), Massachusetts Institute of Technology (US), Stanford University (US)
Openalex Percentile: Top 58%
Cancer Genomics and Diagnostics
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Haplotype-aware segmentation with HapASeg increases accuracy of detecting homolog-specific somatic copy number alterations — Oliver Priebe, Julian Hess, et al. · Genome biology (2026) | TGRS Research Map | TGRS