ACEseq - allele specific copy number estimation from whole genome sequencing
Kortine KleinheinziD, Isabell BludauiD, Daniel HübschmanniD, Michael C. Heinold, Philip Reiner KenscheiD, Zuguang GuiD, Cristina LópeziD, Michael HummeliD, Wolfram KlapperiD, Peter Loof MølleriD, Inga Vater, Rabea WageneriD, ICGC MMML-Seq project, Benedikt BrorsiD, Reiner SiebertiD, Roland EilsiD, Matthias SchlesneriD
Abstract
ACEseq is a computational tool for allele-specific copy number estimation in tumor genomes based on whole genome sequencing. In contrast to other tools it features GC-bias correction, unique replication timing-bias correction and integration of structural variant (SV) breakpoints for improved genome segmentation. ACEseq clearly outperforms widely used state-of-the art methods, provides a fully automated estimation of tumor cell content and ploidy, and additionally computes homologous recombination deficiency scores.
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Abstract summary
Claude Opus 5.5 · xhigh effort · 2 Nov 2026 · from the abstract · CC BY-NC 4.0
ACEseq estimates allele-specific copy numbers, tumor purity, ploidy, and homologous recombination deficiency scores from tumor whole-genome sequencing by combining GC-bias correction, replication-timing correction, and structural variant breakpoints.
Existing computational tools for estimating allele-specific copy number from tumor whole-genome sequencing do not jointly correct for both GC-content and replication-timing biases while integrating structural variant (SV) breakpoints into genome segmentation. ACEseq combines these three features to automate allele-specific copy number calling, tumor cell content and ploidy estimation, and homologous recombination deficiency scoring.
Key results
ClaimedACEseq integrates GC-bias correction, replication-timing-bias correction, and structural variant breakpoints to improve genome segmentation and outperform existing allele-specific copy number estimation methods on tumor whole-genome sequencing data.
Qualitative comparison against existing methods; benchmark datasets, comparator tool names, and quantitative performance metrics are not provided in the abstract. · Abstract
ClaimedACEseq automatically estimates tumor cell content (purity) and ploidy and calculates homologous recombination deficiency (HRD) scores from whole-genome sequencing.
Feature description in the abstract; no quantitative validation statistics are reported in the abstract. · Abstract
Methods, data and reproducibility
ACEseq processes tumor whole-genome sequencing data by applying GC-bias correction and replication-timing-bias correction and incorporating structural variant (SV) breakpoints into genome segmentation. From the segmented allele-specific copy number profiles, it automatically estimates tumor cell content and ploidy and computes homologous recombination deficiency scores.
- Methods & tools
- ACEseq
- Reproducibility gaps
- Software repository URL, benchmark datasets, and runtime requirements are not provided in the abstract.
Limitations (1)
- Abstract only; benchmark datasets, comparator tools, quantitative accuracy metrics, and software availability URLs are not reported. · noted in this summary
Who should read:Read this if you analyze tumor whole-genome sequencing data and need automated allele-specific copy number calling, purity/ploidy estimation, and homologous recombination deficiency scoring.
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