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

Abstract

Multi-region DNA sequencing of primary tumors and metastases from individual patients helps identify somatic aberrations driving cancer development. However, most methods to infer copy-number aberrations (CNAs) analyze individual samples. We introduce HATCHet2 to identify haplotype- and clone-specific CNAs simultaneously from multiple bulk samples. HATCHet2 introduces a novel statistic, the mirrored haplotype B-allele frequency (mhBAF), to identify mirrored-subclonal CNAs having different numbers of copies of parental haplotypes in different tumor clones. HATCHet2 also has high accuracy in identifying focal CNAs and extends the earlier HATCHet method in several directions. We demonstrate HATCHet2's improved accuracy using simulations and a single-cell sequencing dataset. HATCHet2 analysis of 50 prostate cancer samples from 10 patients reveals previously-unreported mirrored-subclonal CNAs affecting cancer genes.

Karyotype Evolution in Response to Chemoradiotherapy and Upon Recurrence of Esophageal Adenocarcinomas

“…By leveraging information from high-purity samples from the same tumor we could improve the inference accuracy of low-purity samples compared to single-sample inference techniques. Inference of absolute CNA is notoriously difficult (28), and previous methods have been developed that leverage the full information from multiple samples of a tumor to determine absolute CNAs (29, 30). We designed L-PAC specifically to improve the inference of absolute CNAs for low-purity samples.…”

Performance comparison of Accucopy, Sequenza, and ControlFreeC

“…Accucopy can only tell if a segment is subclonal or not, but can infer neither the number of subclones nor the genotypes in all subclones, while ControlFreeC and Sequenza do not consider subclones. Many algorithms [27][28][29][30][31][32] have been proposed to tackle the problem of inferring the number of subclones and genotypes of subclonal segments.…”