Abstract
Allele-specific copy number analysis (ASCN) from next generation sequenc- ing (NGS) data can greatly extend the utility of NGS beyond the iden- tification of mutations to precisely annotate the genome for the detection of homozygous/heterozygous deletions, copy-neutral loss-of-heterozygosity (LOH), allele-specific gains/amplifications. In addition, as targeted gene panels are increasingly used in clinical sequencing studies for the detection of “actionable” mutations and copy number alterations to guide treatment decisions, accurate, tumor purity-, ploidy-, and clonal heterogeneity-adjusted integer copy number calls are greatly needed to more reliably interpret NGS- based cancer gene copy number data in the context of clinical sequencing. We developed FACETS, an ASCN tool and open-source software with a broad application to whole genome, whole-exome, as well as targeted panel sequencing platforms. It is a fully integrated stand-alone pipeline that in- cludes sequencing BAM file post-processing, joint segmentation of total- and allele-specific read counts, and integer copy number calls corrected for tumor purity, ploidy and clonal heterogeneity, with comprehensive output and inte- grated visualization. We demonstrate the application of FACETS using the Cancer Genome Atlas (TCGA) whole-exome sequencing of lung adenocarci- noma samples. We also demonstrate its application to a clinical sequencing platform based on a targeted gene panel.
Disciplines
Biostatistics
Suggested Citation
Shen, Ronglai and Seshan, Venkatraman, "FACETS: Allele-Specific Copy Number and Clonal Heterogeneity Analysis Tool Estimates for High-Throughput DNA Sequencing" (May 2016). Memorial Sloan-Kettering Cancer Center, Dept. of Epidemiology & Biostatistics Working Paper Series. Working Paper 29.
https://biostats.bepress.com/mskccbiostat/paper29