Abstract
Motivation Large somatic copy number alterations (CNA), short indels and single nucleotide variants (SNVs) are playing important role in cancer development and can serve as a predictor for targeted therapy selection as well as prognostic factor. Genomic microarrays, FISH, MLPA and many other technologies are widely used for detection of CNAs. Whole-genome sequencing (WGS), whole-exome sequencing (WES) and targeted panel sequencing (TPS) are well established, highly accurate tools for detection of SNVs and small indels, but detection of larger structural variants using WGS, WES and TPS data remains challenging. We developed a tool for high-resolution allele-specific detection of somatic CNAs in NGS data using statistical approach.
Results We have developed a new method for read-depth and B-allele frequency (BAF) based multi-sample detection of copy-number changes in paired normal-tumor NGS data and showed its performance using large cohorts of WES and TPS sequenced samples.
Availability ClinCNV is freely available on https://github.com/imgag/ClinCNV.
Footnotes
stephan.ossowski{at}med.uni-tuebingen.de
