Year: 2017
Type: preprint
Abstract: VCF2CNA is a web interface tool for copy-number alteration (CNA) analysis of VCF and other variant file formats. We applied it to 46 adult glioblastoma and 146 pediatric neuroblastoma samples sequenced by Illumina and Complete Genomics (CGI) platforms respectively. VCF2CNA was highly consistent with a state-of-the-art algorithm using raw sequencing data (mean F1-score=0.994) in high-quality glioblastoma samples and was robust to uneven coverage introduced by library artifacts. In the neuroblastoma set, VCF2CNA identified MYCN high-level amplifications in 31 of 32 clinically validated samples compared to 15 found by CGI’s HMM-based CNA model. The findings suggest that VCF2CNA is an accurate, efficient and platform-independent tool for CNA analyses without accessing raw sequence data.
DOI: 10.1101/131235
Authors: Daniel K. Putnam, Ma Xiaotu, Stephen V. Rice, Yu Liu, Jinghui Zhang, Xiang Chen
Institution: St. Jude Children's Research Hospital
Language: English
Subfield: Genetics
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W2610833998