Control-free calling of copy number alterations in deep-sequencing data using GC-content normalization

• DOI: 10.1093/bioinformatics/btq635
• Publication Date: 2010-11-17T01:33:59Z
• Authors: Valentina Boeva; Andrei Zinovyev; Kevin Bleakley; Jean-Philippe Vert; Isabelle Janoueix...; Olivier Delattre; Emmanuel Barillot
• Keywords: Normalization

Abstract Summary: We present a tool for control-free copy number alteration (CNA) detection using deep-sequencing data, particularly useful cancer studies. The deals with two frequent problems in the analysis of data: absence control sample and possible polyploidy cells. FREEC (control-FREE Copy caller) automatically normalizes segments profiles (CNPs) calls CNAs. If ploidy is known, assigns absolute to each predicted CNA. To normalize raw CNPs, user can provide dataset if available; otherwise GC content used. demonstrate that Illumina single-end, mate-pair or paired-end sequencing, GC-contentr normalization provides smooth be further segmented analyzed order predict Availability: Source code data are available at http://bioinfo-out.curie.fr/projects/freec/. Contact: [e-mail] Supplementary information: Bioinformatics online.