Work

ContEst: estimating cross-contamination of human samples in next-generation sequencing data

Year: 2011

Type: article

Abstract: SUMMARY: Here, we present ContEst, a tool for estimating the level of cross-individual contamination in next-generation sequencing data. We demonstrate the accuracy of ContEst across a range of contamination levels, sources and read depths using sequencing data mixed in silico at known concentrations. We applied our tool to published cancer sequencing datasets and report their estimated contamination levels. AVAILABILITY AND IMPLEMENTATION: ContEst is a GATK module, and distributed under a BSD style license at http://www.broadinstitute.org/cancer/cga/contest CONTACT: [email protected]; [email protected] SUPPLEMENTARY INFORMATION: Supplementary data is available at Bioinformatics online.

Source: Bioinformatics

DOI: 10.1093/bioinformatics/btr446

Authors: Kristian Cibulskis, Aaron McKenna, Tim Fennell, Eric Banks, Mark DePristo, Gad Getz

Institution: Broad Institute

Language: English

Topic: Genomics and Phylogenetic Studies

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

SDG: Good health and well-being

Open Access status: green

Funder: National Cancer Institute