title: ContEst: estimating cross-contamination of human samples in next-generation sequencing data.
abstract: CONCLUSIONS
  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.
  
  
  METHODS
  ContEst is a GATK module, and distributed under a BSD style license at http://www.broadinstitute.org/cancer/cga/contest
  
  
  BACKGROUND
  kcibul@broadinstitute.org; gadgetz@broadinstitute.org
  
  
  BACKGROUND
  Supplementary data is available at Bioinformatics online.
authors.affiliation: Genome Sequencing Analysis Program and Platform, Broad Institute, 7 Cambridge Center, Cambridge, MA 02142, USA. kcibul@broadinstitute.org
authors.forename: Kristian
authors.initials: K
authors.lastname: Cibulskis
authors.forename: Aaron
authors.initials: A
authors.lastname: McKenna
authors.forename: Tim
authors.initials: T
authors.lastname: Fennell
authors.forename: Eric
authors.initials: E
authors.lastname: Banks
authors.forename: Mark
authors.initials: M
authors.lastname: DePristo
authors.forename: Gad
authors.initials: G
authors.lastname: Getz
mesh_terms: D001483:Base Sequence; D001499:Bayes Theorem; D005189:False Positive Reactions; D005838:Genotype; D006801:Humans; D008957:Models, Genetic; D009369:Neoplasms / Q000235:genetics*; D017422:Sequence Analysis, DNA / Q000379:methods*; D012984:Software