title: PurityEst: estimating purity of human tumor samples using next-generation sequencing data.
abstract: We developed a novel algorithm, PurityEst, to infer the tumor purity level from the allelic differential representation of heterozygous loci with somatic mutations in a human tumor sample with a matched normal tissue using next-generation sequencing data. We applied our tool to a whole cancer genome sequencing datasets and demonstrated the accuracy of PurityEst compared with DNA copy number-based estimation.
  
  
  BACKGROUND
  PurityEst has been implemented in PERL and is available at http://odin.mdacc.tmc.edu/~xsu1/PurityEst.html.
authors: Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. xsu1@mdanderson.org
authors: Xiaoping
authors: X
authors: Su
authors: Li
authors: L
authors: Zhang
authors: Jianping
authors: J
authors: Zhang
authors: Funda
authors: F
authors: Meric-Bernstam
authors: John N
authors: JN
authors: Weinstein
mesh_terms: D000465:Algorithms; D000483:Alleles; D001483:Base Sequence; D006579:Heterozygote; D006801:Humans; D008957:Models, Genetic; D009369:Neoplasms / Q000235:genetics* / Q000473:pathology*; D017422:Sequence Analysis, DNA / Q000379:methods*