title: Shimmer: detection of genetic alterations in tumors using next-generation sequence data.
abstract: BACKGROUND
  Extensive DNA sequencing of tumor and matched normal samples using exome and whole-genome sequencing technologies has enabled the discovery of recurrent genetic alterations in cancer cells, but variability in stromal contamination and subclonal heterogeneity still present a severe challenge to available detection algorithms.
  
  
  RESULTS
  Here, we describe publicly available software, Shimmer, which accurately detects somatic single-nucleotide variants using statistical hypothesis testing with multiple testing correction. This program produces somatic single-nucleotide variant predictions with significantly higher sensitivity and accuracy than other available software when run on highly contaminated or heterogeneous samples, and it gives comparable sensitivity and accuracy when run on samples of high purity.
  
  
  BACKGROUND
  http://www.github.com/nhansen/Shimmer
authors.affiliation: Genome Technology Branch, NHGRI/NIH, Bethesda, MD 20892-9400, USA. nhansen@mail.nih.gov
authors.forename: Nancy F
authors.initials: NF
authors.lastname: Hansen
authors.forename: Jared J
authors.initials: JJ
authors.lastname: Gartner
authors.forename: Lan
authors.initials: L
authors.lastname: Mei
authors.forename: Yardena
authors.initials: Y
authors.lastname: Samuels
authors.forename: James C
authors.initials: JC
authors.lastname: Mullikin
mesh_terms: D000465:Algorithms; D045744:Cell Line, Tumor; D004252:DNA Mutational Analysis / Q000379:methods*; D059472:Exome; D014644:Genetic Variation; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods*; D006801:Humans; D009154:Mutation; D009369:Neoplasms / Q000235:genetics*; D012984:Software