Shimmer: detection of genetic alterations in tumors using next-generation sequence data

Bioinformatics. 2013 Jun 15;29(12):1498-503. doi: 10.1093/bioinformatics/btt183. Epub 2013 Apr 24.


Motivation: 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.


Publication types

  • Research Support, N.I.H., Intramural

MeSH terms

  • Algorithms
  • Cell Line, Tumor
  • DNA Mutational Analysis / methods*
  • Exome
  • Genetic Variation
  • High-Throughput Nucleotide Sequencing / methods*
  • Humans
  • Mutation
  • Neoplasms / genetics*
  • Software*