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• W2130626344 abstract "Abstract 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. Availability: http://www.github.com/nhansen/Shimmer Contact: nhansen@mail.nih.gov Supplementary information: Supplementary data are available at Bioinformatics online." @default.
• W2130626344 created "2016-06-24" @default.
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• W2130626344 date "2013-04-24" @default.
• W2130626344 modified "2023-10-16" @default.
• W2130626344 title "Shimmer: detection of genetic alterations in tumors using next-generation sequence data" @default.
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• W2130626344 doi "https://doi.org/10.1093/bioinformatics/btt183" @default.
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