Published December 21, 2021 | Version 0.1
Journal article Open

Achieving robust somatic mutation detection with deep learning models derived from reference data sets of a cancer sample

Authors/Creators

  • 1. Roche Sequencing Solutions, Santa Clara, CA, 95050, USA
  • 2. The Center for Biologics Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, MD, USA
  • 3. National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA
  • 4. Office of Oncological Diseases, Office of New Drug, Center for Drug Evaluation and Research, Food and Drug Administration, 10903 New Hampshire Avenue, Silver Spring, MD 20993
  • 5. Bioinformatics branch, Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, Food and Drug Administration, 3900 NCTR Road, Jefferson, AR 72079
  • 6. Office of Oncological Diseases, Office of New Drug, Center for Drug Evaluation and Research, Food and Drug Administration, 10903 New Hampshire Avenue, Silver Spring, MD 20993;

Description

Information about the scripts and data used in this study:

Sahraeian SME, et al., Achieving Robust Somatic Mutation Detection with Deep Learning Models Derived from Reference Data Sets of a Cancer Sample, Genome Biology, 2022.

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