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A computational method combining the patient-matched normal and tumor DNA with the tumor RNA to detect somatic mutations. The inclusion of the RNA increases the power to detect somatic mutations, especially at low DNA allelic frequencies.

Software type:
Command line interface
Restrictions to use:
Academic users only
Input data:
Sequence data
Input format:
Output data:
Variant calls
Output format:
Operating system:
Programming languages:
Computer skills:
python (version 2.7), samtools (version 0.1.18), pysam API (version 0.7.5), BLAT, SnpEff (version 3.3)
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  • Amie J. Radenbaugh <aradenba at soe.ucsc.edu>


University of California Santa Cruz Genomics Institute, Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, California, United States of America

  • (Radenbaugh et al., 2014) RADIA: RNA and DNA integrated analysis for somatic mutation detection. PloS one.
    PMID: 25405470
  • (Spencer et al., 2014) Performance of common analysis methods for detecting low-frequency single nucleotide variants in targeted next-generation sequence data. The Journal of molecular diagnostics.
    PMID: 24211364
  • (Stead et al., 2013) Accurately identifying low-allelic fraction variants in single samples with next-generation sequencing: applications in tumor subclone resolution. Human mutation.
    PMID: 23766071
  • (Roberts et al., 2013) A comparative analysis of algorithms for somatic SNV detection in cancer. Bioinformatics.
    PMID: 23842810
  • (Wang et al., 2013) Detecting somatic point mutations in cancer genome sequencing data: a comparison of mutation callers. Genome medicine.
    PMID: 24112718

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