1. Directory
  2. High-throughput sequencing
  3. Whole-genome sequencing
  4. Somatic SNV detection
Join community Sign in
By using OMICtools you acknowledge that you have read and accepted the terms of the end user license agreement.

A software tool for analyzing de novo mutations from familial and somatic tissue sequencing data. DeNovoGear uses likelihood-based error modeling to reduce the false positive rate of mutation discovery in exome analysis and fragment information to identify the parental origin of germ-line mutations.

Software type:
Package
Interface:
Command line interface
Restrictions to use:
None
Operating system:
Unix/Linux
Programming languages:
C++
License:
GNU General Public License version 2.0
Computer skills:
Advanced
Version:
DeNovoGear version 1.1.1
Stability:
Stable
View all reviews

0 user review

No review has been posted.

View all issues

0 issue

No open issue.

Institution(s)

Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, USA; Center for Evolutionary Medicine and Informatics, The Biodesign Institute, Arizona State University, Tempe, Arizona, USA; Genome Mutation and Genetic Disease Group, Wellcome Trust Sanger Institute, Cambridge, UK; School of Life Sciences, Arizona State University, Tempe, Arizona, USA; Department of Pathology & Immunology, Washington University School of Medicine, St. Louis, Missouri, USA

  • (Ramu et al., 2013) DeNovoGear: de novo indel and point mutation discovery and phasing. Nature methods.
    PMID: 23975140
  • (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

33 related tools