1. Directory
  2. Genomics
  3. Genome annotation
  4. Repetitive DNA
Join community Sign in
By using OMICtools you acknowledge that you have read and accepted the terms of the end user license agreement.

Implement a likelihood-based framework for calling single nucleotide variants and detecting de novo point mutation events in families for next-generation sequencing data. In addition to facilitating detection and genotyping of SNPs, Polymutt can interface with existing tools to improve the accuracy of more challenging short insertion deletion polymorphisms and other types of variants. Polymutt should make studies of families even more attractive because, in addition to making it easy to study rare variants and de novo mutation events, family studies will now be able to better transform sequence data into accurate genotypes.

Software type:
Command line interface
Restrictions to use:
Input format:
Output data:
Variant calls
Output format:
Operating system:
Computer skills:
Polymutt version 0.18
View all reviews

0 user review

No review has been posted.

View all issues

0 issue

No open issue.


  • Bingshan Li <bingshan at umich.edu>


Center for Human Genetics Research, Department of Physiology and Biophysics, Vanderbilt University, Nashville, Tennessee, United States of America; Department of Pediatrics, Children’s Hospital of Pittsburgh, Pittsburgh, Pennsylvania, United States of America; Center for Statistical Genetics, Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America; Istituto di Ricerca Genetica e Biomedica, Consiglio Nazionale delle Ricerche (CNR), Monserrato, Italy

  • (Li et al., 2012) A likelihood-based framework for variant calling and de novo mutation detection in families. PLoS genetics.
    PMID: 23055937
  • (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