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  2. High-throughput sequencing
  3. Whole-genome sequencing
  4. Somatic SNV detection
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A software package for calling single nucleotide variants (SNVs) using NGS data from multiple same-patient samples. Instead of performing multiple pairwise analyses of a single tumour sample and a matched normal, multiSNV jointly considers all available samples under a Bayesian framework to increase sensitivity of calling shared SNVs. By leveraging information from all available samples, multiSNV is able to detect rare mutations with variant allele frequencies down to 3% from whole-exome sequencing experiments.

Software type:
Package
Interface:
Command line interface
Restrictions to use:
None
Input format:
Pileup
Output format:
VCF
Operating system:
Unix/Linux
Computer skills:
Advanced
Stability:
Stable
Requirements:
R (latest version), R packages (Rcpp, RInside and inline), Git, cmake, Boost, compile libraries
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Maintainer

  • Malvina Josephidou <malvina.josephidou at cruk.cam.ac.uk>

Institution(s)

Cancer Research UK Cambridge Institute, Li Ka Shing Centre, Robinson Way, Cambridge CB2 0RE, UK

  • (Josephidou et al., 2015) multiSNV: a probabilistic approach for improving detection of somatic point mutations from multiple related tumour samples. Nucleic acids research.
    PMID: 25722372
  • (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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