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deepSNV | Detection of subclonal single-nucleotide variants in tumour cell populations

Provides quantitative variant callers for detecting subclonal mutations in ultra-deep sequencing experiments. DeepSNV is a comparative targeted deep-sequencing approach combined with a customised statistical algorithm, which can detect and quantify subclonal single-nucleotide variants (SNVs) in mixed populations. The deepSNV algorithm is used for a comparative setup with a control experiment of the same loci and the shearwater algorithm computes a Bayes classifier based on a beta-binomial model for variant calling with multiple samples for precisely estimating model parameters.

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deepSNV classification

deepSNV specifications

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GNU General Public License version 2.0
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deepSNV support



  • Moritz Gerstung <>


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Cancer Genome Project, Wellcome Trust Sanger Institute, Hinxton, UK; Department of Haematology, Addenbrooke's Hospital, Cambridge, UK; Department of Haematology, University of Cambridge, Cambridge, UK

Funding source(s)

Supported by a Specialized Center of Research grant from the Leukemia Lymphoma Society (LLS), the Kay Kendall Leukaemia Fund, the Wellcome Trust (grant reference 077012/Z/05/Z) and a Wellcome Trust Senior Clinical Research Fellowship (grant reference WT088340MA).

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