bioconductor-deepsnv
Detection of subclonal SNVs in deep sequencing data.
Detection of subclonal SNVs in deep sequencing data.
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This package provides provides quantitative variant callers for detecting subclonal mutations in ultra-deep (>=100x coverage) sequencing experiments. The deepSNV algorithm is used for a comparative setup with a control experiment of the same loci and uses a beta-binomial model and a likelihood ratio test to discriminate sequencing errors and subclonal SNVs. The shearwater algorithm computes a Bayes classifier based on a beta-binomial model for variant calling with multiple samples for precisely estimating model parameters - such as local error rates and dispersion - and prior knowledge, e.g. from variation data bases such as COSMIC.
Summary
Detection of subclonal SNVs in deep sequencing data.
Last Updated
Dec 24, 2024 at 20:02
License
GPL-3
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