Learn R Programming

⚠️There's a newer version (2.1.1) of this package.Take me there.

mutSignatures (version 1.2)

Decipher Mutational Signatures from Somatic Mutational Catalogs

Description

Cancer cells accumulate DNA mutations as result of DNA damage and DNA repair processes. This computational framework is aimed at deciphering DNA mutational signatures operating in cancer. The input is a numeric matrix of DNA mutation counts detected in a panel of cancer samples. The framework performs Non-negative Matrix Factorization to extract the most likely signatures explaining the observed set of DNA mutations. The framework relies on parallelization and is optimized for use on multi-core systems. This framework is an R-based implementation of the original MATLAB WTSI framework by Alexandrov LB et al (2013) .

Copy Link

Version

Install

install.packages('mutSignatures')

Monthly Downloads

510

Version

1.2

License

GPL-2

Maintainer

Damiano Fantini

Last Published

January 24th, 2017

Functions in mutSignatures (1.2)

evaluateStability

Evaluate Results Stability
getTestRunArgs

Generate Arguments for Running Examples and Mock Runs
decipherMutationalProcesses

Decipher Mutational Processes Contributing to a Collection of Genomic Mutations
setMutClusterParams

Set Parameters for Extracting Mutational Signatures
removeWeak

Remove Mutation Types Not Meeting the Threshold
setMutCountObject

Create a Mutation Count Object Suitable for Signatures Extraction
leadZeros

Add Leading Zeros to a Number
plotSignatureExposures

Generate Plot Signature
mutSignatures-package

Computational Framework for Deciphering Cancer Mutational Signatures
silhouetteMLB

Silhouette Analysis
extractSignatures

Extract Signatures from Genomic Mutational Catalogs
filterOutIterations

Remove Iterations that Generated Outlier Results
citation

Print Citation Information
bootstrapCancerGenomes

Bootstrap a Mutation Count Matrix
addWeak

Add Weak Mutation Types
deconvoluteMutCounts

Deconvolute Mutation Counts
do.nmf

Perform Non-negative Matrix Factorization