Decipher Mutational Signatures from Somatic Mutational Catalogs
Add Weak Mutation TYpes
Perform Non-negative Matrix Factorization using Brunet's Algotithm.
Convert a mutationCounts object to data.frame.
Convert a mutationSignatures object to data.frame.
Convert and/or transpose a mutSignExposures object to data.frame.
Convert a mutationSignatures object to list.
Convert a mutFrameworkParams object to list.
Convert a mutationCounts object to matrix.
Method as.mutation.counts.
Method as.mutation.signatures.
Method as.mutsign.exposures.
Attach Nucleotide Context.
Attach Mutation Types.
Bootstrap a Mutation Count Matrix.
Combine two mutationSignatures-class objects.
Perform Non-negative Matrix Factorization using Chih-Jen Lin's Algotit...
Method coerceObj.
Count Mutation Types.
Custom CSSLS.
Custom Fast Combinatorial Nonnegative Least-Square.
Decipher Mutational Processes Contributing to a Collection of Genomic ...
Deconvolute Mutation Counts.
Evaluate Results Stability.
Extract Signatures from Genomic Mutational Catalogs.
Extract Variants from XvarlinkData.
Remove Iterations that Generated Outlier Results.
Filter Single Nucleotide Variants.
Convert Mutation COunts to PerMille Frequencies.
Obtain COSMIC mutational Signatures.
Method getCounts.
Method getFwkParam.
Method getMutationTypes.
Method getSampleIdentifiers.
Method getSignatureIdentifiers.
Generate Arguments for Running Examples and Mock Runs.
Import Mutation data from VCF files.
Add Leading Zeros to Numbers.
Match Mutational Signatures.
Method msigPlot.
Class mutationCounts.
Show method of the mutationCounts Class.
Class mutationSignatures.
Show method of the mutationSignatures Class.
Class mutFrameworkParams.
Show method of the mutFrameworkParams Class.
Decipher Mutational Signatures from Somatic Mutational Catalogs.
Class mutSignExposures.
Show method of the mutSignExposures Class.
Plot Mutation Signature Profiles.
Plot Signature Exposure Profiles.
Run a Preliminary Process Assess analysis.
Process VCF data.
Remove Mismatched Mutations.
Remove Mutation Types Not Meeting the Threshold.
Resolve Mutation Signatures.
Compute Reverse Complement sequences.
Method setFwkParam.
Set Parameters for Extracting Mutational Signatures.
Silhouette Analysis.
Simplify Mutational Signatures.
Sort Data by Mutation Type.
Subset a mutationCounts-class object.
Subset a mutationSignatures-class object.
Subset a mutSignExposures-class object.
Table Mutation Types by Sample.
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 framework includes modules that support raw data import and processing, mutational signature extraction, and results interpretation and visualization. The framework accepts widely used file formats storing information about DNA variants, such as Variant Call Format files. The framework performs Non-Negative Matrix Factorization to extract mutational signatures explaining the observed set of DNA mutations. Bootstrapping is performed as part of the analysis. The framework supports parallelization and is optimized for use on multi-core systems. The software was described by Fantini D et al (2020) <doi:10.1038/s41598-020-75062-0> and is based on a custom R-based implementation of the original MATLAB WTSI framework by Alexandrov LB et al (2013) <doi:10.1016/j.celrep.2012.12.008>.