processMultipleSigSets: processMultipleSigSets (internal function)

In decompTumor2Sig: Decomposition of individual tumors into mutational signatures by signature refitting

Description

Performs the quadratic programming/exposure prediction for multiple subsets (of size k) of mutational signatures and returns information on the best subset (highest explained variance). This function is used by getBestDecomp4Ksignatures and addBestSignatureToSubset.

Usage

processMultipleSigSets(genome, signatures, sigCombn, k,
constrainToMaxContribution=FALSE, tolerance=0.1)

Arguments

genome	Genome for which to approximate the decomposition.
signatures	The whole set of signatures (from which to choose a subset signatures.
sigCombn	The combinations of subsets of k signatures to use. Has to be the same format as generated by combn.
k	Number of signatures to use (subset size).
constrainToMaxContribution	(Optional) [Note: this is experimental and is usually not needed!] If TRUE, the maximum contribution that can be attributed to a signature will be constraint by the variant feature counts (e.g., specific flanking bases) observed in the individual tumor genome. If, for example, 30% of all observed variants have a specific feature and 60% of the variants produced by a mutational process/signature will manifest the feature, then the signature can have contributed up to 0.3/0.6 (=0.5 or 50%) of the observed variants. The lowest possible contribution over all signature features will be taken as the allowed maximum contribution of the signature. This allowed maximum will additionally be increased by the value specified as tolerance (see below). For the illustrated example and tolerance=0.1 a contribution of up to 0.5+0.1 = 0.6 (or 60%) of the signature would be allowed.
tolerance	(Optional) If constrainToMaxContribution is TRUE, the maximum contribution computed for a signature is increased by this value (see above). If the parameter constrainToMaxContribution is FALSE, the tolerance value is ignored. Default: 0.1.

Value

A list object containing: k=number of signatures; explVar=variance explained by these signatures; sigList=list of the signatures; decomposition=decomposition (exposures) obtained with these signatures.

Author(s)

Rosario M. Piro
Politecnico di Milano
Maintainer: Rosario M. Piro
E-Mail: <[e-mail]> or <[e-mail]>

References

http://rmpiro.net/decompTumor2Sig/
Krueger, Piro (2019) decompTumor2Sig: Identification of mutational signatures active in individual tumors. BMC Bioinformatics 20(Suppl 4):152.

decompTumor2Sig documentation built on Nov. 8, 2020, 8:23 p.m.