addBestSignatureToSubset {decompTumor2Sig} | R Documentation

## addBestSignatureToSubset (internal function)

### Description

Add the best signature to an existing subset (highest increase in expl. var.) to improve the approximate decomposition of a genome.

### Usage

    addBestSignatureToSubset(genome, signatures, subset,
    constrainToMaxContribution=FALSE, tolerance=0.1)

### Arguments

`genome` | Genome for which to improve the decomposition.
`signatures` | The whole set of signatures (from which to choose additional signatures.
`subset` | The current subset that is used for decomposition.
`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: <rmpiro@gmail.com> or <rosariomichael.piro@polimi.it>

### References

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

[Package decompTumor2Sig version 2.10.0 Index]