extractSignatures {maftools} | R Documentation

## Extract mutational signatures from trinucleotide context.

### Description

Decompose a matrix of 96 substitution classes into `n` signatures.

### Usage

    extractSignatures(mat, n = NULL, nTry = 6, plotBestFitRes = FALSE,
      parallel = NULL)

### Arguments

`mat` | Input matrix of diemnsion nx96 generated by `trinucleotideMatrix`
`n` | decompose matrix into n signatures. Default NULL. Tries to predict best value for `n` by running NMF on a range of values and chooses based on cophenetic correlation coefficient.
`nTry` | tries upto this number of signatures before choosing best `n`. Default 6.
`plotBestFitRes` | plots consensus heatmap for range of values tried. Default FALSE
`parallel` | calls to .opt argument of `nmf`. e.g, 'P4' for using 4 cores. See note on `nmf` for MAC users.

### Details

This function decomposes a non-negative matrix into n signatures. Extracted signatures are compared against 30 experimentally validated signatures by calculating cosine similarity. See http://cancer.sanger.ac.uk/cosmic/signatures for details.

### Value

a list with decomposed scaled signatures, signature contributions in each sample and a cosine similarity table against validated signatures.

### See Also

`trinucleotideMatrix` `plotSignatures`

### Examples

    ## Not run:
    laml.tnm <- trinucleotideMatrix(maf = laml, ref_genome = 'hg19.fa', prefix = 'chr',
    add = TRUE, useSyn = TRUE)
    laml.sign <- extractSignatures(mat = laml.tnm, plotBestFitRes = FALSE)

    ## End(Not run)

[Package maftools version 1.6.15 Index]