estimateSignatures {maftools} | R Documentation

## Estimate number of signatures based on cophenetic correlation metric

### Description

Estimate number of signatures based on cophenetic correlation metric

### Usage

    estimateSignatures(
      mat,
      nMin = 2,
      nTry = 6,
      nrun = 10,
      parallel = 4,
      pConstant = NULL,
      verbose = TRUE,
      plotBestFitRes = FALSE
    )

### Arguments

`mat` | Input matrix of diemnsion nx96 generated by `trinucleotideMatrix`
`nMin` | Minimum number of signatures to try. Default 2.
`nTry` | Maximum number of signatures to try. Default 6.
`nrun` | numeric giving the number of run to perform for each value in range. Default 5
`parallel` | Default 4. Number of cores to use.
`pConstant` | A small positive value to add to the matrix. Use it ONLY if the functions throws an `non-conformable arrays` error
`verbose` | Default TRUE
`plotBestFitRes` | plots consensus heatmap for range of values tried. Default FALSE

### 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 `NMF.rank` object and summary stats.

### See Also

`plotCophenetic` `extractSignatures` `trinucleotideMatrix`

### Examples

    ## Not run:
    laml.maf <- system.file("extdata", "tcga_laml.maf.gz", package = "maftools")
    laml <- read.maf(maf = laml.maf)
    laml.tnm <- trinucleotideMatrix(maf = laml, ref_genome = 'BSgenome.Hsapiens.UCSC.hg19', prefix = 'chr',
    add = TRUE, useSyn = TRUE)
    library("NMF")
    laml.sign <- estimateSignatures(mat = laml.tnm, plotBestFitRes = FALSE, nMin = 2, nTry = 3, nrun = 2, pConstant = 0.01)

    ## End(Not run)

[Package maftools version 2.4.12 Index]