Decompose a matrix of 96 substitution classes into `n`

signatures.

1 2 | ```
extractSignatures(mat, n = NULL, nTry = 6, plotBestFitRes = FALSE,
parallel = NULL)
``` |

`mat` |
Input matrix of diemnsion nx96 generated by |

`n` |
decompose matrix into n signatures. Default NULL. Tries to predict best value for |

`nTry` |
tries upto this number of signatures before choosing best |

`plotBestFitRes` |
plots consensus heatmap for range of values tried. Default FALSE |

`parallel` |
calls to .opt argument of |

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.

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

`trinucleotideMatrix`

`plotSignatures`

1 2 3 4 5 6 | ```
## 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)
``` |

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