discover_signatures {musicatk} | R Documentation

## Discover mutational signatures

### Description

Mutational signatures and exposures will be discovered using methods such as Latent Dirichlet Allocation (lda) or Non-Negative Matrix Factorization (nmf). These algorithms will deconvolute a matrix of counts for mutation types in each sample to two matrices: 1) a "signature" matrix containing the probability of each mutation type in each sample and 2) an "exposure" matrix containing the estimated counts for each signature in each sample. Before mutational discovery can be performed, variants from samples first need to be stored in a `musica` object using the create_musica function and mutation count tables need to be created using functions such as build_standard_table.

### Usage

    discover_signatures(
      musica,
      table_name,
      num_signatures,
      algorithm = "lda",
      seed = 1,
      nstart = 10,
      par_cores = 1
    )

### Arguments

`musica` | A `musica` object.
`table_name` | Name of the table to use for signature discovery. Needs to be the same name supplied to the table building functions such as build_standard_table.
`num_signatures` | Number of signatures to discover.
`algorithm` | Method to use for mutational signature discovery. One of `"lda"` or `"nmf"`. Default `"lda"`.
`seed` | Seed to be used for the random number generators in the signature discovery algorithms. Default `1`.
`nstart` | Number of independent random starts used in the mutational signature algorithms. Default `10`.
`par_cores` | Number of parallel cores to use. Only used if `method = "nmf"`. Default `1`.

### Value

Returns a A `musica_result` object containing signatures and exposures.

### Examples

    data(musica)
    g <- select_genome("19")
    build_standard_table(musica, g, "SBS96", overwrite = TRUE)
    discover_signatures(musica = musica, table_name = "SBS96",
    num_signatures = 3, algorithm = "lda", seed = 12345, nstart = 1)

[Package musicatk version 1.2.0 Index]