signature_potential_damage_analysis {MutationalPatterns} | R Documentation

## Potential damage analysis for the supplied mutational signatures

### Description

The ratio of possible 'stop gain', 'mismatches', 'synonymous mutations' and 'splice site mutations' is counted per signature. Normalized ratios are also given. These were calculated by dividing the ratios in each signature, by the ratios of a completely "flat" signature. A normalized ratio of 2 for "stop gain" mutations, means that a signature is twice as likely to cause "stop gain" mutations, compared to a completely random "flat" signature. N is the number of possible mutations per context, multiplied by the signature contribution per context, summed over all contexts. For mismatches the blosum62 score is also calculated. A lower score means that the amino acids in the mismatches are more dissimilar. More dissimilar amino acids are more likely to have a detrimental effect. Normalized blosum62 scores are also given. These are calculated by substracting the score of a completely "flat" signature from the base blosum62 scores.

### Usage

    signature_potential_damage_analysis(signatures, contexts, context_mismatches)

### Arguments

`signatures` | Matrix containing signatures
`contexts` | Vector of mutational contexts to use for the analysis.
`context_mismatches` | A tibble with the ratio of 'stop gain', 'mismatch', 'synonymous' and 'splice site' mutations per mutation context.

### Details

The function uses a tibble with the ratio of 'stop gain', 'mismatch', 'synonymous' and 'splice site' mutations per mutation context as its input. For each signature these ratios are linearly combined based on the signature weights. They are then divided by a "flat" signature to get the normalized ratios. The blosum62 scores are also linearly combined based on the signature weights.

Please take into account that this is a relatively basic analysis, that only looks at mutational contexts. It does not take into account that signatures can be influenced by open/closed chromatin, strand biases, hairpins or other epigenetic features. This analysis is meant to give an indication, not a definitive answer, of how damaging a signature might be. Further analyses might be required, especially when using signatures in a clinical context.

### Value

A tibble with the ratio of 'stop gain', 'mismatch', 'synonymous' and 'splice site' mutations per signature.

### Examples

    ## Get the signatures
    signatures <- get_known_signatures()

    ## See the 'mut_matrix()' example for how we obtained the
    ## mutation matrix information:
    mut_mat <- readRDS(system.file("states/mut_mat_data.rds",
      package = "MutationalPatterns"
    ))

    contexts <- rownames(mut_mat)

    ## See the 'context_potential_damage_analysis()' example for how we obtained the
    ## context_mismatches:
    context_mismatches <- readRDS(system.file("states/context_mismatches.rds",
      package = "MutationalPatterns"
    ))

    ## Determine the potential damage per signature
    signature_potential_damage_analysis(signatures, contexts, context_mismatches)

[Package MutationalPatterns version 3.0.1 Index]