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% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/signature_potential_damage_analysis.R
\name{signature_potential_damage_analysis}
\alias{signature_potential_damage_analysis}
\title{Potential damage analysis for the supplied mutational signatures}
\usage{
signature_potential_damage_analysis(signatures, contexts, context_mismatches)
}
\arguments{
\item{signatures}{Matrix containing signatures}
\item{contexts}{Vector of mutational contexts to use for the analysis.}
\item{context_mismatches}{A tibble with the ratio of 'stop gain', 'mismatch',
'synonymous' and 'splice site' mutations per mutation context.}
}
\value{
A tibble with the ratio of 'stop gain', 'mismatch', 'synonymous'
and 'splice site' mutations per signature.
}
\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.
}
\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.
}
\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)
}
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