R: Find optimal nonnegative linear combination of mutation...

fit_to_signatures {MutationalPatterns}

R Documentation

Find optimal nonnegative linear combination of mutation signatures to reconstruct the mutation matrix.

Description

Find the linear combination of mutation signatures that most closely reconstructs the mutation matrix by solving the nonnegative least-squares constraints problem.

Usage

fit_to_signatures(mut_matrix, signatures)

Arguments

`mut_matrix`	96 mutation count matrix (dimensions: 96 mutations X n samples)
`signatures`	Signature matrix (dimensions: 96 mutations X n signatures)

Value

Named list with signature contributions and reconstructed mutation matrix

Examples


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

## You can download the signatures from the COSMIC website:
# http://cancer.sanger.ac.uk/cancergenome/assets/signatures_probabilities.txt

## We copied the file into our package for your convenience.
filename <- system.file("extdata/signatures_probabilities.txt",
                        package="MutationalPatterns")
cancer_signatures <- read.table(filename, sep = "\t", header = TRUE)

## Match the order to MutationalPatterns standard of mutation matrix
order = match(row.names(mut_mat), cancer_signatures$Somatic.Mutation.Type)
## Reorder cancer signatures dataframe
cancer_signatures = cancer_signatures[order,]
## Use trinucletiode changes names as row.names
## row.names(cancer_signatures) = cancer_signatures$Somatic.Mutation.Type
## Keep only 96 contributions of the signatures in matrix
cancer_signatures = as.matrix(cancer_signatures[,4:33])
## Rename signatures to number only
colnames(cancer_signatures) = as.character(1:30)


## Perform the fitting
fit_res <- fit_to_signatures(mut_mat, cancer_signatures)