| explained_by_signatures {MutationalPatterns} | R Documentation |
This function has been renamed to 'cos_sim_matrix'.
explained_by_signatures(mut_matrix, signatures)
mut_matrix |
96 mutation count matrix (dimensions: 96 mutations X n samples) |
signatures |
96 mutation count matrix (dimensions: 96 mutations X m samples) |
Matrix with pairwise cosine similarities
cos_sim_matrix
mut_matrix,
fit_to_signatures,
plot_cosine_heatmap
## You can download mutational signatures from the COSMIC database:
# sp_url = http://cancer.sanger.ac.uk/cancergenome/assets/signatures_probabilities.txt
# cancer_signatures = read.table(sp_url, sep = "\t", header = T)
## 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)
## See the 'mut_matrix()' example for how we obtained the mutation matrix:
mut_mat <- readRDS(system.file("states/mut_mat_data.rds",
package="MutationalPatterns"))
## 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)
## Calculate the cosine similarity between each COSMIC signature and each 96 mutational profile
cos_sim_matrix(mut_mat, cancer_signatures)