cluster_signatures {MutationalPatterns} | R Documentation

## Signature clustering function

### Description

Hierarchical clustering of signatures based on cosine similarity

### Usage

    cluster_signatures(signatures, method = "complete")

### Arguments

`signatures` | Matrix with 96 trinucleotides (rows) and any number of signatures (columns)
`method` | The agglomeration method to be used for hierarchical clustering. This should be one of "ward.D", "ward.D2", "single", "complete", "average" (= UPGMA), "mcquitty" (= WPGMA), "median" (= WPGMC) or "centroid" (= UPGMC). Default = "complete".

### Value

hclust object

### See Also

`plot_contribution_heatmap`

### Examples

    ## 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)

    ## Hierarchically cluster the cancer signatures based on cosine similarity
    hclust_cancer_signatures = cluster_signatures(cancer_signatures)

    ## Plot dendrogram
    plot(hclust_cancer_signatures)

    ## Save the signature names in the order of the clustering
    sig_order = colnames(cancer_signatures)[hclust_cancer_signatures$order]

[Package MutationalPatterns version 2.0.0 Index]