get_classification: Get classification using Bayes' Thereom

In jdavilal/excerno: Fillter out somatic mutations generated by the Formalin-Fixed Paraffin-Embedded (FFPE) tissue preservation technique from cancer tissue

Get classification using Bayes' Thereom

Description

Determine probability of where each mutation came from using Bayes' Thereom.

Usage

get_classification(signatures, contribution)

get_classifications(signatures, contribution)

Arguments

signatures	A matrix of signatures
contribution	A matrix of the contributions coming from each signature

Value

A data frame with the probabilities for each mutation.

Examples

library(MutationalPatterns)
library(tidyverse)

# Load in signatures
cosmic.sigs <- get_known_signatures()

# Get signatures
signatures <- matrix(nrow = 96, ncol = 2)
signatures[,1] <- cosmic.sigs[,4]
signatures[,2] <- get_ffpe_signature()
colnames(signatures) <- c("SBS4", "FFPE")
rownames(signatures) <- get_mutation_types()

# Get contributions
contribution <- matrix(nrow = 2, ncol = 1)
contribution[,1] <- c(0.5, 0.5)
rownames(contribution) <- c("SBS4", "FFPE")
colnames(contribution) <- "SAMPLE1"

# Function usage
get_classification(signatures, contribution)

# For more than one sample
contributions <- matrix(nrow = 2, ncol = 4)
contributions[,] <- sample(0.5, 4, replace = TRUE)
colnames(contributions) <- c("SAMPLE1", "SAMPLE2", "SAMPLE3", "SAMPLE4")
rownames(contributions) <- c("SBS4", "FFPE")
get_classifications(signatures, contributions)

jdavilal/excerno documentation built on Aug. 27, 2022, 8:10 p.m.