bisect_supervised: Add together two numbers.

In bisect: Estimating Cell Type Composition from Methylation Sequencing Data

Description

Add together two numbers.

Usage

bisect_supervised(methylation, total_reads, reference, alpha = NA,
  iterations = 200)

Arguments

methylation	a matrix of individuals (rows) on sites (columns), containing the number of methylated reads for each site, in each individual.
total_reads	a matrix of individuals (rows) on sites (columns), containing the total number of reads for each site, in each individual.
reference	a matrix of sites (rows) on cell types (columns), containing the probability for methylation in each site, in each cell type.
alpha	a vector containing the hyper-parameters for the dirichelt prior. One value for each cell type. If NA, it is initiallized to 1/(number of cell types).
iterations	the number of iterations to use in the EM algorithm.

Value

A matrix of individuals (rows) on cell types (columns) containing the estimated proportion of each cell type, in each individual.

Examples

## Prepare the methylation and total reads matrices
methylation <- as.matrix(methylation_GSE40279)
total_reads <- as.matrix(total_reads_GSE40279)
## Remove the IDs column from the reference
Pi <- as.matrix(reference_blood[,-1])

## Run Bisect. You should use around 200 iterations. I choose than to accelarate the example.
results <- bisect_supervised(methylation, total_reads, Pi, alpha_blood, iterations = 10)

bisect documentation built on May 2, 2019, 9:20 a.m.