pickCompProbesMatrix: Select probes for use in cellular deconvolution

In ds420/CETYGO: Quantifying the accuracy of cellular deconvolution

Select probes for use in cellular deconvolution

Description

Using a DNA methylation dataset containing profiles for a panel of reference cell types this function selects the sites for cellular deconvolution and estimates the nessecary coefficients This function is adapted from minfi pickCompProbes() to take a matrix of beta values rather than mset

Usage

pickCompProbesMatrix(
  rawbetas,
  cellInd,
  cellTypes = NULL,
  numProbes = 50,
  probeSelect = "both"
)

Arguments

rawbetas	A matrix of DNA methylation levels from reference cell types
cellInd	A vector specifying which cell type each column of rawbetas represents
cellTypes	A vector of which cell types in cellInd to include in generation of reference panel
numProbes	The number of probes for each cell type to select
probeSelect	How should probes be selected to distinguish cell types? Options include "both", which selects an equal number (50) of probes (with F-stat p-value < 1E-8) with the greatest magnitude of effect from the hyper- and hypo-methylated sides, and "any", which selects the 100 probes (with F-stat p-value < 1E-8) with the greatest magnitude of difference regardless of direction of effect.

Value

A list with the estimate coefficients, summary of F tests and cell type means.

Examples

# create mean DNAm levels for 100 sites
set.seed(1327)
meanBetas <- runif(100, min = 0, max = 1)
# generate cell type diffs
meanCTDiff <- rnorm(100, mean = 0, sd = 0.2)
# create reference training data
refBetas <- cbind(
    matrix(meanBetas + rnorm(500, mean = 0, sd = 0.01),
        nrow = 100, byrow = FALSE
    ),
    matrix(meanBetas + rnorm(500, mean = 0, sd = 0.01) + meanCTDiff,
        nrow = 100, byrow = FALSE
    )
)
# force to lie between 0 and 1
refBetas[refBetas < 0] <- runif(sum(refBetas < 0), 0, 0.05)
refBetas[refBetas > 1] <- runif(sum(refBetas > 1), 0.95, 1)
cellInd <- c(rep("A", 5), rep("B", 5))
rownames(refBetas) <- paste0("cg", seq_len(100))
pickCompProbesMatrix(
    rawbetas = refBetas,
    cellTypes = c("A", "B"),
    cellInd = cellInd, numProbes = 10
)

ds420/CETYGO documentation built on July 7, 2023, 12:16 a.m.