InferTFactPRL: Estimate TF activity score in different samples

In SEPIRA: Systems EPigenomics Inference of Regulatory Activity

Description

InferTFactPRL is an auxiliary function for function sepiraRegAct.

Usage

InferTFactPRL(idx, tmp, regnet)

Arguments

idx	A numeric vector indicating the samples from which you want to estimate the TF activity score.
tmp	A numeric matrix of gene expression levels for all TF target genes, with rows referring to genes, columns to samples.
regnet	The network estimated from function sepiraInfNet, with +1 referring to positive regulation, -1 negative regulation, and 0 no regulation.

Details

The user needs to input the index of the sample in the data matrix from which InferTFactPRL estimates TF activity. InferTFactPRL accomplishes the work by regressing the expression profile of TF target genes against the binding profile of this TF on these genes. The output t-statistics are taken as the TF activity score.

Value

A vector storing the activity scores of all TFs from user specified sample in the data matrix.

Examples

# TF regulatory network with 100 genes and 5 TFs.
regnet.m <- matrix(sample(c(-1, 0, 1), 500, replace = TRUE), nrow = 100)
# gene expression data matrix with 100 genes and 10 samples.
tmp.m <- matrix(rnorm(1000), nrow = 100)
# TF activity score
TFact.v <- SEPIRA:::InferTFactPRL(1, tmp.m, regnet.m)

SEPIRA documentation built on Nov. 8, 2020, 6:33 p.m.