InferTFactPRL {SEPIRA} | R Documentation

## Estimate TF activity score in different samples

### 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)

[Package SEPIRA version 1.4.1 Index]