threshold_fdr: Apply false discovery rate (FDR) threshold to correlation...

In Sage-Bionetworks/sageseqr: Identify differentially expressed genes counts data

Apply false discovery rate (FDR) threshold to correlation matrix.

Description

Adjusts a given a set of p-values using FDR and returns a vector of logical values indicating whether the value is less than or equal to the threshold FDR.

Usage

threshold_fdr(correlation_values, mask_indices = NULL, maximum_fdr = 0.1)

Arguments

correlation_values	A data frame with p-values in column 'pvalue'.
mask_indices	A logical vector to indicate whether a covariate has missing values and should be skipped when computing FDR.
maximum_fdr	Maximum allowable false discovery rate (FDR). Defaults to 0.1.

Examples

## Not run: 
correlation_values <- data.frame(
  compare = "PC1 (23.16%)",
  covariates = "batch",
  pvalue = 0.56519736,
  r = "0.05729811"
  )

## End(Not run)

Sage-Bionetworks/sageseqr documentation built on June 13, 2024, 2:11 p.m.