findPvalueCutoff: Estimates false positive rate at a series of p-value cutoffs

In vijaykumarmuley/findPvalueCutoff: Select Differentially Expressed Genes At False Positive Rate Less Than Five Percent

Description

Given a p-value vector resulting from differential gene expression analysis, this function estimates false positive error rates expected by random chance at a series of p-value cutoffs

Usage

findPvalueCutoff(
  x = NULL,
  thresholds = NULL,
  range = c(0, 1),
  interval = 0.05,
  nsims = 1000
)

Arguments

x	A vector of p-values.
thresholds	A vector of manually selected p-value cutoffs at which false positive rate needs to be estimated.
range	Limit of lower and upper p-value cutoffs within which false positive rate will be estimated. Default is c(0,1) when thresholds parameter is NULL.
interval	Interval used to generate a series of p-values within lower and upper bound given in range porameter. Default is 0.05.
nsims	An integer value representing the number of simulated randomized datasets (controlled experiments) to be generated to compute false positive error rate. Default is 1000 but at least 10000 datasets are recommended.

Value

A named (p-value cutoffs) vector with estimated false positive rate.

Examples

## Not run: 
findPvalueCutoff(x = pval, thresholds=c(0.0001, 0.001, 0.01, 0.1, 0.2), nsims = 1000)
findPvalueCutoff(x = pval, range= c(0,2), interval= 0.01, nsims = 1000)

## End(Not run)

vijaykumarmuley/findPvalueCutoff documentation built on Dec. 23, 2021, 3:11 p.m.