dCorClass: Classify differential correlations.

In andymckenzie/DGCA: Differential Gene Correlation Analysis

Classify differential correlations.

Description

Classifies identifiers (e.g., genes) into one of the different categories pairwise-differential correlation classes. These categories are one of the Cartesian products of "Up Correlation", "No Correlation", and "Down Correlation" in each of the conditions, as well as a category for "no significant differential correlation".

Usage

dCorClass(corsA, pvalsA, corsB, pvalsB, dCorPVals, sigThresh = 1,
  corSigThresh = 0.05, convertClasses = FALSE)

Arguments

corsA	Numeric vector of correlations between gene pairs in condition A.
pvalsA	Numeric vector of the significance of correlation calls between gene pairs in condition A.
corsB	Numeric vector of correlations between gene pairs in condition B.
pvalsB	Numeric vector of the significance of correlation calls between gene pairs in condition B.
dCorPVals	Numeric vector of the differential correlation p-value calls.
sigThresh	If classify = TRUE, this numeric value specifies the p-value threshold at which a differential correlation p-value is deemed significant for differential correlation class calculation. Default = 1, as investigators may use different cutoff thresholds; however, this can be lowered to establish significant classes as desired.
corSigThresh	Threshold at which the correlation p-values must be below in order to be called "significant". Default = 0.05.
convertClasses	Logical indicating whether the returned classes should be in numeric (factor) format or character format indicating the "actual" class.

Value

A numeric vector of classes derived from each of the input vectors.

Examples

rho1 = runif(100, -1, 1); rho2 = runif(100, -1, 1)
pvalsA = runif(100, 0, 1); pvalsB = runif(100, 0, 1); dcor_pvals = runif(100, 0, 1)
cor_classes = dCorClass(rho1, pvalsA, rho2, pvalsB, dcor_pvals)
cor_classes = dCorClass(rho1, pvalsA, rho2, pvalsB, dcor_pvals, convertClasses = TRUE)

andymckenzie/DGCA documentation built on July 3, 2024, 10:29 a.m.