dCorClass | R Documentation |
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".
dCorClass(corsA, pvalsA, corsB, pvalsB, dCorPVals, sigThresh = 1,
corSigThresh = 0.05, convertClasses = FALSE)
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. |
A numeric vector of classes derived from each of the input vectors.
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)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.