dcTopPairs: Creates a data frame for the top differentially correlated...

In andymckenzie/DGCA: Differential Gene Correlation Analysis

Creates a data frame for the top differentially correlated gene pairs in your data set.

Description

Reads in a dcPair object and outputs a table of all gene pairs (or just the top n pairs), sorted by their unadjusted differential correlation p-value.

Usage

dcTopPairs(dcObject, nPairs, adjust = "none", plotFdr = FALSE,
  classify = TRUE, sigThresh = 1, corSigThresh = 0.05,
  zScorePerm = NULL, verbose = FALSE, compare = NULL, secondMat = FALSE)

Arguments

dcObject	The dcPair class object which you'd like to convert into a table.
nPairs	The number of gene pairs to display in the resulting table.
adjust	Allows for resulting p-values to be corrected for multiple hypothesis tests, optional. Some non-default choices require the "fdrtool" package or the "qvalue". Default = "none", which means that no p-value adjustment is performed. Other options include "perm" to use permutation samples, methods in ?p.adjust (i.e., "holm", "hochberg", "hommel", "bonferroni", "BH", "BY", "fdr"), and methods in ?fdrtool (i.e., "fndr", "pct0", "locfdr").
plotFdr	Allows for plotting of p-value adjustment result, if this is chosen. Requires fdrtool or qvalue package. Default = FALSE.
classify	Binary value specifying whether the correlation values in each condition and differential correlation scores should be used to classifying the resulting identifiers into groups. Default = TRUE
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	If classify = TRUE, this numeric value specifies the p-value threshold at which a correlation p-value is deemed significant. Default = 0.05.
zScorePerm	A matrix of values with z-scores from permutation tests to be used to generate empirical p-values. Default = NULL.
verbose	Whether summaries of the operations should be reported.
compare	Vector of two character strings, each corresponding to one group name in the design matrix, that should be compared.
secondMat	Logical indicator of whether there is a second matrix in the comparison or not.

Value

A table containing columns for each name in the considered gene pair (the order of which is arbitrary), correlation values in each condition, differences in z-score of the correlation, and p-values for that z-score difference.

andymckenzie/DGCA documentation built on Sept. 15, 2023, 5:04 a.m.