permQValue: Calculate q-values from DGCA class objects based on...

In ryananeff/DGCA: Differential Gene Correlation Analysis

Description

First, estimate empirical p-values based on a comparison of the actual and permuted test statistics. Next, estimate the proportion of true null hypotheses using the qvalue package as well as qvalues from the empirical p-values, using this value. If the estimated pi0 <= 0, then sequentially recalculates using increasingly conservative set of lambda values, until lambda = 0.5.

Usage

permQValue(dcObject, permObject, secondMat, testSlot, verbose = FALSE,
  plotFdr = FALSE, empOnly = FALSE)

Arguments

dcObject	The original S4 class object containing the test statistics to be extracted.
permObject	The array of matrices containing the null test statistics.
secondMat	Logical, indicating whether a second matrix was used in the construction of this dcObject and permObject. If FALSE, the upper.tri of both are extracted to avoid double counting test statistics.
testSlot	The slot of the dcObject to be removed for use as the actual test statistic.
verbose	Whether summaries of the q-value operations should be reported.
plotFdr	Allows for plotting of fdrtool p-value adjustment result OR empirical FDR q-value adjustment technique, if either of these are chosen. Requires fdrtool package OR qvalue package. Default = FALSE.
empOnly	Whether or not we don't want to calculate qvalues for the empirical pvalues. Default = FALSE.

Value

A list containing a vectof of empirical p-values and a vector of q-values, both of the same length as the original actual test statistics.

ryananeff/DGCA documentation built on June 13, 2019, 12:57 a.m.