EBcoexpress (version 1.16.0)

utilities: Basic utilities for the EBcoexpress package

Description

At present there are two utilties: crit.fun() and bwmc(). The former is used to compute soft thresholds for FDR control, the latter is like cor() but uses biwieght midcorrelation instead of the usual Pearson's correlation coefficient.

Usage

crit.fun(ecPostProbs, targetFDR)
bwmc(X)

Arguments

ecPostProbs

An array of posterior probabilities of equivalent coexpression for all pairs

targetFDR

A target FDR rate

X

An expression matrix in one condition where the rows correspond to genes

Value

crit.fun returns a single value; under a soft thresholding approach, any pair with total posterior probability of differential co-expression (i.e., 1 - posterior probability of equivalent co-expression) greater than this value is deemed to be DCIf X has 1st dimension m, bwmc(t(X)) returns an m-by-m matrix of pairwise biweight midcorrelations as a matrix, in a manner similar to cor().

Details

crit.fun() returns a soft threshold for FDR control. It is similar to the function of the same name in the package EBarrays. bwmc() computes the biweight midcorrelation for an expression matrix; it is used internally to generate the D correlations matrix by makeMyD() when useBWMC is TRUE. It is also a handy little function so we made it visible at the top level. The guts of this function are in C for speed

References

Dawson JA and Kendziorski C. An empirical Bayesian approach for identifying differential co-expression in high-throughput experiments. (2011) Biometrics. E-publication before print: http://onlinelibrary.wiley.com/doi/10.1111/j.1541-0420.2011.01688.x/abstract

Examples

set.seed(1)
ecs <- c(runif(950),runif(50,0,0.01))
thresh <- crit.fun(ecs, 0.05)

set.seed(1)
X <- matrix(runif(10*100),10,100)
print(cor(t(X)))
print(bwmc(t(X)))