utilities: Basic utilities for the EBcoexpress package
In EBcoexpress: EBcoexpress for Differential Co-Expression Analysis

Description Usage Arguments Details Value Author(s) References Examples

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.

1 2	crit.fun(ecPostProbs, targetFDR) bwmc(X)

`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

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

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 DC

If 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().

John A. Dawson <jadawson@wisc.edu>

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

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)))