Function reference • dcanr

Differential co-expression analysis methods These functions are used to perform a differential co-expression analysis on experimental data with binary conditions.
`dcMethods()`	Get names of differential co-expression methods
`dcScore()`	Compute scores from differential association analysis
`dcTest()`	Statistical test for differential association analysis
`dcAdjust()`	Adjust for multiple testing in differential association analysis
`dcNetwork()`	Generate a differential network from a DC analysis
Functions to evaluate DC methods These functions are used to evaluate methods implemented in the package and novel methods on simulated data. Expression data is simulated for two conditions, wild-type and knock-down of given genes.
`sim102`	Simulated expression data with knock-outs
`getSimData()` `getConditionNames()` `getTrueNetwork()`	Get data and conditions from a given knock-down (KD)
`plotSimNetwork()`	Plot source and true differential networks from simulations
`dcPipeline()`	Run a DC pipeline on a simulation
`dcEvaluate()`	Evaluate performance of DC methods on simulations
Additional general use functions These are functions used in the package but have further uses in general
`cor.pairs()`	Fast pairwise correlation estimation
`mi.ap()`	Mutual information using adaptive partitioning
`perfMethods()`	Get names of performance metric methods
`performanceMeasure()`	Performance metrics to evaluate classification

Reference