getGammaPVal: Get a p-value for region set scores based on a gamma...
In COCOA: Coordinate Covariation Analysis

First fit a gamma distribution to each region set's null distribution/s (nullDistList). Then use this gamma distribution to convert scores in rsScores to p-values.

getGammaPVal(
  rsScores,
  nullDistList,
  signalCol,
  method = "mme",
  realScoreInDist = TRUE,
  force = FALSE
)

`rsScores`	data.frame. A data.frame with region set scores. The output of the 'aggregateSignalGRList' function. Each row is a region set. One column for each sample variable of interest (e.g. PC or sample phenotype). Also can have columns with info on the overlap between the region set and the epigenetic data. Rows should be in the same order as the region sets in GRList (the list of region sets used to create rsScores.)
`nullDistList`	list of data.frames. Each list item has null distributions for a single region set (list items should be in the same order as rows of rsScores). Has same score columns as rsScores. Each column corresponds to a null distribution for that region set for a given sample variable of interest/target variable (e.g. PC or sample phenotype).
`signalCol`	A character vector with the names of the sample variables of interest/target variables (e.g. PCs or sample phenotypes). Must be column names of rsScores.
`method`	Character. Has the method to use to fit the gamma distribution to the null distribution. Options are "mme" (moment matching estimation), "mle" (maximum likelihood estimation), "qme" (quantile matching estimation), and "mge" (maximum goodness-of-fit estimation). See ?fitdistrplus::fitdist() for available options and meaning.
`realScoreInDist`	logical. Should the actual score (from test with no permutations) be included in the null distribution when fitting the gamma distribution. realScoreInDist=TRUE is recommended.
`force`	logical. If force=TRUE, when fitting the gamma distribution returns an error (as may happen when a method other than "mme" is used) then allow the error. If force=FALSE, when fitting the gamma distribution returns an error then don't return an error but instead use the "mme" method for fitting that specific gamma distribution.