plotNull: Plot the empirically estimated null distribution and...
In singscore: Rank-based single-sample gene set scoring method

Description Usage Arguments Value Author(s) Examples

This function takes the results from function generateNull() and plots the density curves of permuted scores for the provided samples via sampleNames parameter. It can plot null distribution(s) for a single sample or multiple samples.

plotNull(
  permuteResult,
  scoredf,
  pvals,
  sampleNames = NULL,
  cutoff = 0.01,
  textSize = 2,
  labelSize = 5
)

`permuteResult`	A matrix, null distributions for each sample generated using the `generateNull()` function
`scoredf`	A dataframe, singscores generated using the `simpleScore()` function
`pvals`	A vector, estimated p-values using the `getPvals()` function `permuteResult`,`scoredf` and `pvals` are the results for the same samples.
`sampleNames`	A character vector, sample IDs for which null distributions will be plotted
`cutoff`	numeric, the cutoff value for determining significance
`textSize`	numeric, size of axes labels, axes values and title
`labelSize`	numeric, size of label texts

a ggplot object

Ruqian Lyu

ranked <- rankGenes(toy_expr_se)
scoredf <- simpleScore(ranked, upSet = toy_gs_up, downSet = toy_gs_dn)
# find out what backends can be registered on your machine
BiocParallel::registered()
# the first one is the default backend, and it can be changed explicitly.
permuteResult = generateNull(upSet = toy_gs_up, downSet = toy_gs_dn, ranked,
B =10, seed = 1,useBPPARAM = NULL)
# call the permutation function to generate the empirical scores
#for B times.
pvals <- getPvals(permuteResult,scoredf)
# plot for all samples
plotNull(permuteResult,scoredf,pvals,sampleNames = names(pvals))
#plot for the first sample
plotNull(permuteResult,scoredf,pvals,sampleNames = names(pvals)[1])