plotNull: Plot the empirically estimated null distribution and...

In DavisLaboratory/singscore: Rank-based single-sample gene set scoring method

Plot the empirically estimated null distribution and associated p-values

Description

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.

Usage

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

Arguments

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

Value

a ggplot object

Author(s)

Ruqian Lyu

Examples

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])

DavisLaboratory/singscore documentation built on Nov. 21, 2024, 8:17 a.m.