test_genesets_fisherexact {goat}

Geneset ORA using Fisher-exact test

Description

In most cases, it's more convenient to call the more generic test_genesets function which also deals with multiple-testing correction (per geneset source)

It is assumed that the genesets and genelist parameters are in sync, i.e. genesets provided here is the result of the filter_genesets() function (using the same genelist table)

Same as hypergeometric for non-EASE, but slower because stats::fisher.test isn't vectorized

Only genesets with at least 1 significant gene are subjected to statistical testing (e.g. NA is returned for genesets without significant genes)

Usage

test_genesets_fisherexact(
  genesets,
  genelist,
  require_nsignif = 1L,
  use_ease = FALSE
)

Arguments

genesets

tibble with genesets, must contain columns 'id', 'ngenes' and 'ngenes_signif'

genelist

tibble with genes, must contain column 'signif'. The number of rows in this table (where signif is not NA) is assumed to be the total number of tested genes, the number of rows where signif==TRUE is assumed the total number of significant genes.

require_nsignif

minimum number of 'signif genes' that overlap with a geneset; NA pvalues are returned for genesets with ngenes_signif <= require_nsignif. This function 'prefilters' genesets, so beware that this will influence downstream multiple testing correction. Default is 1

use_ease

use a more conservative score coined by DAVID online tools @ https://david.ncifcrf.gov/helps/functional_annotation.html#fisher

Value

input genesets table with results in the "pvalue" column

See Also

test_genesets

Examples

# note; this example downloads data when first run, and typically takes ~60seconds

# store the downloaded files in the following directory. Here, the temporary file
# directory is used. Alternatively, consider storing this data in a more permanent location.
# e.g. output_dir="~/data/goat" on unix systems or output_dir="C:/data/goat" on Windows
output_dir = tempdir()

## first run the default example from test_genesets() to obtain input data
datasets = download_goat_manuscript_data(output_dir)
genelist = datasets$`Wingo 2020:mass-spec:PMID32424284`
genesets_asis = download_genesets_goatrepo(output_dir)
genesets_filtered = filter_genesets(genesets_asis, genelist)

## example: same results between Fisher-exact and hypergeometric tests
result_hg = test_genesets_hypergeometric(genesets_filtered, genelist, require_nsignif = 3L)
result_fe = test_genesets_fisherexact(genesets_filtered, genelist, require_nsignif = 3L)
all.equal(result_hg$pvalue, result_fe$pvalue)