test_gene_overrepresentation-methods: analyse gene over-representation with GSEA

In stemangiola/tidybulk: Brings transcriptomics to the tidyverse

analyse gene over-representation with GSEA

Description

test_gene_overrepresentation() takes as input a 'tbl' (with at least three columns for sample, feature and transcript abundance) or 'SummarizedExperiment' (more convenient if abstracted to tibble with library(tidySummarizedExperiment)) and returns a 'tbl' with the GSEA statistics

Usage

test_gene_overrepresentation(
  .data,
  .entrez,
  .do_test,
  species,
  .sample = NULL,
  gene_sets = NULL,
  gene_set = NULL
)

## S4 method for signature 'spec_tbl_df'
test_gene_overrepresentation(
  .data,
  .entrez,
  .do_test,
  species,
  .sample = NULL,
  gene_sets = NULL,
  gene_set = NULL
)

## S4 method for signature 'tbl_df'
test_gene_overrepresentation(
  .data,
  .entrez,
  .do_test,
  species,
  .sample = NULL,
  gene_sets = NULL,
  gene_set = NULL
)

## S4 method for signature 'tidybulk'
test_gene_overrepresentation(
  .data,
  .entrez,
  .do_test,
  species,
  .sample = NULL,
  gene_sets = NULL,
  gene_set = NULL
)

## S4 method for signature 'SummarizedExperiment'
test_gene_overrepresentation(
  .data,
  .entrez,
  .do_test,
  species,
  .sample = NULL,
  gene_sets = NULL,
  gene_set = NULL
)

## S4 method for signature 'RangedSummarizedExperiment'
test_gene_overrepresentation(
  .data,
  .entrez,
  .do_test,
  species,
  .sample = NULL,
  gene_sets = NULL,
  gene_set = NULL
)

Arguments

.data	A 'tbl' (with at least three columns for sample, feature and transcript abundance) or 'SummarizedExperiment' (more convenient if abstracted to tibble with library(tidySummarizedExperiment))
.entrez	The ENTREZ ID of the transcripts/genes
.do_test	A boolean column name symbol. It indicates the transcript to check
species	A character. For example, human or mouse. MSigDB uses the latin species names (e.g., \"Mus musculus\", \"Homo sapiens\")
.sample	The name of the sample column
gene_sets	A character vector. The subset of MSigDB datasets you want to test against (e.g. \"C2\"). If NULL all gene sets are used (suggested). This argument was added to avoid time overflow of the examples.
gene_set	DEPRECATED. Use gene_sets instead.

Details

'r lifecycle::badge("maturing")'

This wrapper execute gene enrichment analyses of the dataset using a list of transcripts and GSEA. This wrapper uses clusterProfiler (DOI: doi.org/10.1089/omi.2011.0118) on the back-end.

Undelying method: msigdbr::msigdbr(species = species) |> nest(data = -gs_cat) |> mutate(test = map( data, ~ clusterProfiler::enricher( my_entrez_rank, TERM2GENE=.x |> select(gs_name, entrez_gene), pvalueCutoff = 1 ) |> as_tibble() ))

Value

A consistent object (to the input)

A 'spec_tbl_df' object

A 'tbl_df' object

A 'tidybulk' object

A 'SummarizedExperiment' object

A 'RangedSummarizedExperiment' object

Examples

print("Not run for build time.")

#se_mini = aggregate_duplicates(tidybulk::se_mini, .transcript = entrez)
#df_entrez = mutate(df_entrez, do_test = feature %in% c("TNFRSF4", "PLCH2", "PADI4", "PAX7"))

## Not run: 
	test_gene_overrepresentation(
		df_entrez,
		.sample = sample,
		.entrez = entrez,
		.do_test = do_test,
		species="Homo sapiens",
   gene_sets =c("C2")
	)

## End(Not run)

stemangiola/tidybulk documentation built on Oct. 23, 2024, 8 a.m.