test_gene_overrepresentation {tidybulk} | R Documentation

## analyse gene over-representation with GSEA

### Description

test_gene_overrepresentation() takes as input a 'tbl' formatted as | <SAMPLE> | <ENSEMBL_ID> | <COUNT> | <...> | 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' formatted as | <SAMPLE> | <TRANSCRIPT> | <COUNT> | <...> |
`.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 pvalueCutoff = 1 ) ))

### Value

A 'tbl' object

A 'spec_tbl_df' object

A 'tbl_df' object

A 'tidybulk' object

A 'SummarizedExperiment' object

A 'RangedSummarizedExperiment' object

### Examples

    df_entrez = tidybulk::se_mini %>% tidybulk() %>% as_tibble() %>% symbol_to_entrez( .transcript = feature, .sample = sample)
    df_entrez = aggregate_duplicates(df_entrez, aggregation_function = sum, .sample = sample, .transcript = entrez, .abundance = count)
    df_entrez = mutate(df_entrez, do_test = feature %in% c("TNFRSF4", "PLCH2", "PADI4", "PAX7"))

    	test_gene_overrepresentation(
    		df_entrez,
    		.sample = sample,
    		.entrez = entrez,
    		.do_test = do_test,
    		species="Homo sapiens",
       gene_sets =c("C2")
    	)

[Package tidybulk version 1.4.0 Index]