protti: kegg_enrichment – R documentation

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kegg_enrichment

Perform KEGG pathway enrichment analysis

Description

Analyses enrichment of KEGG pathways associated with proteins in the fraction of significant proteins compared to all detected proteins. A Fisher's exact test is performed to test significance of enrichment.

Usage

kegg_enrichment(
  data,
  protein_id,
  is_significant,
  pathway_id = pathway_id,
  pathway_name = pathway_name,
  plot = TRUE,
  plot_cutoff = "adj_pval top10"
)

Arguments

`data`	A data frame that contains at least the input variables.
`protein_id`	The name of the column containing the protein accession numbers.
`is_significant`	The name of the column containing a logical indicating if the corresponding protein has a significantly changing peptide. The input data frame may contain peptide level information with significance information. The function is able to extract protein level information from this.
`pathway_id`	The name of the column containing KEGG pathway identifiers. These can be obtained from KEGG using `fetch_kegg`.
`pathway_name`	The name of the column containing KEGG pathway names. These can be obtained from KEGG using `fetch_kegg`.
`plot`	A logical indicating whether the result should be plotted or returned as a table.
`plot_cutoff`	A character vector indicating if the plot should contain the top 10 most significant proteins (p-value or adjusted p-value), or if a significance cutoff should be used to determine the number of GO terms in the plot. This information should be provided with the type first followed by the threshold separated by a space. Example are `plot_cutoff = "adj_pval top10"`, `plot_cutoff = "pval 0.05"` or `plot_cutoff = "adj_pval 0.01"`. The threshold can be chosen freely.

Value

A bar plot displaying negative log10 adjusted p-values for the top 10 enriched pathways. Bars are coloured according to the direction of the enrichment. If plot = FALSE, a data frame is returned.

Examples

## Not run: 
kegg_enrichment(
  data,
  protein_id = pg_protein_accessions,
  is_significant = significant,
  pathway_id = pathway_id,
  pathway_name = pathway_name
)

## End(Not run)

protti

Bottom-Up Proteomics and LiP-MS Quality Control and Data Analysis Tools

v0.1.1

MIT + file LICENSE

Authors

Jan-Philipp Quast [aut, cre], Dina Schuster [aut], ETH Zurich [cph, fnd]

Initial release