# Enrichment analysis using GprofileR

Source: `R/enrichments.R`
`artmsEnrichProfiler.Rd`

This function simplifies the enrichment analysis performed by the excellent tool GprofileR.

    artmsEnrichProfiler(
      x,
      categorySource = c("GO"),
      species,
      background = NA,
      verbose = TRUE
    )

## Arguments

x | (list, data.frame) List of protein ids. It can be anything: either a list of ids, or you could also send a data.frame and it will find the columns with the IDs. Is not cool? Multiple list can be also sent simultaneously, as for example running: `tmp <- split(enrichment$Gene, enrichment$cl_number, drop= TRUE)`
categorySource | (vector) Resources providing the terms on which the enrichment will be performed. The supported resources by gprofiler are: GO (GO:BP, GO:MF, GO:CC): Gene Ontology (see more below) KEGG: Biological pathways REAC: Biological pathways (Reactome) TF: Regulatory motifs in DNA (TRANSFAC TFBS) MI: Regulatory motifs in DNA (miRBase microRNAs) CORUM: protein complexes database HP: Human Phenotype Ontology HPA: Protein databases (Human Protein Atlas) OMIM: Online Mendelian Inheritance in Man annotations: BIOGRID: BioGRID protein-protein interactions The type of annotations for Gene Ontology: Inferred from experiment (IDA, IPI, IMP, IGI, IEP) Direct assay (IDA) / Mutant phenotype (IMP] Genetic interaction (IGI) / Physical interaction (IPI) Traceable author (TAS) / Non-traceable author (NAS) / Inferred by curator (IC) Expression pattern (IEP) / Sequence or structural similarity (ISS) / Genomic context (IGC) Biological aspect of ancestor (IBA) / Rapid divergence (IRD) Reviewed computational analysis (RCA) / Electronic annotation (IEA) No biological data (ND) / Not annotated or not in background (NA)
species | (char) Specie code: Organism names are constructed by concatenating the first letter of the name and the family name. Example: human - ’hsapiens’, mouse - ’mmusculus’. Check gProfileR to find out more about supported species.
background | (vector) gene list to use as background for the enrichment analysis. Default: `NA`
verbose | (logical) `TRUE` (default) shows function messages

## Value

The enrichment results as provided by gprofiler

## Details

This function uses the following `gprofiler` arguments as default:

- ordered_query = FALSE

- significant = TRUE

- exclude_iea = TRUE

- underrep = FALSE

- evcodes = FALSE

- region_query = FALSE

- max_p_value = 0.05

- min_set_size = 0

- max_set_size = 0

- min_isect_size = 0

- correction_method = "analytical" #Options: "gSCS", "fdr", "bonferroni"

- hier_filtering = "none"

- domain_size = "known" # annotated or known

- numeric_ns = ""

- png_fn = NULL

- include_graph = TRUE

## Examples

    if (FALSE) {
    # annotate the MSstats results to get the Gene name
    data_annotated <- artmsAnnotationUniprot(
                                         x = artms_data_ph_msstats_results,
                                         columnid = "Protein",
                                         species = "human")

    # Filter the list of genes with a log2fc > 2
    filtered_data <-
    unique(data_annotated$Gene[which(data_annotated$log2FC > 2)])

    # And perform enrichment analysis
    data_annotated_enrich <- artmsEnrichProfiler(
                                       x = filtered_data,
                                       categorySource = c('KEGG'),
                                       species = "hsapiens",
                                       background = unique(data_annotated$Gene))
    }