runGOEnrich: Run Gene Ontology enrichment analysis on differentially...

In rliger: Linked Inference of Genomic Experimental Relationships

Run Gene Ontology enrichment analysis on differentially expressed genes.

Description

This function forms genesets basing on the differential expression result, and calls gene ontology (GO) analysis method provided by gprofiler2.

Usage

runGOEnrich(
  result,
  group = NULL,
  useBg = TRUE,
  orderBy = "padj",
  logFCThresh = 1,
  padjThresh = 0.05,
  splitReg = FALSE,
  ...
)

Arguments

result	Data frame of unfiltered output from runMarkerDEG or runPairwiseDEG.
group	Selection of one group available from result$group. Default NULL uses all groups involved in DE result table.
useBg	Logical, whether to set all genes involved in DE analysis (before threshold filtering) as a domain background of GO analysis. Default TRUE.
orderBy	Name of DE statistics metric to order the gene list for each group. Choose from "logFC" (default), "pval" or "padj". Or set NULL to turn off ranked mode.
logFCThresh	The log2FC threshold above which the genes will be used. Default 1.
padjThresh	The adjusted p-value threshold less than which the genes will be used. Default 0.05.
splitReg	Whether to have queries of both up-regulated and down-regulated genes for each group. Default FALSE only queries up-regulated genes and should be preferred when result comes from marker detection test. When result comes from group-to-group DE test, it is recommended to set splitReg = TRUE.
...	Additional arguments passed to gprofiler2::gost(). Useful ones are: organism The organism to be used for the analysis. "hsapiens" for human, "mmusculus" for mouse. evcodes Whether to include overlapping genes for each term. Default FALSE. significant Whether to filter out non-significant terms. Default TRUE. Arguments query, custom_bg, domain_scope, and ordered_query are pre-specified by this wrapper function.

Value

A list object where each element is a result list for a group. Each result list contains two elements:

result	data.frame of main GO analysis result.
meta	Meta information for the query.

See gprofiler2::gost(). for detailed explanation.

References

Kolberg, L. et al, 2020 and Raudvere, U. et al, 2019

Examples

# Setting `significant = FALSE` because it's hard for a gene list obtained
# from small test dataset to represent real-life biology.

if (requireNamespace("gprofiler2", quietly = TRUE)) {
    go <- runGOEnrich(deg.pw, group = "0.stim", significant = FALSE)
}

rliger documentation built on Oct. 30, 2024, 1:07 a.m.