Run Gene Ontology enrichment analysis on differentially expressed genes.
Source:R/GSEA.R
runGOEnrich.Rd
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
orrunPairwiseDEG
.- group
Selection of one group available from
result$group
. DefaultNULL
uses all groups involved in DEresult
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 setNULL
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 whenresult
comes from marker detection test. Whenresult
comes from group-to-group DE test, it is recommended to setsplitReg = TRUE
.- ...
Additional arguments passed to
gprofiler2::gost()
. Argumentsquery
,custom_bg
,domain_scope
, andordered_query
are pre-specified by this wrapper function. Users must setorganism = "mmusculus"
when working on mouse data.
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.
Examples
res <- runMarkerDEG(pbmcPlot)
#> ℹ Running Wilcoxon rank-sum test
#> ✔ Running Wilcoxon rank-sum test ... done
#>
# Setting `significant = FALSE` because it's hard for a gene list obtained
# from small test dataset to represent real-life biology.
# \donttest{
if (requireNamespace("gprofiler2", quietly = TRUE)) {
go <- runGOEnrich(res, group = 0, significant = FALSE)
}
# }