BatchGSEA | R Documentation |
Performs GSEA for all Hotgenes contrasts
BatchGSEA(
m_df = NULL,
HotgenesObj = NULL,
nTop = 10,
cut_padj = 0.1,
minSize = 15,
maxSize = 1000,
nperm = 1e+05,
nproc = 1
)
m_df |
GeneSet generated using msigdbr function |
HotgenesObj |
R object generated by DEseq2_export function |
nTop |
number of pathways to return |
cut_padj |
Adjusted pvalue cut off. Default is 0.1. |
minSize |
Minimal size of a gene set to test. All pathways below the threshold are excluded. |
maxSize |
Maximal size of a gene set to test. All pathways above the threshold are excluded. |
nperm |
Number of permutations to do. Minimial possible nominal p-value is about 1/nperm |
nproc |
If not equal to zero sets BPPARAM to use nproc workers (default = 0). |
HotgenesObj appended with GSEA for each contrast
Example_Hotgenes_dir<-system.file("extdata",
"Example_Hotgenes.Rdata",
package = "Hotgenes", mustWork = TRUE)
load(Example_Hotgenes_dir)
library(msigdbr)
# GO annotations
m_df = msigdbr(species = "Homo sapiens", category = "C5", subcategory = "BP")
# Reactome annotations
# m_df = msigdbr(species = "Homo sapiens", category = "C2",
# subcategory = "CP:REACTOME")
qbat<-BatchGSEA(HotgenesObj=Example_Hotgenes,
m_df= m_df)
# View enriched pathways
lapply(qbat$OuputGSEA, function(x) head(x$fgRes$pathway))
# plot of enriched pathways
qbat$OuputGSEA$shEWS$g
# Prep for GSEA plot
m_list = qbat$m_list
# top pathways
qbat$OuputGSEA$shEWS$top$pathway
pyid<-qbat$OuputGSEA$shEWS$top$pathway[[2]]
pyid
Gene_Ranks <- qbat$OuputGSEA$shEWS$Gene_Ranks
fgsea::plotEnrichment(m_list[[pyid]], Gene_Ranks,
gseaParam = 1, ticksSize = 0.2) +
ggplot2::labs(title=stringr::str_wrap(pyid, 20))
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