scGSVA provides wrap functions to do GSVA analysis for single cell data. And scGSVA includes functions to build annotation for almost all species. scGSVA also provides function to generate figures based on the GSVA results. scGSVA provides functions to generate annotation data which can be used in the analysis.
library(devtools)
install_github("guokai8/scGSVA")
set.seed(123)
library(scGSVA)
data(pbmcs)
hsko<-buildAnnot(species="human",keytype="SYMBOL",anntype="KEGG")
res<-scgsva(pbmcs,hsko)
vlnPlot(res,features="Wnt.signaling.pathway",group_by="groups")
dotPlot(res,features="Wnt.signaling.pathway",group_by="groups")
ridgePlot(res,features="Wnt.signaling.pathway",group_by="groups")
featurePlot(res,features="Wnt.signaling.pathway", reduction="tsne", group_by="groups")
Heatmap(res,group_by="groups")
## find significant pathways across groups
findPathway(res,group = "groups")
sigPathway(res, group = "groups")
## extract specific pathways with expression value
genes(res, features = "Wnt.signaling.pathway")
The scGSVA package use the GSVA package to do the GSVA analysis for the single cell data. The package is still under development.
For any questions please contact guokai8@gmail.com or https://github.com/guokai8/scGSVA/issues