Load the library and the data
library(SpaGene)
load("Slideseq/SlideseqV2_ROI.rds")
Find spatial variable genes and patterns
mc_sv<-SpaGene(sp_count,location)
head(mc_sv$spagene_res[order(mc_sv$spagene_res$adjp),])
## score zval pval adjp
## Aldoc 11.75183 -46.25374 0 0
## Car8 11.65978 -47.99349 0 0
## Fth1 11.67742 -47.66017 0 0
## Itpr1 11.41548 -52.61112 0 0
## Mbp 11.51742 -50.68440 0 0
## Pcp2 11.44129 -52.12334 0 0
pattern<-FindPattern(mc_sv)
PlotPattern(pattern,location,pt.size = 0.3)
Top 5 genes falling into each pattern
top5<-apply(pattern$genepattern,2,function(x){names(x)[order(x,decreasing=T)][1:5]})
library(pheatmap)
pheatmap(pattern$genepattern[rownames(pattern$genepattern)%in%top5,])
Identify colocalized ligand-receptor pairs
load("LRpair.rds")
mc_lr<-SpaGene_LR(sp_count,location,LRpair=LRpair)
head(mc_lr[order(mc_lr$adj),])
## score comm zval pval adjp
## Psap_Gpr37l1 30.71656 601 -11.498993 6.673135e-31 9.629333e-28
## Il16_Kcnd2 30.73462 588 -11.070412 8.729765e-29 6.298525e-26
## App_Sorl1 30.91871 597 -6.702967 1.021147e-11 4.911716e-09
## Ptn_Ptprz1 30.94366 605 -6.111117 4.946806e-10 1.784560e-07
## App_Cd47 30.94624 561 -6.049891 7.247182e-10 2.091537e-07
## Mdk_Ptprz1 30.95570 510 -5.825396 2.848860e-09 6.851508e-07
Plot Ligand-receptor pairs Psap-Gpr37l1 and Ptn-Ptprz1
plotLR(sp_count,location,LRpair=c("Psap","Gpr37l1"),alpha.min=0.2,pt.size = 0.3)
plotLR(sp_count,location,LRpair=c("Ptn","Ptprz1"),alpha.min=0.2,pt.size = 0.3)
