RNA 速率：使用 Seurat 的结果做 RNA velocity

>library (Seurat)

## remotes::install_github ('satijalab/seurat-wrappers')

>library (SeuratWrappers)

## 导入 Seurat 对象，之前分析的结果

>load ("wang.rds")

>load ('wang-loom.rds')

> wt$spliced[1:3,1:3]

3 x 3 sparse Matrix of class "dgCMatrix"

          WANG:AAAGTAGAGATGTTAGx WANG:AAACCTGTCAGCATGTx WANG:AAAGCAACATTTGCTTx

AT1G01020                      .                      .                      .

AT1G01030                      .                      .                      .

AT1G03993                      .                      .                      .

> wang@meta.data[1:3,1:3]

                   orig.ident nCount_RNA nFeature_RNA

AAACCTGAGAATTCCC-1        zxz       3756         2158

AAACCTGAGGGCACTA-1        zxz       2774         1669

AAACCTGAGTAATCCC-1        zxz       2463         1290

> colnames(wt$spliced)<-gsub("x","-1",colnames(wt$spliced))

> colnames(wt$spliced)<-gsub("WANG:","",colnames(wt$spliced))

> colnames(wt$unspliced)<-colnames(wt$spliced)

> colnames(wt$ambiguous)<-colnames(wt$spliced)

## 由于 Seurat 的对象筛选了数据，所以两个文件细胞并不相同，以 Seurat 对象为准

> wt$spliced<-wt$spliced [,rownames (wang@meta.data)]

> wt$unspliced<-wt$unspliced [,rownames (wang@meta.data)]

> wt$ambiguous<-wt$ambiguous [,rownames (wang@meta.data)]

> sp <- wt$spliced

> unsp <- wt$unspliced

> WTumap <- wang@reductions$umap@cell.embeddings

## 估计细胞和细胞的距离

> cell.dist <- as.dist (1-armaCor (t (wang@reductions$umap@cell.embeddings)))

> fit.quantile <- 0.02

> rvel.cd <- gene.relative.velocity.estimates (sp,unsp,deltaT=2,kCells=10, cell.dist=cell.dist,fit.quantile=fit.quantile,n.cores=24)

library(ggplot2)

pdf("cell_velocity.pdf",height=6,width=8)

gg <- UMAPPlot(wang)

ggplot_build(gg)$data

colors <- as.list(ggplot_build(gg)$data[[1]]$colour)

names(colors) <- rownames(WTumap)

p1 <- show.velocity.on.embedding.cor(WTumap,rvel.cd,n=30,scale='sqrt',cell.colors=ac(colors,alpha=0.5),cex=0.8,arrow.scale=2,show.grid.flow=T,min.grid.cell.mass=1.0,grid.n=50,arrow.lwd=1,do.par=F,cell.border.alpha =0.1,USE_OPENMP=1,n.cores=24,main="Cell Velocity")

dev.off()

id<-c ('2','3','19','20')

Cell.sub <- subset (wang@meta.data,seurat_clusters==id)

scRNAsub <- subset (wang, cells=row.names (Cell.sub))

## 后续的操作相同