# #——回声= FALSE,结果=“隐藏”,消息= FALSE ------------------------------- 需要(knitr)库(BiocStyle) opts_chunk美元集(错误= FALSE,消息= FALSE,警告= FALSE ) ## ----------------------------------------------------------------------------- 南加州爱迪生公司库(scRNAseq) < - HermannSpermatogenesisData南加州爱迪生公司() ## ----------------------------------------------------------------------------- 南加州爱迪生公司< -南加州爱迪生公司(,1:50 0 ] ## ----------------------------------------------------------------------------- 南加州爱迪生公司库(天窗)< - logNormCounts (sce assay.type = 1)图书馆(残渣)12月< modelGeneVar (sce)。hvgs < - getTopHVGs(2000年12月,n = ) ## ----------------------------------------------------------------------------- 图书馆velo(迅猛龙)。Out <- scvelo(sce, sub - set.row=top。hvgs, assay.X="spliced") velo。出 ## ----------------------------------------------------------------------------- 库(嘘)set.seed南加州爱迪生公司(100)< - runPCA南加州爱迪生公司(,subset_row = top.hvgs) < - runTSNE (sce dimred = PCA) sce velocity_pseudotime < - velo美元。美元velocity_pseudotime plotTSNE (sce colour_by = " velocity_pseudotime ") ## ----------------------------------------------------------------------------- 嵌入式< - embedVelocity (reducedDim (sce、“TSNE”),velo.out)网格。df <- gridVectors(reducedDim(sce， "TSNE")， embedded) library(ggplot2) plotTSNE(sce, colour_by="velocity_pseudotime") + geom_segment(data=grid. time)。df,映射= aes (x =开始。1, y =开始。2, xend =结束。1、yend = end.2)箭头=箭头(长度=单位(英寸0.05。 "))) ## ----------------------------------------------------------------------------- # 只有设置分析。对于最初的AnnData创建，X= #它实际上不会在任何后续步骤中使用。velo。Out2 <- scvelo(sce，化验。X = 1, subset.row =。hvgs, use.dimred="PCA") velo。out2 ## ----------------------------------------------------------------------------- velo。Out3 <- scvelo(sce, assay. o)X=1，使用。their =TRUE) velo。out3 ## ----------------------------------------------------------------------------- velo.out4 <- scvelo(sce, assay.X=1, subset.row=top.hvgs, scvelo.params=list(recover_dynamics=list(max_iter=20))) velo.out4 ## ----------------------------------------------------------------------------- sessionInfo()