# #——风格,回声= FALSE,结果=“隐藏”,消息= FALSE,缓存= FALSE ------------ 图书馆(BiocStyle)图书馆(knitr)美元opts_chunk组(错误= FALSE,消息= FALSE,警告= FALSE,缓存= TRUE) opts_chunk设置(fig.asp = 1美元 ) ## ----------------------------------------------------------------------------- 库(BiocFileCache)均< - BiocFileCache威尔逊(“raw_data”,问= FALSE)。fname <- bfcrpath(bfc, file.path("ftp://ftp.ncbi.nlm.nih.gov/geo/series"， "GSE61nnn/GSE61533/suppl/GSE61533_HTSEQ_count_results.xls.gz") library(R.utils) wilson.name2 <- "GSE61533_HTSEQ_count_results.xls" gunzip(wilson. utils)fname, destname=wilson.name2, remove=FALSE, override =TRUE) library(readxl)所有。计数<- read_excel(wilson.name2) gene.names <- all。计数$ ID。counts <- as.matrix(all.counts[，-1]) rownames(all.counts) <- gene.names library(singlecel实验)hsc <- singlecel实验(list(counts=all.counts))是。spike <- grepl("^ERCC"， rownames(sce.hsc))hsc <- splitAltExps(sce. splitAltExps)hsc ifelse(。穗，"ERCC"， "基因"))库(散粒)sce。hsc <- addPerCellQC(sce.hsc)峰值。drop <- quickPerCellQC(colData(sce.hsc))HSC <- sce.hsc[，!Drop $discard]库(scran) scehsc <- computeSumFactors(sce.hsc) sce.hsc。hsc < - logNormCounts (sce.hsc ) ## ----------------------------------------------------------------------------- set.seed (100) var.cor < correlatePairs (sce。hsc子集。行= grep(“^ H2 - rownames (sce.hsc))) (var.cor ) ## ----------------------------------------------------------------------------- sig.cor < - var.cor罗斯福< = 0.05美元(sig.cor摘要 ) ## ----------------------------------------------------------------------------- correlatePairs (sce)。hsc子集。row=cbind("Fos"， "Jun")) ## ----fosjuncorplot, fig.cap=" HSC数据集中所有细胞的_Fos_表达与_Jun_表达的对比。"---- library(scater) plotExpression(sce. exe)hsc特性=“安全系数”,x = "小君 ") ## ----------------------------------------------------------------------------- ave.counts < - calculateAverage (sce.hsc)演示。Keep <- ave.counts >= 1 filtering .sce.hsc <- sce.hsc[演示。keep,] summary(demo.keep) ## ----------------------------------------------------------------------------- sessionInfo()