# #——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"))库(R.utils) wilson.name2 <- "GSE61533_HTSEQ_count_results.xls" gunzip(fname, destname=wilson.name2, remove=FALSE, overwrite=TRUE)库(readxl)count <- read_excel(wilson.name2) gene.names <- all。计数$ ID。count <- as.matrix(all.counts[，-1]) rownames(all.counts) <- gene.names library(singlecellexperexperiment)hsc <- singlecellexperexperiment (list(counts=all.counts))是。spike <- grepl("^ERCC"， rownames(sce.hsc))hsc < splitAltExps (sce。hsc ifelse(。穗，“ERCC”，“基因”))库(散布器)hsc <- addPerCellQC(sce.hsc) spike。drop <- quickPerCellQC(colData(sce.hsc))hsc < - sce.hsc[, !飙升。南加州爱迪生公司抛弃美元下降)库(食物)。sce.hsc <- computeSumFactors(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="在HSC数据集中的所有细胞中，_Fos_的表达与_Jun_的表达作对比。"(嘘)plotExpression (sce -库。hsc特性=“安全系数”,x = "小君 ") ## ----------------------------------------------------------------------------- ave.counts < - calculateAverage (sce.hsc)演示。Keep <- ave.counts >= 1 filter .sce.hsc <- sce.hsckeep,] summary(demo.keep) ## ----------------------------------------------------------------------------- sessionInfo()