## ----setup, include = FALSE, cache = FALSE, message = FALSE------------------- library("knitr") ### Chunk选项:参见http://yihui.name/knitr/options/ ### ##文本结果opts_chunk$set(echo = TRUE, warning = TRUE, message = FALSE, include = TRUE) ## cache opts_chunk$set(cache = 3, cache。path = "output/cache/") ##绘制opts_chunk$set路径= " /数据输出 /") ## ---- eval = FALSE,消息= FALSE,结果= '隐藏 '------------------------- # (“ToxicoGx BiocManager:安装 ") ## ---- 消息= FALSE, fig.width = 8, fig.height = 3 -------------------------- 库(CoreGx)图书馆(ToxicoGx)图书馆(ggplot2) #加载tset数据(TGGATESsmall) ToxicoGx:: drugGeneResponseCurve (TGGATESsmall、持续时间= c(“2”,“8”,“24”),cell_lines =“肝细胞”,mDataTypes =“rna”特性=“ENSG00000140465_at剂量= c(“控制”,“低”,“中”，“高”)，药物=“四氯化碳”，ggplot_args =列表(实验室(标题=“四氯化碳对CYP1A1的影响”))，summarize_copies = FALSE) ## ---- echo = FALSE, out。宽度= " 500 px "----------------------------------------- knitr:: include_graphics (CS1_published.png ') ## ---- 结果=“黑名单”,警告= FALSE ---------------------------------------- 图书馆(xtable)数据(“TGGATESsmall”)#计算药物浓度的影响在分子细胞的药物。微动<- ToxicoGx:: drug微动sig (tSet = TGGATESsmall, mDataType = "rna"， cell_lines = "Hepatocyte"， duration = "24"， features = fNames(TGGATESsmall， "rna")， dose =c(" Control"， "Low")， drugs =c("奥美拉唑"，"异烟azid")， returnValues=c("estimate"，"tstat"， "pvalue"， "fdr")， verbose = FALSE) data(HCC_sig) res <- apply(drug。扰动[，，c("tstat"， "fdr")]， 2, function(x, HCC){返回(CoreGx::connectivityScore(x = x, y = HCC[， 2, drop = FALSE]， method = "fgsea"， nperm=100)}， HCC = HCC_sig[seq_len(195)，]) rownames(res) <- c("Connectivity"， "P Value") res <- t(res) res <- cbind(res，" fdr" = p.c adjust(res[，2]， method = "fdr") res <- res[order(res[，3])，] knitr::kable(res，标题= ' HCC和TG-GATEs PHH基因签名的Connectivity Score结果')