# # # R代码从装饰图案的splineTimeR来源。Rnw“# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #代码块1号:splineTimeR。Rnw: 62 - 66 (eval = FALSE) # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # path1 < -“/用户/ hbraselmann / R / Bioc3.4dev /图书馆”# # # path2 < -“/图书馆/框架/ R.framework /版本/ 3.3 /资源/图书馆”# # #。libPaths (c (path1 path2) # # # .libPaths() # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #代码块2号:splineTimeR。Rnw: 69 - 72 # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #库(splineTimeR)数据(TCsimData)头(pData (TCsimData), 8) # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #代码块3号:splineTimeR。Rnw: 100 - 104 # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # diffExprs < splineDiffExprs (eSetObject = TCsimData df = 3, cutoff.adj。pVal = 0.01,参考= T1,拦截= TRUE)头(diffExprs, 3) # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #代码块数量4:splineTimeR。Rnw: 112 - 114 # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # splinePlot (eSetObject = TCsimData df = 3,参考=“T1”,如何= c (“EEF2”、“OR5W2”)) # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #代码块5号:splineTimeR。Rnw: 138 - 155 (eval = FALSE) # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #没有运行# # # # c2.all.v5.0.symbols下载.gmt文件”。格林尼治时间”(所有策划基因集,# # # #基因符号)的广泛,http://www.broad.mit.edu/gsea/downloads.jsp # # # # # msigdb,然后# # geneSets < - getGmt(“/道路/ / c2.all.v5.0.symbols.gmt”) # # # # # #加载ExpressionSet对象包含模拟时间进程数据数据(TCsimData) # # # # # # # # # #的差异表达基因检查diffExprs < splineDiffExprs (eSetObject = TCsimData df = 3, # # cutoff.adj。pVal = 0.01,参考= T1) # # # # # #使用差异表达的基因通路富集分析# # enrichPath <——pathEnrich (geneList = rownames (diffExprs) geneSets = geneSets宇宙# # = 6536)# # # #结束(不运行)# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #代码块6号:splineTimeR。Rnw: 160 - 171 (eval = FALSE) # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #不运行.gmt # # # #请下载并解压缩。ReactomePathways.gmt zip文件。邮政的# # # # (“Reactome通路基因设置”下“专用数据格式”)从# # # # Reactome网站http://www.reactome.org/pages/download-data/,然后# # geneSets < - getGmt(“/道路/ / ReactomePathways.gmt”)数据(TCsimData) # # # # diffExprs < splineDiffExprs (eSetObject = TCsimData df = 3, # # cutoff.adj。pVal = 0.01,参考= T1) # # enrichPath <——pathEnrich (geneList = rownames (diffExprs) geneSets = geneSets宇宙# # = 6536)# # # #结束(不运行)# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #代码块7号:single_igr # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # igr < splineNetRecon (eSetObject = TCsimData treatmentType = T2, probesForNR = rownames (diffExprs)截止。药物= 0.7,=方法“动态”)# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #代码块8号:plot_igr1 # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #情节(igr,顶点。标签= NA,顶点。大小= 3,主要= " igraph_0.7”) # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #代码块9号:two_igraphs # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # igr < splineNetRecon (eSetObject = TCsimData treatmentType = T2, probesForNR = rownames (diffExprs)截止。药物= c(0.8, 0.9),方法=“动态”)# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #代码块10号:plot_igrlist # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #情节(igr[[1]],顶点。标签= NA,顶点。size = 3, main = "igraph_0.8") plot(igr[[2]], vertex.label = NA, vertex.size = 3, main = "igraph_0.9") ################################################### ### code chunk number 11: splineTimeR.Rnw:233-238 (eval = FALSE) ################################################### ## library(FIs) ## data(FIs) ## names(FIs) ## head(FIs$FIs_Reactome) ## head(FIs$FIs_BioGRID) ################################################### ### code chunk number 12: splineTimeR.Rnw:243-248 ################################################### igr <- splineNetRecon(eSetObject = TCsimData, treatmentType = "T2", probesForNR = rownames(diffExprs), cutoff.ggm = c(0.7,0.8,0.9), method = "dynamic") scaleFreeProp <- networkProperties(igr) head(scaleFreeProp)