# # # R代码从装饰图案的dataPrep来源。Rnw“# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #代码块1号:开始# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #选项(宽度= 80)# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #代码块2号:开始# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #库(计)# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #代码块3号:演示。数据# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #文件名=执行(“extdata / gse16873.demo”、包=“规”)演示。data = readExpData(文件名,row.names = 1) #检查数据头(demo.data) str (demo.data) # data.frame转换为一个矩阵,加快计算demo.data = as.matrix (demo.data) str (demo.data) # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #代码块数量4:readList # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #一个例子基因设置数据来源于MSigDB数据文件名=格林尼治时间执行(“extdata / c2.demo.gmt”、包=“规”)demo.gs = readList(文件名)演示。gs[1:3] #与gse16873使用这些基因集,需要基因符号#先Entrez IDs数据转换(egSymb) demo.gs.sym < -lapply(演示。gs, demo.gs sym2eg)。信谊(1:3)# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #代码块5号:gse16873。affyid # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #库(gageData)数据(gse16873.affyid) affyid = rownames (gse16873.affyid)库(hgu133a.db) egids2 = hgu133aENTREZID [affyid] annots = toTable (egids2) str (annots) gse16873.affyid = gse16873。affyid [annots probe_id美元]#如果多个探针集映射到一个基因,选择一个最大差差= (gse16873申请。affyid 1位差)sel.rn = tapply (1: nrow (annots) annots gene_id美元,函数(x) {x [which.max (IQR [x])]}) gse16873.egid = gse16873.affyid[选取。rn,] rownames (gse16873.egid) =名字(sel.rn) cn = colnames (gse16873.egid) hn = grep (cn,接下来的忽视。例= T) dcis = grep (dcis, cn,忽视。(kegg.gs) gse16873.kegg.p = T)数据。affy < -计(gse16873。egid gsets = kegg。gs, ref = hn,桑普= dcis) #结果应该类似于使用gse16873 # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #代码块6号:pathview。转换# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #库(pathview)数据(bod)打印(bod) #模拟人类表达数据与RefSeq RefSeq ID。数据< - sim.mol.data(摩尔。type = "基因",id.type =“REFSEQ nexp = 2, nmol = 1000) #构造之间的映射non-Entrez ID和id.map Entrez基因ID。refseq < - id2eg (id = rownames (refseq.data),类别=“refseq org =“海关”)#地图数据到Entrez基因id,注意不同的总和。方法可以可以使用。数据< - mol.sum(摩尔。data = refseq。data, id.map = id.map.refseq, sum.method = "mean")