{"id":25806,"date":"2024-01-23T17:20:50","date_gmt":"2024-01-23T09:20:50","guid":{"rendered":"http:\/\/www.biocloudservice.com\/wordpress\/?p=25806"},"modified":"2024-01-23T17:20:52","modified_gmt":"2024-01-23T09:20:52","slug":"%e8%b7%9f%e7%9d%80%e5%b0%8f%e6%9e%9cget%e6%97%a0%e7%9b%91%e7%9d%a3%e8%81%9a%e7%b1%bb%ef%bc%81-consensusclusterplus","status":"publish","type":"post","link":"http:\/\/www.biocloudservice.com\/wordpress\/?p=25806","title":{"rendered":"\u8ddf\u7740\u5c0f\u679cGet\u65e0\u76d1\u7763\u805a\u7c7b\uff01-ConsensusClusterPlus"},"content":{"rendered":"

\u5c0f\u4f19\u4f34\u5728\u505a\u751f\u4fe1\u5206\u6790\u7684\u65f6\u5019\uff0c\u4f1a\u7ecf\u5e38\u89c1\u5230\u805a\u7c7b\u8fd9\u4e2a\u540d\u8bcd\uff0c\u5374\u4e0d\u77e5\u9053\u662f\u4ec0\u4e48\u610f\u4e49\u3002\u5176\u5b9e\u5e73\u65f6\u6211\u4eec\u505a\u57fa\u56e0\u70ed\u56fe\u65f6\u5019\u5c31\u7528\u5230\u4e86\u805a\u7c7b\u7684\u601d\u60f3\u3002\u6709\u7684\u5c0f\u4f19\u4f34\u5728\u505a\u764c\u75c7\u5206\u6790\u65f6\u5019\uff0c\u4e5f\u89c1\u8fc7\u7ed9\u75be\u75c5\u505a\u5206\u5b50\u4e9a\u578b\uff0c\u8fd9\u4e2a\u65f6\u5019\u65e0\u76d1\u7763\u805a\u7c7b\u5c31\u6d3e\u4e0a\u7528\u573a\u4e86\u3002<\/p>\n

\u6240\u4ee5\u4eca\u5929\u5c0f\u679c\u5e26\u5927\u5bb6\u4e86\u89e3\u65e0\u76d1\u7763\u805a\u7c7b\uff0c\u5e76\u5b66\u4e60\u5982\u4f55\u4f7f\u7528\u4ed6\u3002<\/p>\n

\u9996\u5148\u6211\u4eec\u5148\u5927\u81f4\u4e86\u89e3\u4e00\u4e0b\u4ec0\u4e48\u662f\u65e0\u76d1\u7763\u805a\u7c7b\u3002\u5c31\u597d\u6bd4\u4e00\u81f4\u6027\u805a\u7c7b\u65b9\u6cd5\u5305\u62ec\u4ece\u4e00\u7ec4\u9879\u76ee\u4e2d\u8fdb\u884c\u6b21\u62bd\u6837\uff0c\u4f8b\u5982\u5fae\u9635\u5217\uff0c\u5e76\u786e\u5b9a\u7279\u5b9a\u7c07\u8ba1\u6570\uff08k\uff09\u7684\u7c07\u3002\u7136\u540e\uff0c\u5bf9\u5171\u8bc6\u503c\uff0c\u4e24\u4e2a\u9879\u76ee\u5360\u5728\u540c\u4e00\u5b50\u6837\u672c\u4e2d\u53d1\u751f\u7684\u6b21\u6570\u4e2d\u6709\u76f8\u540c\u7684\u805a\u7c7b\uff0c\u8ba1\u7b97\u5e76\u5b58\u50a8\u5728\u6bcf\u4e2ak\u7684\u5bf9\u79f0\u4e00\u81f4\u77e9\u9635\u4e2d\u3002<\/p>\n

\u5177\u4f53\u7684\u542b\u4e49\u6211\u4eec\u4e0d\u5728\u6b64\u4e00\u4e00\u8d58\u8ff0\u3002<\/p>\n

\u5c0f\u679c\u5728\u8fd9\u91cc\u7528\u5230\u7684\u662fConsensusClusterPlus\u8fd9\u4e2a\u5305\u5bf9\u57fa\u56e0\u8fdb\u884c\u805a\u7c7b\u3002<\/p>\n

\u6240\u9700\u8981\u7684\u662f\u4e0b\u9762\u8fd9\u79cd\u683c\u5f0f\u7684\u57fa\u56e0\u8868\u8fbe\u8c31\uff1a<\/p>\n

<\/p>\n

#install.packages(“BiocManager”)<\/p>\n

#BiocManager::install(‘ConsensusClusterPlus’)#\u5c0f\u4f19\u4f34\u6ca1\u6709\u7684\u81ea\u5df1\u8981\u4e0b\u8f7d\u4e00\u4e0b<\/p>\n

library(tidyverse)<\/p>\n

library(ConsensusClusterPlus)<\/p>\n

#\u5bfc\u5165\u6570\u636e<\/p>\n

exp <- read.table(“text1.txt”,sep = “\\t”,row.names = 1,check.names = F,stringsAsFactors = F,header = T)<\/p>\n

d=as.matrix(exp)<\/p>\n

gene <- c(“MMP9″,”CCND1″,”STAT1″,”AR”,”AKR1C3″,”GSTP1″,”PGR”)<\/p>\n

d <- d[gene,]<\/p>\n

mads=apply(d,1,mad)<\/p>\n

d=d[rev(order(mads))[1:7],] #7\u662f\u57fa\u56e0\u4e2a\u6570<\/p>\n

d = sweep(d,1, apply(d,1,median,na.rm=T))<\/p>\n

title=(“JULEI”) ##\u6587\u4ef6\u5939\u8f93\u51fa\u56fe\u7247\u7684\u4f4d\u7f6e<\/p>\n

set.seed(1) #\u6211\u53d1\u73b0\u8bbe\u4e0d\u8bbe\u7f6e\u79cd\u5b50\u90fd\u4e00\u6837<\/p>\n

#\u8fd9\u91cc\u5c0f\u679c\u9009\u53d6\u81ea\u5df1\u7684\u793a\u4f8b\u6570\u636e\uff0c\u5c0f\u4f19\u4f34\u4eec\u6574\u7406\u81ea\u5df1\u60f3\u53bb\u805a\u7c7b\u7684\u57fa\u56e0\u3002<\/p>\n

\u7136\u540e\u6211\u4eec\u6253\u5f00JULEI\u8fd9\u4e2a\u6587\u4ef6\u5939\u4f1a\u53d1\u73b0\u5f97\u5230\u4e86\u805a\u7c7b\u7684\u7ed3\u679c\uff1a
\n\u4e00\u81f4\u6027\u77e9\u9635<\/h3>\n

\u4e00\u81f4\u6027\u7d2f\u79ef\u5206\u5e03\u51fd\u6570\u56fe<\/h3>\n

\u788e\u77f3\u56fe<\/h3>\n

<\/p>\n

\u5728\u8fd9\u91cc\u5c0f\u679c\u5c31\u4e0d\u5168\u90e8\u5c55\u793a\u4e86\uff0c\u5c0f\u4f19\u4f34\u4eec\u81ea\u5df1\u505a\u7684\u8bdd\u53ef\u4ee5\u6162\u6162\u770b\u3002<\/p>\n

\u4ece\u4e0a\u8ff0\u788e\u77f3\u56fe\u770b\u51fa\u5462\uff0c\u5728k=7,k=8\u5de6\u53f3\u65f6\u5019\u5462\uff0c\u6bd4\u8f83\u5e73\u7a33\uff0c\u524d\u9762K=3\uff0c\u548ck=4\u8fd9\u4e24\u4e2a\u5206\u7ec4\u6570\u95f4\u76f8\u5bf9\u5dee\u503c\u53d8\u5316\u8d8a\u5927\uff0c\u8bf4\u660e\u8be5\u5206\u7ec4\u8d8a\u6709\u4ef7\u503c\u3002\u5c0f\u4f19\u4f34\u9700\u8981\u5bf9\u75c7\u4e0b\u836f\uff0c\u67e5\u770b\u81ea\u5df1\u805a\u7c7b\u7684\u7ed3\u679c\u8fdb\u884c\u89e3\u91ca\u548c\u540e\u7eed\u7684\u5206\u6790\u3002<\/p>\n

\u56fe\u4e2dK\u503c\u5462\u5c31\u4ee3\u8868\u7c07\uff0c<\/p>\n

\u63a5\u4e0b\u6765\u6211\u4eec\u7ed8\u5236\u53e6\u4e00\u7ec4\u56fe\uff1a<\/p>\n

\u805a\u7c7b\u4e00\u81f4\u6027(cluster-consensus)\u4ee5\u53ca\u6837\u54c1\u4e00\u81f4\u6027(item-consensus)<\/p>\n

title=title,clusterAlg=”hc”,distance=”pearson”,seed=1,plot=”pdf”)<\/p>\n

results[[2]][[“consensusMatrix”]][1:5,1:5]<\/p>\n

results[[2]][[“consensusTree”]]<\/p>\n

results[[2]][[“consensusClass”]][1:5]<\/p>\n

icl = calcICL(results,title=title,plot=”pdf”) ##\u753b\u53e6\u4e00\u7ec4\u56fe\u7247<\/p>\n

\u7ed3\u679c\u5982\u4e0b\uff1a<\/p>\n

\u805a\u7c7b\u4e00\u81f4\u6027(cluster-consensus)<\/p>\n

<\/p>\n

\u6837\u54c1\u4e00\u81f4\u6027(item-consensus)<\/p>\n

<\/p>\n

\u5c0f\u4f19\u4f34\u4eec\u628a\u9700\u8981\u90a3\u4e9b\u56fe\u7247\u8fdb\u884c\u5c55\u793a\u5c31\u53ef\u4ee5\u4e86\u3002<\/p>\n

#\u4e0a\u8ff0\u5c31\u662f\u7ed8\u5236\u53e6\u4e00\u7ec4\u56fe\uff0c\u7136\u800c\u6211\u4eec\u8fd8\u9700\u8981\u505a\u7684\u662f\u628a\u7ed3\u679c\u4fdd\u5b58\u4e0b\u6765\u3002<\/p>\n

group<-results[[2]][[“consensusClass”]]<\/p>\n

group<-as.data.frame(group)<\/p>\n

group$group <- factor(group$group,levels=c(1,2))<\/p>\n

save(group,file = “group_AY.Rda”)#\u8fd9\u91cc\u628a\u5206\u7ec4\u7ed3\u679c\u4fdd\u5b58<\/p>\n

\u7136\u800c\uff0c\u53c8\u4f1a\u6709\u5c0f\u4f19\u4f34\u4f1a\u95ee\u5982\u4f55\u5c55\u793a\u805a\u7c7b\u540e\u7684\u6548\u679c\u5462\u3002<\/p>\n

\u5c0f\u679c\u5728\u8fd9\u91cc\u6559\u5927\u5bb6\u4e00\u79cd\u65b9\u5f0f\u7528\u70ed\u56fe\u7684\u65b9\u5f0f\u8fdb\u5c55\u5c55\u793a\uff0c<\/p>\n

\u7ed8\u5236ConsensusClusterPlus\u540e\u7684\u70ed\u56fe\uff1a<\/p>\n

\u8fd9\u4e2a\u65f6\u5019\u5c31\u7528\u5230\u4e0a\u8ff0\u54b1\u4eec\u4fdd\u5b58\u7684\u5206\u7ec4\u4fe1\u606f\u4e86\uff1a<\/p>\n

\u8ddf\u7740\u5c0f\u679c\u7684\u4ee3\u7801\u5f80\u4e0b\u8dd1\u5c31\u53ef\u4ee5\u5566\uff01<\/p>\n

library(pheatmap)#\u8c03\u7528\u4e00\u4e0b\u70ed\u56fe\u7684\u5305<\/p>\n

group <- group %>%<\/p>\n

rownames_to_column(“sample”)<\/p>\n

annotation <- group %>% arrange(group) %>% column_to_rownames(“sample”)<\/p>\n

a <- group %>% arrange(group) %>% mutate(sample=substring(.$sample,1,12))<\/p>\n

b <- t(exp_gene) %>%<\/p>\n

as.data.frame() %>%<\/p>\n

rownames_to_column(“sample”) %>%<\/p>\n

mutate(sample=substring(.$sample,1,12))<\/p>\n

c <- inner_join(a,b,”sample”) %>% .[,-2] %>% column_to_rownames(“sample”) %>% t(.)<\/p>\n

pheatmap(c,annotation = annotation,<\/p>\n

cluster_cols = F,fontsize=5,fontsize_row=5,<\/p>\n

scale=”row”,show_colnames=F,<\/p>\n

fontsize_col=3)<\/p>\n

bk <- c(seq(-5,-0.1,by=0.01),seq(0,5,by=0.01))<\/p>\n

pheatmap(c,annotation = annotation,<\/p>\n

annotation_colors = list(group = c(“1″ =”#8B1C62”,”2″= “#EE9572″)),<\/p>\n

cluster_cols = F,fontsize=10,fontsize_row=10,<\/p>\n

scale=”row”,show_colnames=F,cluster_row = F,<\/p>\n

color = c(colorRampPalette(colors = c(“#551A8B”,”white”))(length(bk)\/2),colorRampPalette(colors = c(“white”,”#CD3700″))(length(bk)\/2)),<\/p>\n

#legend_breaks=seq(-3,3,1),<\/p>\n

fontsize_col=3)<\/p>\n

dev.off()<\/p>\n

\u8fd9\u91cc\u70ed\u56fe\u7684\u53c2\u6570\u6bd4\u5982\uff1a\u989c\u8272\u7684\u7ed8\u5236\u90fd\u53ef\u4ee5\u6839\u636e\u5c0f\u4f19\u4f34\u81ea\u5df1\u7684\u9700\u6c42\u6765\u4fee\u6539\uff0c<\/p>\n

<\/p>\n

\u6548\u679c\u5c31\u51fa\u6765\u4e86\uff0c\u53ef\u4ee5\u770b\u51fa\u6765\u5728MMP9\u548cCCND1\u7b49\u8fd9\u51e0\u4e2a\u57fa\u56e0\u805a\u7c7b\u6548\u679c\u6bd4\u8f83\u660e\u663e\uff0c\u5c0f\u679c\u5728\u8fd9\u91cc\u5c55\u793a\u7684\u662fK=2\u60c5\u51b5\u4e0b\u805a\u7c7b\u7684\u70ed\u56fe\u3002\u5c0f\u4f19\u4f34\u4eec\u81ea\u5df1\u9009\u62e9K\u7684\u503c\u8fdb\u884c\u7ed8\u5236\u3002<\/p>\n

\u4e0b\u9762\u5c31\u53ef\u4ee5\u6839\u636e\u805a\u7c7b\u7684\u7ed3\u679c\u53bb\u540e\u7eed\u7684\u5206\u6790\u4e86\u3002\u6bd4\u5982;\u5206\u7ec4\u7684ssGSEA\u7b49\u7b49<\/p>\n

\u5c0f\u4f19\u4f34\u4eec\u9700\u8981\u591a\u591a\u5b66\u4e60\u4ee3\u7801\u7684\u542b\u4e49\uff0c\u4ee5\u53ca\u5bf9\u56fe\u7247\u7684\u7406\u89e3\u624d\u80fd\uff0c\u66f4\u597d\u7684\u53bb\u8fd0\u7528\u3002<\/p>\n

\u4e0a\u8ff0\u5c31\u662f\u5bf9\u65e0\u76d1\u7763\u805a\u7c7b\u6cd5\u7684\u5b66\u4e60\u3002\u5c0f\u4f19\u4f34\u4eec\u662f\u5426\u5b66\u4f1a\u4e86\u5462<\/p>\n","protected":false},"excerpt":{"rendered":"

\u5c0f\u4f19\u4f34\u5728\u505a\u751f\u4fe1\u5206\u6790\u7684\u65f6\u5019\uff0c\u4f1a\u7ecf\u5e38\u89c1\u5230\u805a\u7c7b\u8fd9\u4e2a\u540d\u8bcd\uff0c\u5374\u4e0d\u77e5\u9053\u662f\u4ec0\u4e48\u610f\u4e49\u3002\u5176\u5b9e\u5e73\u65f6\u6211\u4eec\u505a\u57fa\u56e0\u70ed\u56fe\u65f6\u5019\u5c31\u7528\u5230\u4e86\u805a\u7c7b\u7684 […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":""},"categories":[1],"tags":[],"jetpack_featured_media_url":"","_links":{"self":[{"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=\/wp\/v2\/posts\/25806"}],"collection":[{"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=25806"}],"version-history":[{"count":1,"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=\/wp\/v2\/posts\/25806\/revisions"}],"predecessor-version":[{"id":25815,"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=\/wp\/v2\/posts\/25806\/revisions\/25815"}],"wp:attachment":[{"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=25806"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=25806"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=25806"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}