{"id":26009,"date":"2024-01-24T17:05:40","date_gmt":"2024-01-24T09:05:40","guid":{"rendered":"http:\/\/www.biocloudservice.com\/wordpress\/?p=26009"},"modified":"2024-01-24T17:05:41","modified_gmt":"2024-01-24T09:05:41","slug":"%e4%bf%9d%e5%a7%86%e7%ba%a7%e6%95%99%e7%a8%8b%ef%bc%81%ef%bc%81geo%e6%95%b0%e6%8d%ae%e9%9b%86%e8%8a%af%e7%89%87%e6%95%b0%e6%8d%ae%e7%9a%84%e6%8e%a2%e9%92%88id%e8%bd%ac%e6%8d%a2%ef%bc%81%ef%bc%81-2","status":"publish","type":"post","link":"http:\/\/www.biocloudservice.com\/wordpress\/?p=26009","title":{"rendered":"\u4fdd\u59c6\u7ea7\u6559\u7a0b\uff01\uff01GEO\u6570\u636e\u96c6\u82af\u7247\u6570\u636e\u7684\u63a2\u9488ID\u8f6c\u6362\uff01\uff01"},"content":{"rendered":"

\u5c0f\u4f19\u4f34\u4eec\u5f97\u5230GEO\u6570\u636e\u96c6\u539f\u59cb\u6570\u636e\u540e\uff0c\u53d1\u73b0\u5bc6\u5bc6\u9ebb\u9ebb\u7684\u57fa\u56e0\u8868\u8fbe\u4fe1\u606f\u4e0d\u77e5\u9053\u4ece\u54ea\u91cc\u4e0b\u624b\u3002\u800c\u4e14\u57fa\u56e0\u8868\u8fbe\u4fe1\u606f\u5f80\u5f80\u6709\u5f88\u591a\u6211\u4eec\u4e0d\u9700\u8981\u7684\u4fe1\u606f\uff0c\u5e76\u4e14\u57fa\u56e0\u8868\u8fbe\u8c31\u6570\u636e\u5f80\u5f80\u4e5f\u662f\u5c42\u6b21\u4e0d\u9f50\u3002\u5728\u8fd9\u91cc\u5c0f\u679c\u81ea\u5df1\u6574\u7406\u4e86\u4e00\u4efd\u4ee3\u7801\uff0c\u53ef\u4ee5\u628a\u57fa\u56e0\u8868\u8fbe\u8c31\u6574\u7406\u51fa\u6765\uff0c\u5e76\u4e14\u628a\u63a2\u9488ID\u4e5f\u8f6c\u6362\u5b8c\u6210\uff0c\u628a\u6570\u636e\u4e5f\u5f52\u4e00\u5316\u5904\u7406\u3002\u63a5\u4e0b\u6765\u8ddf\u7740\u5c0f\u679c\u53bb\u5b66\u4e60\u4e00\u4e0b\u5427\uff01<\/p>\n

\u5728\u8fd9\u91cc\u5c0f\u679c\u4f7f\u7528\u5b9e\u4f8b\u6570\u636eGSE63514,\u5e73\u53f0\u4e3aGPL-570\u3002\u5c0f\u4f19\u4f34\u53ef\u4ee5\u81ea\u884c\u5728GEO\u6570\u636e\u5e93\u4e2d\u4e0b\u8f7d\u3002\u4e0d\u8fc7\uff0c\u5c0f\u679c\u6559\u5927\u5bb6\u4e00\u4e2a\u5c0f\u6280\u5de7\uff1a<\/p>\n

\u5728\u5b98\u7f51\u641c\u5230\u81ea\u5df1\u9700\u8981\u7684GEO\u6570\u636e\u96c6\u540e\uff0c\u53ef\u4ee5\u5728<\/p>\n

<\/p>\n

\u8fd9\u4e2a\u9009\u9879\u4e2d\u9009\u62e9\u67e5\u770b\u4e00\u4e0b\u8fd9\u4e2a\u6570\u636e\u96c6\u4e2d\u542b\u6709\u90a3\u4e9b\u6837\u672c:<\/p>\n

<\/p>\n

<\/p>\n

\u6b64\u5916\uff0c\u5728 <\/p>\n

<\/p>\n

\u5f53\u6211\u4eec\u70b9\u51fbGPL\u5e73\u53f0\u540e\u4f1a\u51fa\u73b0\u4e00\u4e9b\u4fe1\u606f\u5728\u8fd9\u91cc\uff1a<\/p>\n

<\/p>\n

\u5982\u679c\u8fd9\u4e2a\u5e73\u53f0\u4fe1\u606f\u542b\u6709 \u90a3\u4e48\u6211\u4eec\u5904\u7406\u6570\u636e\u8d77\u6765\u5c31\u4f1a\u5f88\u65b9\u4fbf\uff0c\u5229\u7528Gene Symbol\u5c31\u53ef\u4ee5\u8f6c\u6362ID\u5f97\u5230\u6211\u4eec\u60f3\u8981\u7684\u57fa\u56e0\u540d\u79f0\u3002\u5c0f\u4f19\u4f34\u4eec\u4e00\u5b9a\u8981\u6ce8\u610f\uff0c\u5982\u679c\u6ca1\u6709\u8fd9\u4e2aSymbol\u4fe1\u606f\uff08\u6709\u7684\u5e73\u53f0\u53ef\u80fd\u53ea\u4f1a\u663e\u793aSymbol\uff09\uff0c\u5c0f\u679c\u8fd9\u91cc\u7684\u4ee3\u7801\u53ef\u80fd\u4e0d\u592a\u4f7f\u7528\u3002\u63a5\u4e0b\u6765\u6211\u4eec\u5c31\u8fdb\u5165\u6b63\u9898\u5427\uff01<\/p>\n

\u6211\u4eec\u5f97\u5230\u8fd9\u4e2a\u539f\u59cb\u6570\u636e\u96c6\uff0c\u5148\u5bfc\u5165\u5b83\u4eec\uff1a<\/p>\n

setwd(“E:\\\\\u751f\u4fe1\u679c”)<\/p>\n

Sys.setlocale(‘LC_ALL’,’C’)<\/p>\n

#\u8bfb\u53d6GPL\u6587\u4ef6<\/p>\n

GPL_table = read.table(‘E:\\\\\u751f\u4fe1\u679c\\\\GPL570-55999.txt’,sep = “\\t”,<\/p>\n

comment.char = “#”, stringsAsFactors = F,<\/p>\n

header = T, fill = TRUE, quote = “”)<\/p>\n

#\u8bfb\u53d6GSE\u6587\u4ef6<\/p>\n

GSE4100 <- read.table(‘E:\\\\\u751f\u4fe1\u679c\\\\GSE63514_series_matrix.txt’,sep = “\\t”,<\/p>\n

comment.char = “!”, stringsAsFactors = F,header = T, fill=TRUE)#43931<\/p>\n

#\u5bfc\u5165\u6587\u4ef6\uff0c\u6211\u4eec\u53ef\u4ee5\u67e5\u770b\u4e00\u4e0b\u5bfc\u5165\u7684\u6570\u636e\u5f62\u5f0f\u3002<\/p>\n

<\/p>\n

<\/p>\n

\u7ec6\u5fc3\u7684\u5c0f\u4f19\u4f34\u4f1a\u53d1\u73b0\uff0cID\u8fd9\u4e00\u5217\u4e0d\u662f\u6211\u4eec\u60f3\u8981\u7684Gene\u540d\uff0c\u8fd9\u5c31\u9700\u8981\u6211\u4eec\u5427ID\u8f6c\u5316\u4e00\u4e0b\u3002<\/p>\n

\u63a5\u4e0b\u6765\uff1a<\/p>\n

ID_Sybmol = GPL_table[,c(1,11)] #GPL\u5bf9\u5e94ID\u5217<\/p>\n

colnames(ID_Sybmol)[2]=”Symbol” #\u66f4\u6539\u540d\u79f0\u4e3aSymbol\uff0c\u4e3b\u8981\u662f\u4e3a\u4e86\u5bf9\u5176\u6c42\u5e73\u5747\u51fd\u6570<\/p>\n

c(1,11)\u8fd9\u91cc\u768411\u662fGPL\u5e73\u53f0\u8868\u683c\u91cc\u9762\uff0c\u4ee3\u8868\u7b2c11\u5217\uff0c\u5c0f\u679c\u8fd9\u91ccGeneSymbol\u662f11\u5217\uff0c\u6240\u4ee5\u8fd9\u91cc\u662f11\uff0c\u5c0f\u4f19\u4f34\u4eec\u9700\u8981\u6570\u4e00\u4e0b\u81ea\u5df1\u6570\u636eSymbol\u5728\u7b2c\u51e0\u5217\u3002<\/p>\n

\u63a5\u4e0b\u6765\uff1a<\/p>\n

#\u5408\u5e76ID\u4e0e\u57fa\u56e0\u5217<\/p>\n

Exp = merge(ID_Sybmol,GSE4100,by.x = “ID”,by.y = “ID_REF”,all=T) #45782\u4e2a<\/p>\n

Exp = Exp[,-1]<\/p>\n

View(Exp)#\u67e5\u770b\u4e00\u4e0b\u6570\u636e\u96c6<\/p>\n

<\/p>\n

\u8fd9\u6837\u4e00\u6765\u5c31\u5f97\u5230\u6211\u4eec\u60f3\u8981\u7684\u57fa\u56e0\u540d\u79f0\u4e86\uff0c\u4f46\u662f\u53c8\u51fa\u73b0\u4e00\u4e2a\u65b0\u7684\u95ee\u9898\uff0c\u57fa\u56e0\u540d\u6709\u91cd\u590d\u7684\uff0c\u800c\u4e14\u6709\u4e2a\u57fa\u56e0\u542b\u6709\u591a\u4e2a\uff0c\u8fd9\u8be5\u600e\u4e48\u529e\u5462\uff0c\u5c0f\u679c\u518d\u6559\u4e00\u62db\u3002\u5bf9\u6570\u636e\u8fc7\u6ee4\uff1a<\/p>\n

#\u6570\u636e\u8fc7\u6ee4\uff0c\u5bf9\u591a\u4f59\u7684\u57fa\u56e0\u8fdb\u884c\u5220\u9664<\/p>\n

Exp = Exp[Exp$Symbol != “”,] #<\/p>\n

Exp = na.omit(Exp) #<\/p>\n

#\u53bb\u9664\u591a\u4f59\u7684\u57fa\u56e0\uff0c<\/p>\n

Exp1 = data.frame(Exp[-grep(“\/”,Exp$”Symbol”),]) #\u53bb\u4e00\u5bf9\u591a\uff0cgrep\u662f\u5305\u542b\u7684\u610f\u601d\uff0c-\u5c31\u662f\u4e0d\u5305\u542b<\/p>\n

write.table(Exp1,”Exp1.txt”,row.names = F,quote = F,sep=”\\t”)<\/p>\n

\u90a3\u4e48\u8fd9\u91cc<\/p>\n

\u5c31\u5f97\u5230\u5e72\u51c0\u7684\u57fa\u56e0\u8868\u8fbe\u8c31<\/p>\n

<\/p>\n

\u4f46\u662f\uff0c\u6709\u7684\u5c0f\u4f19\u4f34\u4ed6\u7684\u57fa\u56e0\u8868\u8fbe\u8c31\u4e2d\u6570\u636e\u6709\u7684\u5f02\u5e38\u7684\u5927\uff0c\u90a3\u4e48\u5c31\u9700\u8981\u5bf9\u6570\u636e\u5f52\u4e00\u5316\u3002<\/p>\n

\u63a5\u4e0b\u6765\u5c0f\u679c\u5728\u7ee7\u7eed\u6559\u5927\u5bb6\u5982\u4f55\u628a\u6570\u636e\u96c6\u505a\u5e73\u5747\u503c\u5904\u7406\uff0c\u8fd9\u91cc\u9700\u8981\u7528\u5230for\u5faa\u73af\u5904\u7406\u6570\u636e\u3002<\/p>\n

#\u6c42\u5e73\u5747\u503c<\/p>\n

meanfun <- function(x) {<\/p>\n

x1 <- data.frame(unique(x[,1]))<\/p>\n

colnames(x1) <- c(“Symbol”)<\/p>\n

for (i in 2:ncol(x)){<\/p>\n

x2 <- data.frame(tapply(x[,i],x[,1],mean))<\/p>\n

x2[,2] <- rownames(x2)<\/p>\n

colnames(x2) <- c(colnames(x)[i], “Symbol”)<\/p>\n

x1 <- merge(x1,x2,by.x = “Symbol”,by.y = “Symbol”,all=FALSE)<\/p>\n

}<\/p>\n

return(x1)<\/p>\n

}<\/p>\n

Exp2 <- meanfun(Exp1)<\/p>\n

\u8fd9\u91cc\u6570\u636e\u5c31\u4f1a\u53d8\u89c4\u6574\u5f88\u591a\u3002<\/p>\n

\u6211\u4eec\u4f7f\u7528\u67f1\u72b6\u56fe\u5c55\u793a\u6570\u636e\u5f62\u5f0f<\/p>\n

# \u67e5\u770b\u6570\u636e<\/p>\n

par(cex = 0.7)<\/p>\n

n.sample=ncol(Exp2[,-1])<\/p>\n

if(n.sample>40) par(cex = 0.5)<\/p>\n

cols <- rainbow(n.sample*1.2)<\/p>\n

boxplot(Exp2[,-1], col = cols,main=”expression value”,las=2)<\/p>\n

write.table(Exp2,”Exp_Original.txt”,row.names = F,quote = F,sep=”\\t”)<\/p>\n

row.names(Exp2) = Exp2[,1]<\/p>\n

Exp2 = log(Exp2[,-1])<\/p>\n

par(cex = 0.7)<\/p>\n

n.sample=ncol(Exp2)<\/p>\n

if(n.sample>40) par(cex = 0.5)<\/p>\n

cols <- rainbow(n.sample*1.2)<\/p>\n

boxplot(Exp2, col = cols,main=”expression value”,las=2)<\/p>\n

Symbol = row.names(Exp2)<\/p>\n

Exp_test = cbind(Symbol,Exp2)<\/p>\n

write.table(Exp_test,”Exp.txt”,row.names = F,quote = F,sep=”\\t”)<\/p>\n

\u6700\u7ec8\u5f97\u5230\u7684\u6570\u636e\u96c6\u5c31\u662f\u6211\u4eec\u60f3\u8981\u7684\u57fa\u56e0\u8868\u8fbe\u8c31\u4e86\uff0c\u5c0f\u4f19\u4f34\u53ef\u4ee5\u4f7f\u7528\u5f97\u5230\u7684\u57fa\u56e0\u8868\u8fbe\u8c31\u505a\u540e\u7eed\u7684\u5206\u6790\u5566\uff01<\/p>\n

\u5c0f\u679c\u8fd9\u91cc\u63d0\u9192\u4e00\u4e0b\uff0c\u6709\u7684\u6570\u636e\u96c6\u4e0d\u9700\u8981\u505a\u5f52\u4e00\u5316\u5904\u7406\uff0c\u5c0f\u4f19\u4f34\u8981\u6e05\u695a\u81ea\u5df1\u60f3\u8981\u5f97\u5230\u90a3\u4e2a\u57fa\u56e0\u8868\u8fbe\u8c31\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"

\u5c0f\u4f19\u4f34\u4eec\u5f97\u5230GEO\u6570\u636e\u96c6\u539f\u59cb\u6570\u636e\u540e\uff0c\u53d1\u73b0\u5bc6\u5bc6\u9ebb\u9ebb\u7684\u57fa\u56e0\u8868\u8fbe\u4fe1\u606f\u4e0d\u77e5\u9053\u4ece\u54ea\u91cc\u4e0b\u624b\u3002\u800c\u4e14\u57fa\u56e0\u8868\u8fbe\u4fe1\u606f\u5f80\u5f80\u6709\u5f88\u591a\u6211\u4eec […]<\/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\/26009"}],"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=26009"}],"version-history":[{"count":1,"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=\/wp\/v2\/posts\/26009\/revisions"}],"predecessor-version":[{"id":26022,"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=\/wp\/v2\/posts\/26009\/revisions\/26022"}],"wp:attachment":[{"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=26009"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=26009"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=26009"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}