{"id":61671,"date":"2024-11-19T15:30:43","date_gmt":"2024-11-19T07:30:43","guid":{"rendered":"http:\/\/www.biocloudservice.com\/wordpress\/?p=61671"},"modified":"2024-11-19T15:30:43","modified_gmt":"2024-11-19T07:30:43","slug":"%e5%af%8c%e9%9b%86%e5%88%86%e6%9e%90%e5%9b%be%e8%bf%98%e8%83%bd%e8%bf%99%e6%a0%b7%e7%94%bb%ef%bc%9f%e5%b0%8f%e8%8a%b1%e6%95%99%e4%bd%a0%e7%94%bb%e5%a5%bd%e7%9c%8b%e7%9a%84%e5%af%8c%e9%9b%86%e7%bb%93","status":"publish","type":"post","link":"http:\/\/www.biocloudservice.com\/wordpress\/?p=61671","title":{"rendered":"\u5bcc\u96c6\u5206\u6790\u56fe\u8fd8\u80fd\u8fd9\u6837\u753b\uff1f\u5c0f\u82b1\u6559\u4f60\u753b\u597d\u770b\u7684\u5bcc\u96c6\u7ed3\u679c\u56fe"},"content":{"rendered":"\n

<\/h1>\n\n\n\n

\u76f8\u4fe1\u5927\u5bb6\u90fd\u4f1a\u505a\u5bcc\u96c6\u5206\u6790\uff0c\u4f46\u662f\u4f60\u4f1a\u628a\u5bcc\u96c6\u5206\u6790\u7684\u7ed3\u679c\u7f8e\u89c2\u3001\u5168\u9762\u5730\u5c55\u793a\u51fa\u6765\u5417\uff1f\u4e00\u4e2a\u597d\u7684\u5206\u6790\u7ed3\u679c\u56fa\u7136\u91cd\u8981\uff0c\u4e00\u4e2a\u597d\u7684\u7ed3\u679c\u56fe\u4e5f\u540c\u6837\u91cd\u8981\uff0c\u7ed3\u679c\u56fe\u53ef\u4ee5\u8ba9\u8bfb\u8005\u5bf9\u4f60\u7684\u5206\u6790\u7ed3\u679c\u4e00\u76ee\u4e86\u7136\uff0c\u8d4f\u5fc3\u60a6\u76ee\u7684\u56fe\u7247\u4e5f\u53ef\u4ee5\u63d0\u5347\u4f60\u7684\u6587\u7ae0\u7684\u6863\u6b21\u3002\u5927\u5bb6\u5bf9\u5206\u6790\u6d41\u7a0b\u90fd\u80f8\u6709\u6210\u7af9\uff0c\u4f46\u662f\u53ef\u80fd\u4f1a\u56e0\u4e0d\u77e5\u9053\u5982\u4f55\u66f4\u597d\u5730\u5c06\u7ed3\u679c\u5c55\u73b0\u51fa\u6765\u800c\u82e6\u607c\u3002\u522b\u62c5\u5fc3\uff0c\u4eca\u5929\u5c0f\u82b1\u5c31\u5e26\u5927\u5bb6\u7ed8\u5236\u4e00\u79cd\u7f8e\u89c2\u7684\u5bcc\u96c6\u5206\u6790\u7ed3\u679c\u56fe\u3002\u8981\u662f<\/strong>\u60a8<\/strong>\u6709\u81ea\u5df1\u505a\u4e0d\u4e86\u7684\u751f\u4fe1\u5206\u6790\uff0c\u53ef\u4ee5\u8054\u7cfb<\/strong>\u6211\uff0c\u5982\u679c\u60a8\u7684\u6570\u636e\u91cf\u6bd4\u8f83\u5927\u4e5f\u53ef\u4ee5\u8054\u7cfb\u5c0f\u82b1\u79df\u8d41\u9ad8\u6027\u4ef7\u6bd4\u7684\u670d\u52a1\u5668\u54e6<\/strong>\u3002<\/strong><\/strong><\/p>\n\n\n\n

\u8fd9\u662f\u4e00\u4e2a\u666e\u901a\u7684\u5bcc\u96c6\u5206\u6790\u548c\u4e00\u5f20\u666e\u901a\u7684\u5bcc\u96c6\u6761\u5f62\u56fe\uff1a<\/p>\n\n\n\n

## \u666e\u901a\u7684\u5bcc\u96c6\u5206\u6790\u7ed3\u679c\u56fe<\/p>\n\n\n\n

## \u8bfb\u8fdb\u5dee\u5f02\u5206\u6790\u7ed3\u679c<\/p>\n\n\n\n

allDiff = read.csv(“..\/input\/DEGs.csv”, row.names = 1)<\/p>\n\n\n\n

## \u8bbe\u7f6e\u5dee\u5f02\u9608\u503c\u4e3apvalue<0.05 & abs(log2FC)>0.585<\/p>\n\n\n\n

allDiff$trend = ifelse(allDiff$pvalue<0.05 & abs(allDiff$logFC)>=0.585,<\/p>\n\n\n\n

ifelse(allDiff$logFC>0, “up”, “down”), “stable”)<\/p>\n\n\n\n

up_gene = allDiff$gene[which(allDiff$trend==”up”)]<\/p>\n\n\n\n

down_gene = allDiff$gene[which(allDiff$trend==”down”)]<\/p>\n\n\n\n

## \u5bf9\u4e0a\u8c03\u57fa\u56e0\u505aGO\u5bcc\u96c6\u5206\u6790<\/p>\n\n\n\n

library(clusterProfiler) #\u5bcc\u96c6\u5206\u6790\u4e3b\u8981\u7684\u5305<\/p>\n\n\n\n

library(org.Hs.eg.db)#\u67e5\u627e\u7269\u79cd\u6ce8\u91ca\u4fe1\u606f<\/p>\n\n\n\n

library(ggplot2)#\u5206\u9762\u7ed8\u56fe\u6240\u9700<\/p>\n\n\n\n

library(dplyr)#\u6574\u7406\u6570\u636e<\/p>\n\n\n\n

library(ggsci)#\u914d\u8272<\/p>\n\n\n\n

library(showtext)<\/p>\n\n\n\n

library(scico)<\/p>\n\n\n\n

Genes <- bitr(up_gene,  <\/p>\n\n\n\n

fromType = “SYMBOL”, #\u8f93\u5165\u6570\u636e\u7684\u7c7b\u578b<\/p>\n\n\n\n

toType = c(“ENTREZID”), #\u8981\u8f6c\u6362\u7684\u6570\u636e\u7c7b\u578b<\/p>\n\n\n\n

OrgDb = org.Hs.eg.db)<\/p>\n\n\n\n

# \u5bcc\u96c6\u5206\u6790 ——————————————————————–<\/p>\n\n\n\n

GO <- enrichGO(gene = Genes$ENTREZID, #\u8f93\u5165\u57fa\u56e0\u7684”ENTREZID”<\/p>\n\n\n\n

OrgDb = org.Hs.eg.db,#\u6ce8\u91ca\u4fe1\u606f<\/p>\n\n\n\n

keyType = “ENTREZID”,<\/p>\n\n\n\n

ont = “all”,     #\u53ef\u9009\u6761\u76eeBP\/CC\/MF<\/p>\n\n\n\n

pAdjustMethod = “BH”, #p\u503c\u7684\u6821\u6b63\u65b9\u5f0f<\/p>\n\n\n\n

pvalueCutoff = 1,   #pvalue\u7684\u9608\u503c<\/p>\n\n\n\n

qvalueCutoff = 1, #qvalue\u7684\u9608\u503c<\/p>\n\n\n\n

minGSSize = 5,<\/p>\n\n\n\n

maxGSSize = 5000,<\/p>\n\n\n\n

readable = TRUE)   #\u662f\u5426\u5c06entrez id\u8f6c\u6362\u4e3asymbol<\/p>\n\n\n\n

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

## \u663e\u8457\u5bcc\u96c6\u9608\u503c\u662fp.adjust<0.05\uff0ccount>=2<\/p>\n\n\n\n

GO_sig = GO_result[which(GO_result$p.adjust<0.05 & GO_result$Count>=2),]<\/p>\n\n\n\n

# \u6311\u9009\u6bcf\u4e2a\u5206\u7c7b\u4e2d\u524d5\u663e\u8457\u7684\u6761\u76ee<\/p>\n\n\n\n

BP_top5 <- GO_sig %>%<\/p>\n\n\n\n

filter(ONTOLOGY == “BP”) %>%  <\/p>\n\n\n\n

arrange(p.adjust) %>%        <\/p>\n\n\n\n

head(5)                     <\/p>\n\n\n\n

CC_top5 <- GO_sig %>%<\/p>\n\n\n\n

filter(ONTOLOGY == “CC”) %>%  <\/p>\n\n\n\n

arrange(p.adjust) %>%      <\/p>\n\n\n\n

head(5)                 <\/p>\n\n\n\n

MF_top5 <- GO_sig %>%<\/p>\n\n\n\n

filter(ONTOLOGY == “MF”) %>%<\/p>\n\n\n\n

arrange(p.adjust) %>%       <\/p>\n\n\n\n

head(5)                  <\/p>\n\n\n\n

top5 <- rbind(BP_top5,CC_top5,MF_top5)<\/p>\n\n\n\n

top5$ONTOLOGY <- factor(top5$ONTOLOGY, levels = c(“BP”, “CC”,”MF”))<\/p>\n\n\n\n

top5$logPvalue <- (-log(top5$p.adjust))<\/p>\n\n\n\n

top5$log10P.adjust <- (-log10(top5$p.adjust))<\/p>\n\n\n\n

# \u7f8e\u5316\u7248\u672c ——————————————————————–<\/p>\n\n\n\n

colnames(top5)<\/p>\n\n\n\n

top5$Description <- factor(top5$Description, levels = unique(top5$Description[order(top5$ONTOLOGY)]))<\/p>\n\n\n\n

p = ggplot(top5, aes(x = Description, y = log10P.adjust, fill = ONTOLOGY)) +<\/p>\n\n\n\n

geom_bar(stat = “identity”, width = 0.7, color = “black”) +<\/p>\n\n\n\n

scale_x_discrete(limits = unique(top5$Description[order(top5$ONTOLOGY)])) +<\/p>\n\n\n\n

coord_flip() +<\/p>\n\n\n\n

scale_y_continuous(expand = c(0,0))+<\/p>\n\n\n\n

theme(panel.background = element_rect(fill = “white”))+<\/p>\n\n\n\n

theme(axis.text = element_text(size = 38, color=”black”,family = “Arial”),<\/p>\n\n\n\n

axis.title = element_text(size=45,family=”Arial”,colour = “black”),<\/p>\n\n\n\n

legend.text = element_text(size = 45, family = “Arial”),<\/p>\n\n\n\n

legend.title = element_text(size = 45, family = “Arial”),<\/p>\n\n\n\n

legend.position = “top”)+<\/p>\n\n\n\n

labs(x = “GO term”, y = “-log10 P.adjust”)+<\/p>\n\n\n\n

scale_fill_nejm(alpha = 0.8)<\/p>\n\n\n\n

showtext_auto()<\/p>\n\n\n\n

pdf(“..\/output\/figure1.pdf”,width = 25,height = 15)<\/p>\n\n\n\n

print(p)<\/p>\n\n\n\n

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

\"\"<\/figure>\n\n\n\n

\u8fd9\u5f20\u5bcc\u96c6\u7ed3\u679c\u56fe\u5c55\u793a\u4e86GO\u5bcc\u96c6\u5206\u6790\u5404\u4e2a\u7c7b\u522b\u5bcc\u96c6\u6700\u663e\u8457\u7684\u524d5\u4e2a\u6761\u76ee\uff0c\u5b83\u7684\u6a2a\u5750\u6807\u662f-log10(p.adjust)\uff0c\u7eb5\u5750\u6807\u662f\u6761\u76ee\u7684\u63cf\u8ff0\u3002<\/p>\n\n\n\n

\u6709\u7684\u5c0f\u4f19\u4f34\u5c31\u8bf4\u4e86\uff0c\u8fd9\u4e2a\u56fe\u770b\u7740\u592a\u666e\u901a\u4e86\uff0c\u5c31\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u6761\u5f62\u56fe\u561b\u3002\u54ce\uff0c\u8fd9\u4e2a\u65f6\u5019\u6211\u5c31\u8981\u4ecb\u7ecd\u4e00\u4e0bGOplot\u8fd9\u4e2a\u5305\u4e86\u3002GOplot\uff0c\u4e13\u95e8\u7528\u4e8e\u53ef\u89c6\u5316\u57fa\u56e0\u672c\u4f53\u8bba\uff08Gene Ontology, GO\uff09\u5bcc\u96c6\u5206\u6790\u7684\u7ed3\u679c\u3002\u5b83\u53ef\u4ee5\u7ed8\u5236\u6761\u5f62\u56fe\uff0c\u663e\u793a\u6bcf\u4e2aGO\u672f\u8bed\u7684\u5bcc\u96c6\u5206\u6570\u548c\u663e\u8457\u6027\uff1b\u5b83\u53ef\u4ee5\u7ed8\u5236\u5706\u5f62\u56fe\uff0c\u663e\u793aGO\u672f\u8bed\u7684\u5bcc\u96c6\u5206\u6570\u548c\u663e\u8457\u6027\uff1b\u4ed6\u53ef\u4ee5\u7ed8\u5236\u6c14\u6ce1\u56fe\uff0c\u663e\u793aGO\u672f\u8bed\u7684\u663e\u8457\u6027\u548c\u57fa\u56e0\u6570\uff1b\u5b83\u53ef\u4ee5\u7ed8\u5236\u548c\u5f26\u56fe\uff0c\u663e\u793a\u4e0d\u540cGO\u7c7b\u522b\u4e4b\u95f4\u7684\u57fa\u56e0\u91cd\u53e0\u3002\u4f60\u662f\u5426\u6709\u4e9b\u5fc3\u52a8\u4e86\u5462\uff0c\u4e0b\u9762\u5c0f\u82b1\u5c31\u5e26\u5927\u5bb6\u7ed8\u5236\u8fd9\u4e9b\u7f8e\u89c2\u7684\u5bcc\u96c6\u5206\u6790\u56fe\u3002<\/p>\n\n\n\n

GOplot\u9700\u8981\u7684\u6570\u636e\u683c\u5f0f\u548c\u666e\u901a\u7684\u5bcc\u96c6\u5206\u6790\u7ed3\u679c\u4e0d\u592a\u4e00\u6837\uff0c\u6240\u4ee5\u6211\u4eec\u8981\u5148\u5236\u4f5c\u51c6\u5907\u6570\u636e\uff1a<\/p>\n\n\n\n

## diff\u662f\u5dee\u5f02\u5206\u6790\u7ed3\u679c\uff0c\u4e14\u53ea\u5305\u542b\u4e86\u5dee\u5f02\u57fa\u56e0<\/p>\n\n\n\n

diff = allDiff[which(allDiff$trend!=”stable”), -8]<\/p>\n\n\n\n

colnames(diff) = c(“ID”, “logFC”, “AveExpr”, “t”, “P.Value”, “adj.P.Val”, “B”)<\/p>\n\n\n\n

Genes <- bitr(diff$ID,  <\/p>\n\n\n\n

fromType = “SYMBOL”,<\/p>\n\n\n\n

toType = c(“ENTREZID”),<\/p>\n\n\n\n

OrgDb = org.Hs.eg.db)<\/p>\n\n\n\n

# \u5bcc\u96c6\u5206\u6790 ——————————————————————–<\/p>\n\n\n\n

GO <- enrichGO(gene = Genes$ENTREZID,<\/p>\n\n\n\n

OrgDb = org.Hs.eg.db,<\/p>\n\n\n\n

keyType = “ENTREZID”,<\/p>\n\n\n\n

ont = “all”,     <\/p>\n\n\n\n

pAdjustMethod = “BH”,<\/p>\n\n\n\n

pvalueCutoff = 1,   <\/p>\n\n\n\n

qvalueCutoff = 1,<\/p>\n\n\n\n

minGSSize = 5,<\/p>\n\n\n\n

maxGSSize = 5000,<\/p>\n\n\n\n

readable = TRUE)   <\/p>\n\n\n\n

## \u628a\u7ed3\u679c\u6574\u7406\u6210\u9700\u8981\u7684\u5f62\u5f0f<\/p>\n\n\n\n

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

GO_result = GO_result[which(GO_result$p.adjust<0.05 & GO_result$Count>=2), c(1, 2, 3, 9, 7)]<\/p>\n\n\n\n

colnames(GO_result) = c(“Category”, “ID”, “Term”, “Genes”, “adj_pval”)<\/p>\n\n\n\n

GO_result$Genes = apply(GO_result, 1, function(x){<\/p>\n\n\n\n

  return(gsub(“\/”, “, “, x[4]))<\/p>\n\n\n\n

})<\/p>\n\n\n\n

circ <- circle_dat(GO_result, diff)<\/p>\n\n\n\n

head(circ)<\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

\u8fd9\u91cc\u7684circ\u5c31\u662f\u6211\u4eec\u9700\u8981\u7684\u6570\u636e\u4e86\uff0c\u8fd9\u91cc\u6709\u4e00\u5217\u662fzscore\uff0c\u5b83\u7528\u6765\u8868\u793a\u8fd9\u4e2a\u6761\u76ee\u4e2d\u4e0a\u8c03\u57fa\u56e0\u548c\u4e0b\u8c03\u57fa\u56e0\u7684\u60c5\u51b5\uff0c\u5982\u679czscore\u5927\u4e8e0\u8868\u793a\u8fd9\u4e2a\u5bcc\u96c6\u5230\u8fd9\u4e2a\u6761\u76ee\u7684\u4e0a\u8c03\u57fa\u56e0\u591a\uff0c\u53cd\u4e4b\u5219\u662f\u4e0b\u8c03\u57fa\u56e0\u591a\u3002<\/p>\n\n\n\n

\u8fd9\u91cc\u7684up\u662f\u6307\u5bcc\u96c6\u5230\u8fd9\u4e2a\u6761\u76ee\u7684\u4e0a\u8c03\u57fa\u56e0\u7684\u6570\u76ee\uff0cdown\u662f\u6307\u5bcc\u96c6\u5230\u8fd9\u4e2a\u6761\u76ee\u7684\u4e0b\u8c03\u57fa\u56e0\u7684\u6570\u76ee\uff0ccount\u662f\u5bcc\u96c6\u5230\u8fd9\u4e2a\u6761\u76ee\u7684\u6240\u6709\u57fa\u56e0\u7684\u6570\u76ee\u3002<\/p>\n\n\n\n

\u9996\u5148\uff0c\u6211\u4eec\u6765\u5c55\u793a\u4e00\u4e0bGOplot\u7684\u6761\u5f62\u56fe\uff1a<\/p>\n\n\n\n

library(GOplot)<\/p>\n\n\n\n

## \u5c55\u793a\u5404\u4e2a\u7c7b\u522b\u6700\u663e\u8457\u7684\u524d5\u4e2a\u6761\u76ee<\/p>\n\n\n\n

BP_top5 <- GO_result %>%<\/p>\n\n\n\n

filter(Category == “BP”) %>%  <\/p>\n\n\n\n

arrange(adj_pval) %>%        <\/p>\n\n\n\n

head(5)                     <\/p>\n\n\n\n

CC_top5 <- GO_result %>%<\/p>\n\n\n\n

filter(Category == “CC”) %>%  <\/p>\n\n\n\n

arrange(adj_pval) %>%      <\/p>\n\n\n\n

head(5)                 <\/p>\n\n\n\n

MF_top5 <- GO_result %>%<\/p>\n\n\n\n

filter(Category == “MF”) %>%<\/p>\n\n\n\n

arrange(adj_pval) %>%       <\/p>\n\n\n\n

head(5)<\/p>\n\n\n\n

## \u6761\u5f62\u56fe<\/p>\n\n\n\n

pdf(“..\/output\/figure2.pdf”)<\/p>\n\n\n\n

GOBar(subset(circ, ID %in% c(BP_top5$ID, CC_top5$ID, MF_top5$ID)), ## \u5c55\u793a\u7684\u6761\u76ee\u6570\u636e<\/p>\n\n\n\n

display = “multiple”, ## \u5206\u7c7b\u8fdb\u884c\u5206\u9762<\/p>\n\n\n\n

zsc.col = c(‘red’, ‘black’, ‘blue’)) ## \u8bbe\u7f6ez-score\u8272\u9636\uff0c\u4f9d\u6b21\u4e3ac(high, midpoint, low)<\/p>\n\n\n\n

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

\"\"<\/figure>\n\n\n\n

\u8fd9\u91cc\u5176\u5b9e\u4e5f\u662f\u6761\u5f62\u56fe\uff0c\u4f46\u662f\u591a\u4e86\u989c\u8272\uff0c\u4ece\u989c\u8272\u4e2d\u6211\u4eec\u53ef\u4ee5\u77e5\u9053\u8fd9\u4e2a\u6761\u76ee\u6574\u4f53\u662f\u4e0a\u8c03\u7684\u8fd8\u662f\u4e0b\u8c03\u7684\u3002\u4f46\u662f\u56e0\u4e3a\u8fd9\u51e0\u4e2a\u6761\u76ee\u7684zscore\u90fd\u662f\u6b63\u7684\uff0c\u6240\u4ee5\u8bbe\u7f6e\u7684\u8272\u9636\u4e2d\u84dd\u8272\u6ca1\u6709\u663e\u73b0\u51fa\u6765\u3002<\/p>\n\n\n\n

\u7136\u540e\u6211\u4eec\u518d\u6765\u770b\u4e00\u4e0b\u6c14\u6ce1\u56fe\uff1a<\/p>\n\n\n\n

## \u6c14\u6ce1\u56fe<\/p>\n\n\n\n

pdf(“..\/output\/figure3.pdf”)<\/p>\n\n\n\n

GOBubble(circ, colour = c(‘orange’, ‘forestgreen’, ‘purple’), ## \u8bbe\u7f6e\u6bcf\u4e2a\u7c7b\u578b\u7684\u989c\u8272<\/p>\n\n\n\n

display = ‘multiple’, labels = 10 ## \u663e\u793ay>10\u7684\u6807\u7b7e<\/p>\n\n\n\n

)<\/p>\n\n\n\n

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

\"\"<\/figure>\n\n\n\n

\u8fd9\u91cc\u6a2a\u5750\u6807\u5c31\u662fzscore\uff0c\u4f46\u662f\u8fd9\u6837\u770b\u7740\u592a\u4e71\u4e86\uff0c\u8fd9\u662f\u53ef\u4ee5\u628a\u76f8\u4f3c\u6027\u6bd4\u8f83\u9ad8\u7684\u6761\u76ee\u5220\u6389\uff1a<\/p>\n\n\n\n

## \u5f88\u660e\u663e\u53ef\u4ee5\u770b\u5230\u6761\u76ee\u592a\u591a\u4e86\uff0c\u663e\u793a\u4f1a\u6324\u5728\u4e00\u8d77<\/p>\n\n\n\n

## \u5220\u9664\u57fa\u56e0\u91cd\u53e0\u5927\u4e8e\u6216\u7b49\u4e8e 0.75\u7684 terms\uff08\u5177\u4f53\u4e0d\u77e5\u9053\u6309\u4ec0\u4e48\u539f\u5219\u5220\u7684\uff09<\/p>\n\n\n\n

reduced_circ <- reduce_overlap(circ, overlap = 0.75)<\/p>\n\n\n\n

pdf(“..\/output\/figure4.pdf”)<\/p>\n\n\n\n

GOBubble(reduced_circ, colour = c(‘orange’, ‘forestgreen’, ‘purple’), ## \u8bbe\u7f6e\u6bcf\u4e2a\u7c7b\u578b\u7684\u989c\u8272<\/p>\n\n\n\n

display = ‘multiple’, labels = 10 ## \u663e\u793ay>10\u7684\u6807\u7b7e<\/p>\n\n\n\n

)<\/p>\n\n\n\n

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

\"\"<\/figure>\n\n\n\n

\u8fd9\u6837\u770b\u7740\u5c31\u6e05\u723d\u5f88\u591a\u4e86\u3002\u7136\u540e\u6211\u4eec\u518d\u6765\u770b\u4e00\u4e0b\u5708\u56fe\uff1a<\/p>\n\n\n\n

## # \u53ef\u89c6\u5316\u611f\u5174\u8da3\u7684\u6761\u76ee<\/p>\n\n\n\n

IDs <- c(BP_top5$ID[1:3], CC_top5$ID[1:3], MF_top5$ID[1:3])<\/p>\n\n\n\n

pdf(“..\/output\/figure5.pdf”, width = 13, height = 7)<\/p>\n\n\n\n

GOCircle(circ, nsub = IDs)<\/p>\n\n\n\n

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

# \u53ef\u89c6\u5316\u524d5\u4e2a\u6761\u76ee<\/p>\n\n\n\n

pdf(“..\/output\/figure6.pdf”, width = 10, height = 5)<\/p>\n\n\n\n

GOCircle(circ, nsub = 5)<\/p>\n\n\n\n

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

\"\"<\/figure>\n\n\n\n
\"\"<\/figure>\n\n\n\n

\u6700\u5916\u5708\u663e\u793a\u4e86\u5bcc\u96c6\u57fa\u56e0\u7684\u4e0a\u8c03\u548c\u4e0b\u8c03\u60c5\u51b5\uff0c\u5185\u5708\u989c\u8272\u8868\u793azscore\u7684\u5927\u5c0f\uff0c\u5185\u5708\u9ad8\u4f4e\u8868\u793a\u5bcc\u96c6\u7ed3\u679c\u7684\u663e\u8457\u6027\u3002\u6211\u4eec\u518d\u6765\u770b\u4e00\u4e0b\u5f26\u56fe\uff1a<\/p>\n\n\n\n

## \u5f26\u56fe<\/p>\n\n\n\n

chord <- chord_dat(data = subset(circ, ID %in% c(BP_top5$ID[1:3], CC_top5$ID[1:3], MF_top5$ID[1:3])),<\/p>\n\n\n\n

genes = diff[,c(1, 2)])<\/p>\n\n\n\n

pdf(“..\/output\/figure7.pdf”)<\/p>\n\n\n\n

GOChord(chord, space = 0.02, gene.order = ‘logFC’, gene.space = 0.25, gene.size = 3,<\/p>\n\n\n\n

limit = c(3, 30)) ## \u5c55\u793a\u57fa\u56e0\u81f3\u5c11\u5bcc\u96c6\u5230\u4e09\u4e2a\u6761\u76ee\uff0c\u5c55\u793a\u6761\u76ee\u81f3\u5c11\u670930\u4e2a\u57fa\u56e0\u5bcc\u96c6<\/p>\n\n\n\n

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

\"\"<\/figure>\n\n\n\n

\u5f88\u96be\u53d7\u7684\u4e00\u70b9\u5c31\u662f\u65e0\u6cd5\u8c03\u6574\u56fe\u4f8b\u7684\u6392\u5217\u548c\u4f4d\u7f6e\uff0c\u5bfc\u81f4\u5f88\u591a\u56fe\u4f8b\u770b\u4e0d\u5230\uff0c\u800c\u4e14\u51fd\u6570\u6ca1\u6709\u63d0\u4f9b\u53c2\u6570\u6765\u4fee\u6539\u3002\u8fd9\u65f6\u5019\u6211\u4eec\u53ef\u4ee5\u901a\u8fc7\u4fee\u6539\u6e90\u4ee3\u7801\u6765\u89e3\u51b3\u3002<\/p>\n\n\n\n

trace(GOChord, edit = TRUE)<\/p>\n\n\n\n

pdf(“..\/output\/figure8.pdf”, width = 10, height = 5)<\/p>\n\n\n\n

GOChord(chord, space = 0.02, gene.order = ‘logFC’, gene.space = 0.25, gene.size = 3,<\/p>\n\n\n\n

limit = c(3, 30)) ## \u5c55\u793a\u57fa\u56e0\u81f3\u5c11\u5bcc\u96c6\u5230\u4e09\u4e2a\u6761\u76ee\uff0c\u5c55\u793a\u6761\u76ee\u81f3\u5c11\u670930\u4e2a\u57fa\u56e0\u5bcc\u96c6<\/p>\n\n\n\n

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

\u5728\u6240\u793a\u4f4d\u7f6e\u6dfb\u52a0\u8fd9\u51e0\u884c\u4ee3\u7801\u5373\u53ef\uff1a\u8bbe\u7f6eGO Terms\u56fe\u4f8b\u4f4d\u7f6e\u5728\u53f3\u8fb9\uff0c\u4e14\u56fe\u4f8b\u7684\u5217\u662f\u4e00\u5217\u3002\u4ee3\u7801\u5df2\u7ecf\u4e3a\u5927\u5bb6\u51c6\u5907\u597d\u4e86\uff0c\u5927\u5bb6\u53ef\u4ee5\u5728code\/GO_Chord.R\u590d\u5236\u7c98\u8d34\u5373\u53ef\u3002<\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n
\"\"<\/figure>\n\n\n\n

\u8fd9\u6837\u5f26\u56fe\u5c31\u663e\u793a\u5b8c\u5168\u4e86\uff0c\u5f26\u56fe\u5c55\u793a\u4e86\u6240\u9009\u57fa\u56e0\u548c\u6761\u76ee\u4e4b\u95f4\u7684\u5173\u7cfb\uff0c\u4ee5\u53ca\u8fd9\u4e9b\u57fa\u56e0\u7684logFC\u3002<\/p>\n\n\n\n

    \u4eca\u5929\u7684\u5bcc\u96c6\u5206\u6790\u7ed3\u679c\u753b\u56fe\u65b9\u6cd5\u5c31\u5206\u4eab\u5230\u8fd9\u91cc\uff0c\u5e0c\u671b\u5bf9\u5927\u5bb6\u80fd\u6709\u6240\u5e2e\u52a9\uff0c\u5982\u679c\u5927\u5bb6\u53d1\u73b0\u6587\u4e2d\u6709\u4e0d\u5bf9\u7684\u5730\u65b9\u6216\u6709\u5176\u4ed6\u7591\u95ee\uff0c\u6b22\u8fce\u7559\u8a00\u5206\u4eab\u3002\u5982\u679c\u5404\u4f4d\u89c9\u5f97\u81ea\u5df1\u8fd0\u884c\u4ee3\u7801\u592a\u9ebb\u70e6\uff0c\u6b22\u8fce\u7528\u6211\u4eec\u7684\u4e91\u751f\u4fe1\u5c0f\u5de5\u5177<\/strong>(<\/strong>http:\/\/www.biocloudservice.com\/home.html<\/strong>)<\/strong>\uff0c\u53ea\u8981\u8f93\u5165\u5408\u9002\u7684\u6570\u636e\u5c31\u53ef\u4ee5\u76f4\u63a5\u51fa\u60f3\u8981\u7684\u56fe\u5462<\/strong>\u3002<\/strong><\/p>\n","protected":false},"excerpt":{"rendered":"

\u76f8\u4fe1\u5927\u5bb6\u90fd\u4f1a\u505a\u5bcc\u96c6\u5206\u6790\uff0c\u4f46\u662f\u4f60\u4f1a\u628a\u5bcc\u96c6\u5206\u6790\u7684\u7ed3\u679c\u7f8e\u89c2\u3001\u5168\u9762\u5730\u5c55\u793a\u51fa\u6765\u5417\uff1f\u4e00\u4e2a\u597d\u7684\u5206\u6790\u7ed3\u679c\u56fa\u7136\u91cd\u8981\uff0c\u4e00\u4e2a\u597d\u7684\u7ed3\u679c […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"","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\/61671"}],"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=61671"}],"version-history":[{"count":1,"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=\/wp\/v2\/posts\/61671\/revisions"}],"predecessor-version":[{"id":61690,"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=\/wp\/v2\/posts\/61671\/revisions\/61690"}],"wp:attachment":[{"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=61671"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=61671"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=61671"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}