{"id":25529,"date":"2024-01-22T16:57:46","date_gmt":"2024-01-22T08:57:46","guid":{"rendered":"http:\/\/www.biocloudservice.com\/wordpress\/?p=25529"},"modified":"2024-01-22T16:57:48","modified_gmt":"2024-01-22T08:57:48","slug":"%e7%94%9f%e4%bf%a1%e5%b0%8f%e7%99%bd%e7%9a%84%e7%a6%8f%e5%88%a9%ef%bc%8c%e5%88%a9%e7%94%a8quantiseq%e7%ae%97%e6%b3%95%e8%bf%9b%e8%a1%8c%e5%85%8d%e7%96%ab%e6%b5%b8%e6%b6%a6%e5%88%86%e6%9e%90","status":"publish","type":"post","link":"http:\/\/www.biocloudservice.com\/wordpress\/?p=25529","title":{"rendered":"\u751f\u4fe1\u5c0f\u767d\u7684\u798f\u5229\uff0c\u5229\u7528quanTIseq\u7b97\u6cd5\u8fdb\u884c\u514d\u75ab\u6d78\u6da6\u5206\u6790"},"content":{"rendered":"\n

\u5c0f\u679c\u53c8\u6765\u5206\u4eab\u5566\uff01\u4eca\u5929\u5c0f\u679c\u4e3a\u5c0f\u4f19\u4f34\u5e26\u6765\u7684\u5206\u4eab\u4e3a\u5229\u7528quanTIseq\u7b97\u6cd5\u8fdb\u884c\u514d\u75ab\u6d78\u6da6\u5206\u6790\uff0c\u7136\u540e\u57fa\u4e8e\u4e9a\u578b\u5206\u7ec4\u4fe1\u606f\u6587\u4ef6\uff0c\u8fdb\u884c\u4e9a\u578b\u95f4\u514d\u75ab\u7ec6\u80de\u542b\u91cf\u663e\u8457\u5dee\u5f02\u5206\u6790\uff0c\u8be5\u5206\u6790\u5728\u80bf\u7624\u751f\u4fe1\u6587\u7ae0\u4e2d\u5fc5\u5907\u7684\u5206\u6790\u5185\u5bb9\uff0c\u975e\u5e38\u503c\u5f97\u5c0f\u4f19\u4f34\u5b66\u4e60\uff0c\u5c0f\u679c\u5f3a\u70c8\u63a8\u8350\u5440\uff01\u63a5\u4e0b\u6765\u8ddf\u7740\u5c0f\u679c\u5f00\u542f\u5f00\u59cb\u4eca\u5929\u7684\u5206\u4eab\u5b66\u4e60\u3002<\/p>\n\n\n\n

    \n
  1. quanTIseq\u7b97\u6cd5\u4ecb\u7ecd<\/li>\n<\/ol>\n\n\n\n

    \u5728\u8fdb\u884c\u8be5\u5206\u6790\u4e4b\u524d\uff0c\u5c0f\u679c\u5148\u7b80\u5355\u4ecb\u7ecd\u4e00\u4e0bquanTIseq\u7b97\u6cd5\uff0cquanTIseq\u57fa\u4e8e\u53cd\u5377\u79ef\u7b97\u6cd5\uff0c\u5229\u7528bulk samples\u7684RNA_seq\u6570\u636e\uff0c\u53ef\u4ee5\u5bf9\u80bf\u7624\u6837\u672c\u4e2d\u4e0d\u540c\u79cd\u7c7b\u514d\u75ab\u7ec6\u80de\u7684\u7ec4\u6210\u8fdb\u884c\u9884\u6d4b\uff0c\u652f\u630110\u79cd\u7c7b\u578b\u7684\u514d\u75ab\u7ec6\u80de\uff0c\u5305\u62ecB cells\uff0cClassically activated macrophages (M1)\uff0cAlternatively activated macrophages (M2)\uff0cMonocytes\uff0cNeutrophils\uff0cNatural killer (NK) cells\uff0cNon-regulatory CD4+ T cells \uff0cCD8+ T cells\uff0cDendritic cells\uff0cOther uncharacterized cells\uff0c\u8fd9\u5c31\u662f\u5c0f\u679c\u5bf9\u8be5\u7b97\u6cd5\u7684\u4ecb\u7ecd\uff0c\u60f3\u6df1\u5165\u5b66\u4e60\u7684\u5c0f\u4f19\u4f34\u53ef\u4ee5\u5230\u8be5\u7f51\u5740:https:\/\/icbi.i-med.ac.at\/software\/quantiseq\/doc\/index.html#Figure1\u3002<\/p>\n\n\n\n

    #\u9996\u5148\u4e0b\u8f7dquanTIseq\u6d41\u7a0b\u5206\u6790\u811a\u672c\uff0c\u5982\u4e0b\u6587:<\/p>\n\n\n\n

    wget https:\/\/icbi.i-med.ac.at\/software\/quantiseq\/doc\/downloads\/quanTIseq_pipeline.sh<\/p>\n\n\n\n

    #quanTIseq\u6d41\u7a0b\u8fd0\u884c\u53c2\u6570\u4f7f\u7528\u65b9\u6cd5<\/p>\n\n\n\n

    \"Dingtalk_20230713154227\"<\/figure>\n\n\n\n
      \n
    1. \u51c6\u5907\u9700\u8981\u7684R\u5305<\/li>\n<\/ol>\n\n\n\n

      #\u5b89\u88c5\u9700\u8981\u7684\u5305<\/p>\n\n\n\n

      install.packages(“ggplot2”)<\/p>\n\n\n\n

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

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

      install.packages(“reshape2”)<\/p>\n\n\n\n

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

      #\u52a0\u8f7d\u9700\u8981\u7684R\u5305<\/p>\n\n\n\n

      library(reshape2)<\/p>\n\n\n\n

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

      library(ggplot2)<\/p>\n\n\n\n

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

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

      2.\u8f93\u5165\u6570\u636e<\/p>\n\n\n\n

      #EXP.txt\uff0c\u57fa\u56e0\u8868\u8fbe\u77e9\u9635\u6587\u4ef6\uff0c\u884c\u540d\u4e3a\u57fa\u56e0\u540d\uff0c\u5217\u540d\u4e3a\u6837\u672c\u4fe1\u606f\u3002<\/p>\n\n\n\n

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

      \"Dingtalk_20230713145410\"<\/figure>\n\n\n\n

      #\u5c06\u884c\u540d\u8f6c\u5316\u4e3a\u5217\u540d<\/p>\n\n\n\n

      exp<-rownames_to_column(exp,var=”GENE”)<\/p>\n\n\n\n

      4.\u5229\u7528quanTIseq\u7b97\u6cd5\u8fdb\u884c\u514d\u75ab\u6d78\u6da6\u5206\u6790<\/p>\n\n\n\n

      #quanTIseq\u8fdb\u884c\u514d\u75ab\u6d78\u6da6\u5206\u6790<\/p>\n\n\n\n

      bash quanTIseq_pipeline.sh –inputfile=exp.txt –outputdir=quanTIseqTest –prefix=quanTIseqTest –pipelinestart=decon<\/p>\n\n\n\n

      input\u8868\u793a\u57fa\u56e0\u8868\u8fbe\u77e9\u9635\uff0c\u7b2c\u4e00\u5217\u4e3a\u57fa\u56e0\u540d\uff0c\u5176\u4ed6\u5217\u4e3a\u6837\u672c\u540d\u3002<\/p>\n\n\n\n

      outputdir\u8868\u793a\u751f\u6210\u7ed3\u679c\u6587\u4ef6\u540d<\/p>\n\n\n\n

      prefix\u8868\u793a\u751f\u6210\u7ed3\u679c\u6587\u4ef6\u524d\u7f00<\/p>\n\n\n\n

      pipelinestart\u8868\u793aquanTIseq\u5206\u6790\u6d41\u7a0b\uff0c\u57fa\u56e0\u8868\u8fbe\u77e9\u9635\u9009\u7528decon<\/p>\n\n\n\n

      #\u751f\u6210\u7ed3\u679c\u6587\u4ef6\u4e3aquanTIseqTest_cell_fractions.txt\uff0c\u8be5\u7ed3\u679c\u4e3a\u8ba1\u7b97\u768410\u79cd\u514d\u75ab\u7ec6\u80de\u5728\u4e0d\u540c\u6837\u672c\u4e2d\u7684\u542b\u91cf\uff0c\u7b2c\u4e00\u5217\u4e3a\u6837\u672c\u540d\uff0c\u5176\u4ed6\u5217\u4e3a\u514d\u75ab\u7ec6\u80de\u7c7b\u578b\u3002<\/p>\n\n\n\n

      \"Dingtalk_20230713155008\"<\/figure>\n\n\n\n

      5.\u4e0d\u540c\u4e9a\u578b\u4e2dquanTIseq\u7b97\u6cd5\u8ba1\u7b97\u7684\u514d\u75ab\u7ec6\u80de\u7684\u663e\u8457\u5dee\u5f02\u5206\u6790<\/p>\n\n\n\n

      #\u8bfb\u53d6quanTIseq\u5206\u6790\u514d\u75ab\u7ec6\u80de\u7ec4\u6210\u7ed3\u679c\u6587\u4ef6<\/p>\n\n\n\n

      immune<-read.table(“quanTIseqTest_cell_fractions.txt”,header=T,sep=”\\t”)<\/p>\n\n\n\n

      #\u5c06Sample\u5217\u201d.\u201d\u4fee\u6539\u4e3a\u201d-\u201d<\/p>\n\n\n\n

      immune$Sample<-str_replace_all(immune$Sample,”\\\\.”,”-“)<\/p>\n\n\n\n

      #\u4e9a\u578b\u5206\u7ec4\u6587\u4ef6,\u884c\u540d\u4e3a\u6837\u672c\u4fe1\u606f\uff0c\u7b2c\u4e00\u5217\u4e3a\u6837\u672c\u4fe1\u606f\uff0c\u7b2c\u4e8c\u5217\u4e3a\u4e9a\u578b\u5206\u7ec4\u4fe1\u606f\u3002<\/p>\n\n\n\n

      K3<-read.table(“K3.txt”,header=T,sep=”\\t”)<\/p>\n\n\n\n

      \"Dingtalk_20230713220537\"<\/figure>\n\n\n\n

      #\u5408\u5e76\u514d\u75ab\u7ec6\u80de\u7ec4\u6210\u6587\u4ef6\u548c\u4e9a\u578b\u5206\u7ec4\u6587\u4ef6<\/p>\n\n\n\n

      final<-left_join(immune,K3,by=\u201dSample\u201d)<\/p>\n\n\n\n

      #\u957f\u5bbd\u6570\u636e\u8f6c\u6362<\/p>\n\n\n\n

      quanTIseq_cluster<-melt(final,id.vars=c(“Sample”,”Cluster”))<\/p>\n\n\n\n

      #\u8bbe\u7f6e\u5217\u540d<\/p>\n\n\n\n

      colnames(quanTIseq_cluster)<-c(“Sample”,”Cluster”,”celltype”,”quanTIseq”)<\/p>\n\n\n\n

      #\u7ed8\u5236\u663e\u8457\u5dee\u5f02\u5206\u6790\u5c0f\u63d0\u7434+\u7bb1\u7ebf\u56fe<\/p>\n\n\n\n

      boxplot_quanTIseq<- ggplot(quanTIseq_cluster, aes(x = celltype, y =quanTIseq ))+<\/p>\n\n\n\n

      labs(y=”quanTIseq”,x= “”)+<\/p>\n\n\n\n

      geom_boxplot(aes(fill = Cluster),position=position_dodge(0.5),width=0.5)+<\/p>\n\n\n\n

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

      #\u4fee\u6539\u4e3b\u9898<\/p>\n\n\n\n

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

      theme(axis.title = element_text(size = 12,color =”black”),<\/p>\n\n\n\n

      axis.text = element_text(size= 12,color = “black”),<\/p>\n\n\n\n

      panel.grid.minor.y = element_blank(),<\/p>\n\n\n\n

      panel.grid.minor.x = element_blank(),<\/p>\n\n\n\n

      axis.text.x = element_text(angle = 45, hjust = 1 ),<\/p>\n\n\n\n

      panel.grid=element_blank(),<\/p>\n\n\n\n

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

      legend.text = element_text(size= 12),<\/p>\n\n\n\n

      legend.title= element_text(size= 12)<\/p>\n\n\n\n

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

      stat_compare_means(aes(group = Cluster),<\/p>\n\n\n\n

      label = “p.signif”,<\/p>\n\n\n\n

      method = “kruskal.test”,#kruskal.test\u591a\u7ec4\u68c0\u9a8c<\/p>\n\n\n\n

      hide.ns = F)#\u9690\u85cf\u4e0d\u663e\u8457\u7684<\/p>\n\n\n\n

      #\u4fdd\u5b58\u56fe\u7247<\/p>\n\n\n\n

      ggsave(file=”quanTIseq.pdf”,boxplot_quanTIseq,height=10,width=15)<\/p>\n\n\n\n

      \"Dingtalk_20230713174202\"<\/figure>\n\n\n\n

      \u6700\u7ec8\u5c0f\u679c\u6210\u529f\u7684\u5bf9\u4e0d\u540c\u4e9a\u578b\u5229\u7528quanTIseq\u7b97\u6cd5\u8fdb\u884c\u4e86\u514d\u75ab\u6d78\u6da6\u5206\u6790\uff0c\uff0c\u770b\u8d77\u6765\u56fe\u7247\u6548\u679c\u975e\u5e38\u4e0d\u9519\uff0c\u6b22\u8fce\u5927\u5bb6\u548c\u5c0f\u679c\u4e00\u8d77\u8ba8\u8bba\u5b66\u4e60\u5440\uff01\u514d\u75ab\u6d78\u6da6\u76f8\u5173\u5206\u6790\u5185\u5bb9\uff0c\u4f8b\u5982\u5355\u6837\u672c\u5bcc\u96c6\u7b97\u6cd5\u5206\u6790\u514d\u75ab\u6d78\u6da6\u4e30\u5ea6(http:\/\/www.biocloudservice.com\/106\/106.php)\uff0c\u8ba1\u7b9764\u79cd\u514d\u75ab\u7ec6\u80de\u76f8\u5bf9\u542b\u91cf(http:\/\/www.biocloudservice.com\/107\/107.php)\uff0cpanImmune\u514d\u75ab\u6d78\u6da6\u5206\u6790(http:\/\/www.biocloudservice.com\/782\/782.php)\u7b49\u90fd\u53ef\u4ee5\u7528\u672c\u516c\u53f8\u65b0\u5f00\u53d1\u7684\u96f6\u4ee3\u7801\u4e91\u5e73\u53f0\u751f\u4fe1\u5206\u6790\u5c0f\u5de5\u5177\uff0c\u4e00\u952e\u5b8c\u6210\u8be5\u5206\u6790\u5965\uff0c\u611f\u5174\u8da3\u7684\u5c0f\u4f19\u4f34\u6b22\u8fce\u6765\u5c1d\u8bd5\u5965\uff0c\u7f51\u5740\uff1ahttp:\/\/www.biocloudservice.com\/home.html\u3002\u4eca\u5929\u5c0f\u679c\u7684\u5206\u4eab\u5c31\u5230\u8fd9\u91cc\uff0c\u4e0b\u671f\u5728\u89c1\u5965\u3002<\/p>\n\n\n

      \u751f\u4fe1\u5c0f\u767d\u7684\u798f\u5229\uff0c\u5229\u7528quanTIseq\u7b97\u6cd5\u8fdb\u884c\u514d\u75ab\u6d78\u6da6\u5206\u6790<\/p>\n

      \u5c0f\u679c\u53c8\u6765\u5206\u4eab\u5566\uff01\u4eca\u5929\u5c0f\u679c\u4e3a\u5c0f\u4f19\u4f34\u5e26\u6765\u7684\u5206\u4eab\u4e3a\u5229\u7528quanTIseq\u7b97\u6cd5\u8fdb\u884c\u514d\u75ab\u6d78\u6da6\u5206\u6790\uff0c\u7136\u540e\u57fa\u4e8e\u4e9a\u578b\u5206\u7ec4\u4fe1\u606f\u6587\u4ef6\uff0c\u8fdb\u884c\u4e9a\u578b\u95f4\u514d\u75ab\u7ec6\u80de\u542b\u91cf\u663e\u8457\u5dee\u5f02\u5206\u6790\uff0c\u8be5\u5206\u6790\u5728\u80bf\u7624\u751f\u4fe1\u6587\u7ae0\u4e2d\u5fc5\u5907\u7684\u5206\u6790\u5185\u5bb9\uff0c\u975e\u5e38\u503c\u5f97\u5c0f\u4f19\u4f34\u5b66\u4e60\uff0c\u5c0f\u679c\u5f3a\u70c8\u63a8\u8350\u5440\uff01\u63a5\u4e0b\u6765\u8ddf\u7740\u5c0f\u679c\u5f00\u542f\u5f00\u59cb\u4eca\u5929\u7684\u5206\u4eab\u5b66\u4e60\u3002<\/p>\n

        \n
      1. quanTIseq\u7b97\u6cd5\u4ecb\u7ecd<\/li>\n<\/ol>\n

        \u5728\u8fdb\u884c\u8be5\u5206\u6790\u4e4b\u524d\uff0c\u5c0f\u679c\u5148\u7b80\u5355\u4ecb\u7ecd\u4e00\u4e0bquanTIseq\u7b97\u6cd5\uff0cquanTIseq\u57fa\u4e8e\u53cd\u5377\u79ef\u7b97\u6cd5\uff0c\u5229\u7528bulk samples\u7684RNA_seq\u6570\u636e\uff0c\u53ef\u4ee5\u5bf9\u80bf\u7624\u6837\u672c\u4e2d\u4e0d\u540c\u79cd\u7c7b\u514d\u75ab\u7ec6\u80de\u7684\u7ec4\u6210\u8fdb\u884c\u9884\u6d4b\uff0c\u652f\u630110\u79cd\u7c7b\u578b\u7684\u514d\u75ab\u7ec6\u80de\uff0c\u5305\u62ecB cells\uff0cClassically activated macrophages (M1)\uff0cAlternatively activated macrophages (M2)\uff0cMonocytes\uff0cNeutrophils\uff0cNatural killer (NK) cells\uff0cNon-regulatory CD4+ T cells \uff0cCD8+ T cells\uff0cDendritic cells\uff0cOther uncharacterized cells\uff0c\u8fd9\u5c31\u662f\u5c0f\u679c\u5bf9\u8be5\u7b97\u6cd5\u7684\u4ecb\u7ecd\uff0c\u60f3\u6df1\u5165\u5b66\u4e60\u7684\u5c0f\u4f19\u4f34\u53ef\u4ee5\u5230\u8be5\u7f51\u5740:https:\/\/icbi.i-med.ac.at\/software\/quantiseq\/doc\/index.html#Figure1\u3002<\/p>\n

        #\u9996\u5148\u4e0b\u8f7dquanTIseq\u6d41\u7a0b\u5206\u6790\u811a\u672c\uff0c\u5982\u4e0b\u6587:<\/p>\n

        wget https:\/\/icbi.i-med.ac.at\/software\/quantiseq\/doc\/downloads\/quanTIseq_pipeline.sh<\/p>\n

        #quanTIseq\u6d41\u7a0b\u8fd0\u884c\u53c2\u6570\u4f7f\u7528\u65b9\u6cd5<\/p>\n

        \"Dingtalk_20230713154227\"<\/p>\n

          \n
        1. \u51c6\u5907\u9700\u8981\u7684R\u5305<\/li>\n<\/ol>\n

          #\u5b89\u88c5\u9700\u8981\u7684\u5305<\/p>\n

          install.packages(“ggplot2”)<\/p>\n

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

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

          install.packages(“reshape2”)<\/p>\n

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

          #\u52a0\u8f7d\u9700\u8981\u7684R\u5305<\/p>\n

          library(reshape2)<\/p>\n

          library(ggpubr)<\/p>\n

          library(ggplot2)<\/p>\n

          library(tidyverse)<\/p>\n

          library(ggsci)<\/p>\n

          2.\u8f93\u5165\u6570\u636e<\/p>\n

          #EXP.txt\uff0c\u57fa\u56e0\u8868\u8fbe\u77e9\u9635\u6587\u4ef6\uff0c\u884c\u540d\u4e3a\u57fa\u56e0\u540d\uff0c\u5217\u540d\u4e3a\u6837\u672c\u4fe1\u606f\u3002<\/p>\n

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

          \"Dingtalk_20230713145410\"<\/p>\n

          #\u5c06\u884c\u540d\u8f6c\u5316\u4e3a\u5217\u540d<\/p>\n

          exp<-rownames_to_column(exp,var=”GENE”)<\/p>\n

          4.\u5229\u7528quanTIseq\u7b97\u6cd5\u8fdb\u884c\u514d\u75ab\u6d78\u6da6\u5206\u6790<\/p>\n

          #quanTIseq\u8fdb\u884c\u514d\u75ab\u6d78\u6da6\u5206\u6790<\/p>\n

          bash quanTIseq_pipeline.sh –inputfile=exp.txt –outputdir=quanTIseqTest –prefix=quanTIseqTest –pipelinestart=decon<\/p>\n

          input\u8868\u793a\u57fa\u56e0\u8868\u8fbe\u77e9\u9635\uff0c\u7b2c\u4e00\u5217\u4e3a\u57fa\u56e0\u540d\uff0c\u5176\u4ed6\u5217\u4e3a\u6837\u672c\u540d\u3002<\/p>\n

          outputdir\u8868\u793a\u751f\u6210\u7ed3\u679c\u6587\u4ef6\u540d<\/p>\n

          prefix\u8868\u793a\u751f\u6210\u7ed3\u679c\u6587\u4ef6\u524d\u7f00<\/p>\n

          pipelinestart\u8868\u793aquanTIseq\u5206\u6790\u6d41\u7a0b\uff0c\u57fa\u56e0\u8868\u8fbe\u77e9\u9635\u9009\u7528decon<\/p>\n

          #\u751f\u6210\u7ed3\u679c\u6587\u4ef6\u4e3aquanTIseqTest_cell_fractions.txt\uff0c\u8be5\u7ed3\u679c\u4e3a\u8ba1\u7b97\u768410\u79cd\u514d\u75ab\u7ec6\u80de\u5728\u4e0d\u540c\u6837\u672c\u4e2d\u7684\u542b\u91cf\uff0c\u7b2c\u4e00\u5217\u4e3a\u6837\u672c\u540d\uff0c\u5176\u4ed6\u5217\u4e3a\u514d\u75ab\u7ec6\u80de\u7c7b\u578b\u3002<\/p>\n

          \"Dingtalk_20230713155008\"<\/p>\n

          5.\u4e0d\u540c\u4e9a\u578b\u4e2dquanTIseq\u7b97\u6cd5\u8ba1\u7b97\u7684\u514d\u75ab\u7ec6\u80de\u7684\u663e\u8457\u5dee\u5f02\u5206\u6790<\/p>\n

          #\u8bfb\u53d6quanTIseq\u5206\u6790\u514d\u75ab\u7ec6\u80de\u7ec4\u6210\u7ed3\u679c\u6587\u4ef6<\/p>\n

          immune<-read.table(“quanTIseqTest_cell_fractions.txt”,header=T,sep=”\\t”)<\/p>\n

          #\u5c06Sample\u5217\u201d.\u201d\u4fee\u6539\u4e3a\u201d-\u201d<\/p>\n

          immune$Sample<-str_replace_all(immune$Sample,”\\\\.”,”-“)<\/p>\n

          #\u4e9a\u578b\u5206\u7ec4\u6587\u4ef6,\u884c\u540d\u4e3a\u6837\u672c\u4fe1\u606f\uff0c\u7b2c\u4e00\u5217\u4e3a\u6837\u672c\u4fe1\u606f\uff0c\u7b2c\u4e8c\u5217\u4e3a\u4e9a\u578b\u5206\u7ec4\u4fe1\u606f\u3002<\/p>\n

          K3<-read.table(“K3.txt”,header=T,sep=”\\t”)<\/p>\n

          \"Dingtalk_20230713220537\"<\/p>\n

          #\u5408\u5e76\u514d\u75ab\u7ec6\u80de\u7ec4\u6210\u6587\u4ef6\u548c\u4e9a\u578b\u5206\u7ec4\u6587\u4ef6<\/p>\n

          final<-left_join(immune,K3,by=\u201dSample\u201d)<\/p>\n

          #\u957f\u5bbd\u6570\u636e\u8f6c\u6362<\/p>\n

          quanTIseq_cluster<-melt(final,id.vars=c(“Sample”,”Cluster”))<\/p>\n

          #\u8bbe\u7f6e\u5217\u540d<\/p>\n

          colnames(quanTIseq_cluster)<-c(“Sample”,”Cluster”,”celltype”,”quanTIseq”)<\/p>\n

          #\u7ed8\u5236\u663e\u8457\u5dee\u5f02\u5206\u6790\u5c0f\u63d0\u7434+\u7bb1\u7ebf\u56fe<\/p>\n

          boxplot_quanTIseq<- ggplot(quanTIseq_cluster, aes(x = celltype, y =quanTIseq ))+<\/p>\n

          labs(y=”quanTIseq”,x= “”)+<\/p>\n

          geom_boxplot(aes(fill = Cluster),position=position_dodge(0.5),width=0.5)+<\/p>\n

          scale_fill_npg()+<\/p>\n

          #\u4fee\u6539\u4e3b\u9898<\/p>\n

          theme_classic() +<\/p>\n

          theme(axis.title = element_text(size = 12,color =”black”),<\/p>\n

          axis.text = element_text(size= 12,color = “black”),<\/p>\n

          panel.grid.minor.y = element_blank(),<\/p>\n

          panel.grid.minor.x = element_blank(),<\/p>\n

          axis.text.x = element_text(angle = 45, hjust = 1 ),<\/p>\n

          panel.grid=element_blank(),<\/p>\n

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

          legend.text = element_text(size= 12),<\/p>\n

          legend.title= element_text(size= 12)<\/p>\n

          ) +<\/p>\n

          stat_compare_means(aes(group = Cluster),<\/p>\n

          label = “p.signif”,<\/p>\n

          method = “kruskal.test”,#kruskal.test\u591a\u7ec4\u68c0\u9a8c<\/p>\n

          hide.ns = F)#\u9690\u85cf\u4e0d\u663e\u8457\u7684<\/p>\n

          #\u4fdd\u5b58\u56fe\u7247<\/p>\n

          ggsave(file=”quanTIseq.pdf”,boxplot_quanTIseq,height=10,width=15)<\/p>\n

          \"Dingtalk_20230713174202\"<\/p>\n

          \u6700\u7ec8\u5c0f\u679c\u6210\u529f\u7684\u5bf9\u4e0d\u540c\u4e9a\u578b\u5229\u7528quanTIseq\u7b97\u6cd5\u8fdb\u884c\u4e86\u514d\u75ab\u6d78\u6da6\u5206\u6790\uff0c\uff0c\u770b\u8d77\u6765\u56fe\u7247\u6548\u679c\u975e\u5e38\u4e0d\u9519\uff0c\u6b22\u8fce\u5927\u5bb6\u548c\u5c0f\u679c\u4e00\u8d77\u8ba8\u8bba\u5b66\u4e60\u5440\uff01\u514d\u75ab\u6d78\u6da6\u76f8\u5173\u5206\u6790\u5185\u5bb9\uff0c\u4f8b\u5982\u5355\u6837\u672c\u5bcc\u96c6\u7b97\u6cd5\u5206\u6790\u514d\u75ab\u6d78\u6da6\u4e30\u5ea6(http:\/\/www.biocloudservice.com\/106\/106.php)\uff0c\u8ba1\u7b9764\u79cd\u514d\u75ab\u7ec6\u80de\u76f8\u5bf9\u542b\u91cf(http:\/\/www.biocloudservice.com\/107\/107.php)\uff0cpanImmune\u514d\u75ab\u6d78\u6da6\u5206\u6790(http:\/\/www.biocloudservice.com\/782\/782.php)\u7b49\u90fd\u53ef\u4ee5\u7528\u672c\u516c\u53f8\u65b0\u5f00\u53d1\u7684\u96f6\u4ee3\u7801\u4e91\u5e73\u53f0\u751f\u4fe1\u5206\u6790\u5c0f\u5de5\u5177\uff0c\u4e00\u952e\u5b8c\u6210\u8be5\u5206\u6790\u5965\uff0c\u611f\u5174\u8da3\u7684\u5c0f\u4f19\u4f34\u6b22\u8fce\u6765\u5c1d\u8bd5\u5965\uff0c\u7f51\u5740\uff1ahttp:\/\/www.biocloudservice.com\/home.html\u3002\u4eca\u5929\u5c0f\u679c\u7684\u5206\u4eab\u5c31\u5230\u8fd9\u91cc\uff0c\u4e0b\u671f\u5728\u89c1\u5965\u3002<\/p>","protected":false},"excerpt":{"rendered":"

          \u5c0f\u679c\u53c8\u6765\u5206\u4eab\u5566\uff01\u4eca\u5929\u5c0f\u679c\u4e3a\u5c0f\u4f19\u4f34\u5e26\u6765\u7684\u5206\u4eab\u4e3a\u5229\u7528quanTIseq\u7b97\u6cd5\u8fdb\u884c\u514d\u75ab\u6d78\u6da6\u5206\u6790\uff0c\u7136\u540e\u57fa\u4e8e\u4e9a\u578b\u5206\u7ec4\u4fe1\u606f\u6587 […]<\/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\/25529"}],"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=25529"}],"version-history":[{"count":1,"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=\/wp\/v2\/posts\/25529\/revisions"}],"predecessor-version":[{"id":25537,"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=\/wp\/v2\/posts\/25529\/revisions\/25537"}],"wp:attachment":[{"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=25529"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=25529"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=25529"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}