TCGA学习笔记13-对所有差异表达基因进行生存分析

发表于 | 分类于 | | 热度 °C

前面，我们以padj或FoldChange为依据筛选了TOP10基因，并进行了生存分析，但效果并不理想，原因很简单，因为不论是P值还是变化倍数，其实都与病例生存时间没有必然关联。这次，我们来对所有差异表达基因批量进行生存分析，看有多少基因影响病例生存，并且找找规律。

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> dim(result_select_annot) # 注释后的4863个基因
[1] 4863    8
> head(result_select_annot)
  ensembl_gene_id   baseMean log2FoldChange      lfcSE       stat
1 ENSG00000000938  1056.5419       1.507987 0.09991137  15.093251
2 ENSG00000001617  6403.7959       1.138046 0.08970727  12.686216
3 ENSG00000001630   218.0296      -1.154463 0.12005336  -9.616248
4 ENSG00000002586  9712.0493       1.265136 0.08533961  14.824725
5 ENSG00000002746   240.4362      -3.725467 0.22413035 -16.621875
6 ENSG00000002933 29346.9573       1.273440 0.12591051  10.113849
        pvalue         padj hgnc_symbol
1 1.793827e-51 2.147972e-50         FGR
2 7.051123e-37 4.970055e-36      SEMA3F
3 6.827609e-22 2.563747e-21     CYP51A1
4 1.013943e-49 1.138895e-48        CD99
5 4.839515e-62 8.093687e-61       HECW1
6 4.796218e-24 1.976151e-23    TMEM176A

> annot_symbol <- result_select_annot$hgnc_symbol
> length(annot_symbol)
[1] 4863
> annot_id <- result_select_annot$ensembl_gene_id
> length(annot_id)
[1] 4863
> annot_data <- data_select[match(result_select_annot$ensembl_gene_id,rownames(data_select)),]
> colnames(annot_data) <- substr(colnames(annot_data),1,15)
> head(annot_data)[,1:3]
                TCGA-CZ-5465-01 TCGA-BP-4355-01 TCGA-CZ-5451-01
ENSG00000000938             899            1211            1100
ENSG00000001617           16862           10888            9299
ENSG00000001630             310              77             305
ENSG00000002586           10729            8611            7618
ENSG00000002746               7              37               7
ENSG00000002933           60355           29448           47857
> dim(annot_data)
[1] 4863  611 # 数据准备就绪

> kidney_clinic$newID <- gsub("\\_diagnosis","\\-01",kidney_clinic$id)
> dim(kidney_clinic)
[1] 530  14
> head(kidney_clinic)
                      id classification_of_tumor tumor_stage gender
1 TCGA-CZ-5986_diagnosis            not reported     stage i   male
2 TCGA-CZ-4858_diagnosis            not reported    stage ii   male
3 TCGA-B8-5551_diagnosis            not reported     stage i female
4 TCGA-B0-4817_diagnosis            not reported   stage iii   male
5 TCGA-BP-4325_diagnosis            not reported     stage i female
6 TCGA-B0-4698_diagnosis            not reported    stage iv   male
  year_of_birth year_of_death year_of_diagnosis days_to_death age
1          1945  not reported              2006  not reported  61
2          1966  not reported              2005          2105  39
3          1945  not reported              2010  not reported  65
4          1921          2004              2002          1019  81
5          1937  not reported              2001  not reported  64
6          1928          2003              2003            42  75
  deadORlive                      race      alcohol years_smoked
1      Alive                     white Not Reported not reported
2       Dead                     white Not Reported not reported
3      Alive black or african american Not Reported not reported
4       Dead                     white Not Reported not reported
5      Alive                     white Not Reported not reported
6       Dead                     white Not Reported not reported
            newID
1 TCGA-CZ-5986-01
2 TCGA-CZ-4858-01
3 TCGA-B8-5551-01
4 TCGA-B0-4817-01
5 TCGA-BP-4325-01
6 TCGA-B0-4698-01
> km_plot <- apply(annot_data,1,function(x){ifelse(x>median(x),"up","down")})
> dim(km_plot)
[1]  611 4863
> head(km_plot)[,1:3]
                ENSG00000000938 ENSG00000001617 ENSG00000001630
TCGA-CZ-5465-01 "down"          "up"            "up"           
TCGA-BP-4355-01 "up"            "up"            "down"         
TCGA-CZ-5451-01 "up"            "up"            "up"           
TCGA-B0-5081-01 "up"            "up"            "down"         
TCGA-CZ-5454-11 "down"          "up"            "up"           
TCGA-B0-5697-01 "up"            "down"          "down"    
> km_plot_cancer <- km_plot[grepl("TCGA\\S{9}01",rownames(km_plot)),]
> dim(km_plot_cancer)
[1]  538 4863
> head(km_plot_cancer)[,1:3]
                ENSG00000000938 ENSG00000001617 ENSG00000001630
TCGA-CZ-5465-01 "down"          "up"            "up"           
TCGA-BP-4355-01 "up"            "up"            "down"         
TCGA-CZ-5451-01 "up"            "up"            "up"           
TCGA-B0-5081-01 "up"            "up"            "down"         
TCGA-B0-5697-01 "up"            "down"          "down"         
TCGA-A3-A8OV-01 "up"            "down"          "up"   
> kidney_clinic_km <- kidney_clinic[match(rownames(km_plot_cancer),kidney_clinic$newID),]
> dim(kidney_clinic_km)
[1] 538  14
> head(kidney_clinic_km)
                        id classification_of_tumor tumor_stage gender
274 TCGA-CZ-5465_diagnosis            not reported   stage iii female
358 TCGA-BP-4355_diagnosis            not reported   stage iii female
517 TCGA-CZ-5451_diagnosis            not reported    stage ii   male
119 TCGA-B0-5081_diagnosis            not reported   stage iii female
201 TCGA-B0-5697_diagnosis            not reported     stage i   male
484 TCGA-A3-A8OV_diagnosis            not reported     stage i   male
    year_of_birth year_of_death year_of_diagnosis days_to_death age
274          1931  not reported              2007          2564  76
358          1949          2010              2008           953  59
517          1932  not reported              2006  not reported  74
119          1926          2005              2005           362  79
201          1957  not reported              2007  not reported  50
484          1936  not reported              2011  not reported  75
    deadORlive                      race      alcohol years_smoked
274       Dead              not reported Not Reported not reported
358       Dead                     white Not Reported not reported
517      Alive                     white Not Reported not reported
119       Dead                     white Not Reported not reported
201      Alive                     white Not Reported not reported
484      Alive black or african american Not Reported           65
              newID
274 TCGA-CZ-5465-01
358 TCGA-BP-4355-01
517 TCGA-CZ-5451-01
119 TCGA-B0-5081-01
201 TCGA-B0-5697-01
484 TCGA-A3-A8OV-01
> daysToDeath <- as.numeric(as.character(kidney_clinic_km$days_to_death))
> daysToDeath
  [1] 2564  953   NA  362   NA   NA   62 1493   51   NA   NA   NA 1588
 [14]   NA  885 2227  137   NA   NA 1432   NA   NA   NA   NA   NA   NA
 [27] 1657   NA   18   NA 1964   NA  109   NA 1661   NA   NA   NA   NA
 [40]   NA   NA   NA   NA 1315 1404  562  445   NA   NA   NA   NA 1238
 [53]  182 1912   NA   NA   NA   NA 2454  344   NA 1913 1111   NA 1980
 [66]   NA  600 1003   NA   NA   NA   NA 2105 1371  334   NA 1337   NA
 [79]   NA   NA   NA   NA   NA   NA  727   NA   NA 2256   NA   NA   NA
 [92]  782   NA   NA   NA   NA   NA   NA   NA 1625   NA   NA   NA   NA
[105]   NA   NA  768   NA   NA   NA   NA   NA  563   NA 2145   NA   NA
[118]   NA  561   NA   NA   NA   NA   NA   NA   NA   NA 1200   NA   NA
[131]   NA   NA   NA   NA   NA   NA 1317   NA   NA   NA   NA   NA   NA
[144]  329   NA   NA   NA   NA  242   NA   NA  646   NA   NA   NA   NA
[157]  683  587  952    0   NA  320 1092   NA   NA   68  510   NA   NA
[170]  245    2   NA  793   NA   NA   NA 2601   NA   NA   NA 1714   NA
[183]   NA   NA 1230 1170 2386   NA  571  883 1912   NA   NA   NA 1986
[196]   NA 1091   NA   NA   NA   NA   NA 1417   NA   NA   65   NA   NA
[209]   NA   NA   NA   NA 1378   NA   NA   NA   NA   NA   NA   NA   NA
[222]   NA   NA  679  866   NA   NA   NA   NA   NA  330   NA   NA  885
[235]   NA  946   NA   NA  375   NA   NA   NA 1133   NA   NA  561   NA
[248]  431   NA 2764   NA   NA   NA   NA 1696   NA   42   NA   59    0
[261]   NA   NA   NA   NA   NA 1034 1270 1200 2241  333   NA   NA   NA
[274]   NA  342   NA  722   NA   NA 1075   NA   NA   NA   NA  709   NA
[287]   NA   NA   NA   NA   NA   NA   NA   NA   NA   NA   NA   NA  164
[300]   NA   NA   NA   NA   NA  701   69   NA   NA  574  106   NA   NA
[313]   NA   NA  475 1019   NA   NA   NA  162  845   NA   NA  552  139
[326]   NA   NA   NA   NA 1589   NA 1045  735   NA   NA   NA   NA   NA
[339]   NA   NA 1972  459   NA 2299   NA   NA   NA  819 1463   NA   NA
[352] 1724   NA   NA  313   NA   NA   NA  183   NA   NA   NA   NA   NA
[365]   NA   NA 1626  822   NA  206  932 1097   NA   NA   NA   NA   NA
[378]   NA   NA   NA  166  478   NA 1584   NA   NA   NA   NA  480   NA
[391]   NA  311   NA   NA   NA   NA  202   NA  927 1343 1590  454   NA
[404]  834   NA   NA   NA 2090 1598   NA 1639  878  992   NA   NA   NA
[417]   NA   43   NA 2419   NA   NA   NA   NA 1121   NA   NA   NA   NA
[430] 2343  485  110   NA   NA  313  204   NA   NA   NA  238   NA   NA
[443]   NA   NA   NA   NA  480   NA  168   NA   73   NA   NA  101   NA
[456]   NA   NA   NA  446 3615   NA  645   NA 1567   NA 3554   NA   NA
[469]   NA   NA   NA  139   NA   NA   NA  841   NA   NA  336   NA   NA
[482]   NA   99   NA   NA   NA   NA  637   NA   NA   NA   NA 1111   NA
[495]   NA   NA   77  770   NA   NA   NA   NA  222   NA   NA   NA   NA
[508]   41   NA   NA   NA   NA   NA   NA   NA   NA 1610  224   NA 1191
[521]   NA   93   NA   NA  307   NA  211   NA   NA 1625   NA  578   NA
[534]   NA   NA   NA   NA   NA
> daysToDeathN  <- ifelse(is.na(daysToDeath),max(na.omit(daysToDeath)),daysToDeath)
> daysToDeathN
  [1] 2564  953 3615  362 3615 3615   62 1493   51 3615 3615 3615 1588
 [14] 3615  885 2227  137 3615 3615 1432 3615 3615 3615 3615 3615 3615
 [27] 1657 3615   18 3615 1964 3615  109 3615 1661 3615 3615 3615 3615
 [40] 3615 3615 3615 3615 1315 1404  562  445 3615 3615 3615 3615 1238
 [53]  182 1912 3615 3615 3615 3615 2454  344 3615 1913 1111 3615 1980
 [66] 3615  600 1003 3615 3615 3615 3615 2105 1371  334 3615 1337 3615
 [79] 3615 3615 3615 3615 3615 3615  727 3615 3615 2256 3615 3615 3615
 [92]  782 3615 3615 3615 3615 3615 3615 3615 1625 3615 3615 3615 3615
[105] 3615 3615  768 3615 3615 3615 3615 3615  563 3615 2145 3615 3615
[118] 3615  561 3615 3615 3615 3615 3615 3615 3615 3615 1200 3615 3615
[131] 3615 3615 3615 3615 3615 3615 1317 3615 3615 3615 3615 3615 3615
[144]  329 3615 3615 3615 3615  242 3615 3615  646 3615 3615 3615 3615
[157]  683  587  952    0 3615  320 1092 3615 3615   68  510 3615 3615
[170]  245    2 3615  793 3615 3615 3615 2601 3615 3615 3615 1714 3615
[183] 3615 3615 1230 1170 2386 3615  571  883 1912 3615 3615 3615 1986
[196] 3615 1091 3615 3615 3615 3615 3615 1417 3615 3615   65 3615 3615
[209] 3615 3615 3615 3615 1378 3615 3615 3615 3615 3615 3615 3615 3615
[222] 3615 3615  679  866 3615 3615 3615 3615 3615  330 3615 3615  885
[235] 3615  946 3615 3615  375 3615 3615 3615 1133 3615 3615  561 3615
[248]  431 3615 2764 3615 3615 3615 3615 1696 3615   42 3615   59    0
[261] 3615 3615 3615 3615 3615 1034 1270 1200 2241  333 3615 3615 3615
[274] 3615  342 3615  722 3615 3615 1075 3615 3615 3615 3615  709 3615
[287] 3615 3615 3615 3615 3615 3615 3615 3615 3615 3615 3615 3615  164
[300] 3615 3615 3615 3615 3615  701   69 3615 3615  574  106 3615 3615
[313] 3615 3615  475 1019 3615 3615 3615  162  845 3615 3615  552  139
[326] 3615 3615 3615 3615 1589 3615 1045  735 3615 3615 3615 3615 3615
[339] 3615 3615 1972  459 3615 2299 3615 3615 3615  819 1463 3615 3615
[352] 1724 3615 3615  313 3615 3615 3615  183 3615 3615 3615 3615 3615
[365] 3615 3615 1626  822 3615  206  932 1097 3615 3615 3615 3615 3615
[378] 3615 3615 3615  166  478 3615 1584 3615 3615 3615 3615  480 3615
[391] 3615  311 3615 3615 3615 3615  202 3615  927 1343 1590  454 3615
[404]  834 3615 3615 3615 2090 1598 3615 1639  878  992 3615 3615 3615
[417] 3615   43 3615 2419 3615 3615 3615 3615 1121 3615 3615 3615 3615
[430] 2343  485  110 3615 3615  313  204 3615 3615 3615  238 3615 3615
[443] 3615 3615 3615 3615  480 3615  168 3615   73 3615 3615  101 3615
[456] 3615 3615 3615  446 3615 3615  645 3615 1567 3615 3554 3615 3615
[469] 3615 3615 3615  139 3615 3615 3615  841 3615 3615  336 3615 3615
[482] 3615   99 3615 3615 3615 3615  637 3615 3615 3615 3615 1111 3615
[495] 3615 3615   77  770 3615 3615 3615 3615  222 3615 3615 3615 3615
[508]   41 3615 3615 3615 3615 3615 3615 3615 3615 1610  224 3615 1191
[521] 3615   93 3615 3615  307 3615  211 3615 3615 1625 3615  578 3615
[534] 3615 3615 3615 3615 3615
> fit <- Surv(daysToDeathN,ifelse(kidney_clinic_km$deadORlive=="Dead",1,0)==1)
> p <- rep(0,length(annot_id)) # 定义变量p，放p value
> s <- rep(0,length(annot_id)) # 定义变量s，放surv，即生存预期
> for(i in 1:length(annot_id)){
+   m <- survdiff(fit~km_plot_cancer[,i])
+   p[i] <- 1 - pchisq(m$chisq, length(m$n) -1)
+   s[i] <- ifelse(m$obs[1]/m$n[[1]] > m$obs[2]/m$n[[2]],0,1) # 0=低表达生存预期差，高表达生存预期好；1=低表达生存预期好，高表达生存预期差；
+ }
> class(p)
[1] "numeric"
> length(p)
[1] 4863
> class(s)
[1] "numeric"
> length(s)
[1] 4863
> table(s)
s
   0    1 
2245 2618 # 大致各一半

> result_select_annot$survP <- p
> dim(result_select_annot)
[1] 4863    9 # 多出新的一列
> head(result_select_annot)
  ensembl_gene_id   baseMean log2FoldChange      lfcSE       stat
1 ENSG00000000938  1056.5419       1.507987 0.09991137  15.093251
2 ENSG00000001617  6403.7959       1.138046 0.08970727  12.686216
3 ENSG00000001630   218.0296      -1.154463 0.12005336  -9.616248
4 ENSG00000002586  9712.0493       1.265136 0.08533961  14.824725
5 ENSG00000002746   240.4362      -3.725467 0.22413035 -16.621875
6 ENSG00000002933 29346.9573       1.273440 0.12591051  10.113849
        pvalue         padj hgnc_symbol        survP
1 1.793827e-51 2.147972e-50         FGR 9.088360e-01
2 7.051123e-37 4.970055e-36      SEMA3F 2.033993e-03
3 6.827609e-22 2.563747e-21     CYP51A1 1.373636e-05
4 1.013943e-49 1.138895e-48        CD99 3.377814e-01
5 4.839515e-62 8.093687e-61       HECW1 7.404867e-01
6 4.796218e-24 1.976151e-23    TMEM176A 7.017783e-01
> result_select_annot$surv <- s
> dim(result_select_annot)
[1] 4863   10 # 又多出一列
> head(result_select_annot)
  ensembl_gene_id   baseMean log2FoldChange      lfcSE       stat
1 ENSG00000000938  1056.5419       1.507987 0.09991137  15.093251
2 ENSG00000001617  6403.7959       1.138046 0.08970727  12.686216
3 ENSG00000001630   218.0296      -1.154463 0.12005336  -9.616248
4 ENSG00000002586  9712.0493       1.265136 0.08533961  14.824725
5 ENSG00000002746   240.4362      -3.725467 0.22413035 -16.621875
6 ENSG00000002933 29346.9573       1.273440 0.12591051  10.113849
        pvalue         padj hgnc_symbol        survP surv
1 1.793827e-51 2.147972e-50         FGR 9.088360e-01    0
2 7.051123e-37 4.970055e-36      SEMA3F 2.033993e-03    0
3 6.827609e-22 2.563747e-21     CYP51A1 1.373636e-05    0
4 1.013943e-49 1.138895e-48        CD99 3.377814e-01    1
5 4.839515e-62 8.093687e-61       HECW1 7.404867e-01    0
6 4.796218e-24 1.976151e-23    TMEM176A 7.017783e-01    0
> result_survP <- result_select_annot[result_select_annot$survP < 0.001,] # 筛选survP<0.001的基因，共922个 
> dim(result_survP)
[1] 922   9
> head(result_survP)
   ensembl_gene_id   baseMean log2FoldChange     lfcSE       stat
3  ENSG00000001630   218.0296      -1.154463 0.1200534  -9.616248
20 ENSG00000005108  2576.9645      -1.624881 0.1633055  -9.949951
36 ENSG00000007314   397.9782       1.635177 0.1774570   9.214498
47 ENSG00000008988 45747.5469       1.061020 0.0931570  11.389586
49 ENSG00000009765   462.9210      -4.288686 0.2380812 -18.013543
54 ENSG00000010319  2118.5841      -1.634110 0.1484228 -11.009836
         pvalue         padj hgnc_symbol        survP surv
3  6.827609e-22 2.563747e-21     CYP51A1 1.373636e-05    0
20 2.523085e-23 1.004634e-22      THSD7A 2.232279e-04    0
36 3.127375e-20 1.092412e-19       SCN4A 3.566491e-05    0
47 4.712258e-30 2.505970e-29       RPS20 1.083688e-04    1
49 1.525459e-72 3.707111e-71         IYD 2.896293e-04    0
54 3.426265e-28 1.691118e-27      SEMA3G 4.535900e-08    0

最终筛选出来的这922个基因，符合FoldChange > 2 && pvalue < 0.001 && survP < 0.001，下面，我们给这些基因分个组，

1）HG，在肿瘤中表达上调，且高表达生存预期好；log2FoldChange > 1 && surv = 0
2）HB，在肿瘤中表达上调，且高表达生存预期坏，暂且认为是原癌基因；log2FoldChange > 1 && surv = 1
3）LG，在肿瘤中表达下调，且高表达生存预期好，暂且认为是抑癌基因；log2FoldChange < -1 && surv = 0
4）LB，在肿瘤中表达下调，且高表达生存预期坏；log2FoldChange < -1 && surv = 1

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> result_survP_HG <- result_survP[result_survP$log2FoldChange > 1 & result_survP$surv == 0,]
> result_survP_HB <- result_survP[result_survP$log2FoldChange > 1 & result_survP$surv == 1,]
> result_survP_LG <- result_survP[result_survP$log2FoldChange < -1 & result_survP$surv == 0,]
> result_survP_LB <- result_survP[result_survP$log2FoldChange < -1 & result_survP$surv == 1,]

> dim(result_survP_HG)
[1] 141  10
> dim(result_survP_HB)
[1] 416  10
> dim(result_survP_LG)
[1] 314  10
> dim(result_survP_LB)
[1] 51 10

看一下这四个集合的基因

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> result_survP_HG$hgnc_symbol
  [1] "SCN4A"       "NRXN3"       "TLL1"        "ATP11A"     
  [5] "VASH1"       "ADCY2"       "SCGN"        "NRP1"       
  [9] "SLC5A1"      "BMX"         "FLT1"        "RGCC"       
 [13] "GRB10"       "PRUNE2"      "DOCK8"       "LIPA"       
 [17] "VWF"         "SLC17A2"     "HAVCR1"      "HHLA2"      
 [21] "SLC1A4"      "PCDH17"      "TEX11"       "IQSEC3"     
 [25] "TMEM131L"    "PREX1"       "COL21A1"     "CD93"       
 [29] "MCF2L"       "MASP1"       "F2RL3"       "FBXL16"     
 [33] "KDR"         "ACLY"        "PER2"        "ETS1"       
 [37] "DYSF"        "TM6SF1"      "HECW2"       "CLEC18B"    
 [41] "CDH13"       "RGS5"        "HMCN1"       "RIT1"       
 [45] "MALL"        "MARCHF4"     "SLC10A6"     "ARHGAP26"   
 [49] "GFOD1"       "SLC17A4"     "DIAPH2"      "PLIN2"      
 [53] "CDKN2B"      "ANO4"        "PDK1"        "PTPRR"      
 [57] "LURAP1L"     "ENPP3"       "PIEZO2"      "SLC28A1"    
 [61] "FZD1"        "TSPAN18"     "GALNT14"     "ABCG1"      
 [65] "ADGRL4"      "SPATA18"     "TGFA"        "SPRY1"      
 [69] "TLR3"        "TMEM200A"    "SLC18A2"     "BTNL9"      
 [73] "ARHGAP42"    "GALR1"       "KCNAB1"      "DPY19L2P2"  
 [77] "PDGFD"       "INSR"        "CYSLTR1"     "ARL10"      
 [81] "BNIP3"       "CLEC14A"     ""            "SCN4B"      
 [85] "RIMKLA"      "DNAJC22"     "APOLD1"      "EXOC3L1"    
 [89] "CDH4"        "CDH5"        "NLRP11"      "P2RY8"      
 [93] ""            "F8"          "QRFPR"       "ZNF395"     
 [97] "C3orf70"     "SPRY4"       "PEAK3"       "LRRK2"      
[101] "CTSE"        "GIMAP5"      "SLC22A4"     "BNIP3P1"    
[105] "AVPR1B"      "TRIM15"      "INSYN2B"     "C17orf107"  
[109] ""            ""            "LDHAP4"      "ZNF812P"    
[113] "NPY6R"       "LINC01738"   "UBTFL6"      "PRKAR1B-AS2"
[117] ""            "HS1BP3-IT1"  ""            ""           
[121] "LDHAP3"      "GGT8P"       "LILRA4"      "ACAD11"     
[125] "VWFP1"       ""            ""            ""           
[129] ""            "LINC01843"   "SHANK3"      "PTP4A2P2"   
[133] "PABPC4L"     "LINC02747"   "SLC5A8"      ""           
[137] ""            "PECAM1"      ""            ""           
[141] ""           
> result_survP_HB$hgnc_symbol
  [1] "RPS20"        "PLAUR"        "DDX11"        "TACC3"       
  [5] "SLC38A5"      "SLC11A1"      "DEF6"         "TYMP"        
  [9] "RNASET2"      "SH2D2A"       "POU2F2"       "RTN4R"       
 [13] "FOXP3"        "CYBA"         "YBX3"         "COL11A1"     
 [17] "VMP1"         "CHI3L2"       "CACNB1"       "CLEC2D"      
 [21] "TRIP13"       "GSDMB"        "PPP2R2C"      "GTSE1"       
 [25] "ACTN2"        "NDC80"        "CXCL2"        "RAD54L"      
 [29] "PPEF1"        "ACHE"         "TPX2"         "BIRC5"       
 [33] "LAG3"         "DTX2"         "TF"           "ORC6"        
 [37] "RGS17"        "UNC13D"       "HSD3B7"       "DERL3"       
 [41] "OSM"          "LGALS1"       "CENPM"        "HDAC10"      
 [45] "POLE2"        "CDKN3"        "MMP9"         "MYBL2"       
 [49] "PABPC1L"      "SLC17A9"      "PTK6"         "TRIB3"       
 [53] "PIM2"         "TAZ"          "TIMP1"        "RRN3P2"      
 [57] "PYCARD"       "AQP9"         "IGDCC4"       "PDGFRL"      
 [61] "KCNN4"        "GRIN2D"       "JAK3"         "HAMP"        
 [65] "PBX4"         "HOXA13"       "NSUN5P2"      "TFR2"        
 [69] "RAPGEFL1"     "KAT2A"        "CNTNAP1"      "DLX4"        
 [73] "NEIL3"        "HPX"          "MDK"          "TCIRG1"      
 [77] "CDCA3"        "KIF20A"       "STEAP3"       "CENPA"       
 [81] "TPSG1"        "KIAA1324"     "OPRD1"        "CDC20"       
 [85] "NEK2"         "CCDC18"       "DDX39A"       "CENPK"       
 [89] "HJURP"        "BATF3"        "WFDC3"        "TNFSF14"     
 [93] "RBCK1"        "IGFLR1"       "HCST"         "IDUA"        
 [97] "PKMYT1"       "CHTF18"       "LRFN1"        "CPA4"        
[101] "ATP8B3"       "FCHO1"        "C1QL1"        "THOC6"       
[105] "PODNL1"       "SERPINF1"     "C1QTNF6"      "FKBP11"      
[109] "IL15RA"       "SPOCD1"       "CDCA8"        "SLC43A3"     
[113] "OASL"         "TROAP"        "SLC9A5"       "CCM2"        
[117] "LIMD2"        "CD72"         "SLCO5A1"      "ITPKA"       
[121] "CEP55"        "ZNF365"       "ADAMTS14"     "INHBE"       
[125] "GPR84"        "MAP3K12"      "BCL2A1"       "PIF1"        
[129] "TICRR"        "PRELID3A"     "ASGR1"        "CARD14"      
[133] "FKBP10"       "EMP3"         "SH3BGRL3"     "KIF2C"       
[137] "NUF2"         "TMEM44"       "DOK3"         "NFKBIE"      
[141] "MTFR2"        "SLC25A37"     "PRSS53"       "ADAM8"       
[145] "CCDC74B"      "SPC25"        "TRIM36"       "SKA1"        
[149] "GOLGA7B"      "BATF"         "BUB1B"        "ZFHX2-AS1"   
[153] "CDC25C"       "DUSP23"       "NBL1"         "RUNX1"       
[157] "C1R"          "PPP1R35"      "HK3"          "SYCE2"       
[161] "SPC24"        "CCDC78"       "TEDC2"        "LBHD1"       
[165] "CCDC74A"      "DCST2"        "TRIM46"       "RPL22L1"     
[169] "CXCL1"        "UCN"          "SPDYA"        "PTTG1"       
[173] "AGBL2"        "PLEKHF1"      "MSS51"        "PKD1L2"      
[177] "FAM86GP"      "CATSPER2"     "PCLAF"        "PLK1"        
[181] "MEI1"         "PRRX2"        "ENGASE"       "TEPSIN"      
[185] "VKORC1"       "JSRP1"        "CORO6"        "TTYH1"       
[189] "TRPV3"        "CCDC88B"      "REEP4"        "THBS3"       
[193] "NPIPB3"       "RNASE2"       "BUB1"         "CHRNA5"      
[197] "MZB1"         "OSCAR"        "ZNF692"       "RRM2"        
[201] "LRRC15"       "CEBPB"        "MZT2A"        "SAA1"        
[205] "NABP1"        "CD7"          "C1QTNF1"      "IL20RB"      
[209] "RIN1"         "CNIH2"        "UBE2C"        "GOLGA8A"     
[213] "CATSPER1"     "B3GNTL1"      "SPHK1"        "CLK2"        
[217] "C8G"          "LRRN4CL"      "CPNE7"        "MSC"         
[221] "RFLNA"        "AURKB"        "LBX2"         "DNHD1"       
[225] "TMEM86B"      "MAP6D1"       "ARL6IP4"      "B4GALNT4"    
[229] "KCNJ14"       "FBXL6"        "C1S"          "CCNYL2"      
[233] "PYCR1"        "GPR19"        "NPIPA1"       "BMP8A"       
[237] "CHEK2"        "IQGAP3"       "DUSP5P1"      "STAC3"       
[241] "IRF7"         "PRAME"        "KIF18B"       "TNFRSF18"    
[245] "PLEKHN1"      "ISG15"        "FANCA"        "EIF4EBP1"    
[249] "TPRG1"        "RUFY4"        "ZP3"          "NPIPP1"      
[253] "SLC4A5"       "FAM78B"       "SNHG17"       "PDLIM7"      
[257] "ADAM32"       "RAD54B"       "ELOVL2"       "GOLGA6L9"    
[261] "FCGR1B"       "MMP17"        "RYR2"         "PLXNB3"      
[265] ""             "AGAP6"        "LILRB3"       "GABBR1"      
[269] "SYCE1L"       "MUC12"        "DUXAP8"       "IGKC"        
[273] "IGLV1-47"     "IGLV1-44"     "IGLV3-19"     "IGLC2"       
[277] "IGLC3"        "IGHG4"        "IGHG2"        "IGHA1"       
[281] "IGHG1"        "IGHG3"        "CRYGS"        "ASIC3"       
[285] "MXD3"         "RPLP1P6"      "LAT"          "RPL17P50"    
[289] "PPM1N"        "LTB4R"        "NPEPL1"       "IFI30"       
[293] "PRELID1P1"    "PAM16"        ""             "ZGLP1"       
[297] "FADS3"        "CYTOR"        "TSSC2"        ""            
[301] "C5orf66"      "ZMIZ1-AS1"    "MIAT"         "LINC00115"   
[305] ""             ""             "SLC16A1-AS1"  "LINC00511"   
[309] "LTB"          ""             "MELTF-AS1"    "DPY19L1P1"   
[313] ""             ""             "CYP21A2"      "SNHG15"      
[317] "LINC02609"    "YEATS2-AS1"   ""             ""            
[321] "LINC01871"    "KDM4A-AS1"    "MAP3K2-DT"    "PRKAR1B-AS1" 
[325] "FOXD2-AS1"    "PCDHGC5"      "CFB"          "NPIPB5"      
[329] "APOBEC3D"     ""             "IGKV3-15"     ""            
[333] ""             ""             "LINC00926"    "TNXA"        
[337] "LUCAT1"       ""             "SRD5A3-AS1"   "PVT1"        
[341] ""             ""             "IGHGP"        ""            
[345] "IGLL5"        "AGAP2-AS1"    ""             ""            
[349] "KLRA1P"       "PPP1R14B-AS1" "HP"           ""            
[353] "IFITM3P6"     "LINC02328"    "MC1R"         "ZHX1-C8orf76"
[357] ""             ""             "LINC01355"    "VPS9D1-AS1"  
[361] ""             "SMG1P7"       "H2BC20P"      ""            
[365] "CORO7"        ""             ""             ""            
[369] ""             ""             ""             ""            
[373] ""             ""             ""             ""            
[377] ""             ""             ""             ""            
[381] ""             ""             ""             ""            
[385] "GTF2IP20"     ""             ""             ""            
[389] ""             ""             ""             ""            
[393] ""             "EPOP"         ""             "NOL12"       
[397] "LINC01138"    ""             "TBC1D3L"      ""            
[401] ""             ""             ""             ""            
[405] ""             ""             ""             ""            
[409] ""             ""             ""             ""            
[413] ""             ""             ""             "HELLPAR"     
> result_survP_LG$hgnc_symbol
  [1] "CYP51A1"    "THSD7A"     "IYD"        "SEMA3G"     "CHDH"      
  [6] "SLC7A9"     "NDUFS1"     "USP2"       "VPS13D"     "KITLG"     
 [11] "NEDD4L"     "FSTL4"      "AP5M1"      "SYNE2"      "CYFIP2"    
 [16] "ZMYND12"    "MPPED2"     "FECH"       "PTPN3"      "RPS6KA6"   
 [21] "LNX1"       "MPP5"       "EVC"        "FRY"        "NTN4"      
 [26] "ACAT1"      "FMO4"       "NEBL"       "CEACAM1"    "FDFT1"     
 [31] "OPHN1"      "MAGI3"      "COL4A4"     "CADPS2"     "COBLL1"    
 [36] "TRPM3"      "ABCB1"      "L2HGDH"     "PTPN4"      "JPH4"      
 [41] "XYLB"       "SMIM24"     "ERMP1"      "MIOX"       "CDKL1"     
 [46] "DCAF11"     "MCF2"       "CAB39L"     "VWA8"       "TOX3"      
 [51] "CA2"        "SH2D4A"     "DHDH"       "COBL"       "TMEM245"   
 [56] "BAG1"       "CPEB3"      "PBLD"       "TBC1D9"     "TRIM2"     
 [61] "PPARGC1A"   "AKAP3"      "FRK"        "NCOA7"      "EPM2A"     
 [66] "SEMA5A"     "NNT"        "AGXT2"      "CPEB4"      "HYAL1"     
 [71] "ATP6V1A"    "EPB41L5"    "TACR1"      "PLCL1"      "PARD3B"    
 [76] "WLS"        "AGMAT"      "HAO2"       "ACADM"      "ABCD3"     
 [81] "IRF6"       "TREH"       "ECRG4"      "BSPRY"      "ALDH6A1"   
 [86] "GOT1"       "TEK"        "EPHX2"      "PDZRN3"     "CAT"       
 [91] "PLG"        "PCK1"       "SCGB1D2"    "FLRT3"      "PLEKHG3"   
 [96] "PODXL"      "HOXD1"      "HOXD3"      "SYNE1"      "SLC34A1"   
[101] "NAPSA"      "G6PC"       "FMO5"       "ZNF132"     "DDC"       
[106] "ENAM"       "ANGPTL3"    "MYH10"      "KL"         "BEX2"      
[111] "GSTM3"      "VAV3"       "HMGCS2"     "MYCN"       "CLDN10"    
[116] "FBXO21"     "EDAR"       "TBC1D4"     "SUCLA2"     "LMO7"      
[121] "ALDOB"      "BPHL"       "SORL1"      "PAQR5"      "SEMA6D"    
[126] "DBT"        "ARHGAP24"   "GPAT3"      "FRAS1"      "CDKL2"     
[131] "SHROOM3"    "HADH"       "PELI2"      "SLC27A2"    "SLC14A1"   
[136] "ERBB2"      "CGN"        "GDF7"       "CTDSPL"     "ALDH1L1"   
[141] "SCD5"       "USP53"      "UGT3A1"     "BHMT"       "IQGAP2"    
[146] "CRHBP"      "SLC25A48"   "MMUT"       "CYP39A1"    "MFHAS1"    
[151] "AK3"        "AUH"        "ALAD"       "SLC25A25"   "CNNM2"     
[156] "SLC5A12"    "GLYAT"      "SLC22A8"    "TMEM25"     "MPP7"      
[161] "DLG2"       "FREM2"      "THRB"       "ANK3"       "NR3C2"     
[166] "ASAP2"      "SLC25A4"    "GPD1L"      "SLC16A12"   "PANK1"     
[171] "MARVELD2"   "FRMD1"      "KCNJ16"     "PGM5"       "SFXN2"     
[176] "FUT6"       "DHRS4"      "KCNJ15"     "PAFAH2"     "WNT9B"     
[181] "CPAMD8"     "PTH1R"      "MYL3"       "CYP3A7"     "NAPEPLD"   
[186] "TMEM82"     "AKR7A3"     "CDS1"       "PTPN13"     "DNASE1L3"  
[191] "RBM47"      "EMCN"       "HPGD"       "ADGRV1"     "TMEM174"   
[196] "RAET1E"     "FREM1"      "MYORG"      "FBP1"       "SLC16A9"   
[201] "CRYL1"      "EML5"       "NDRG2"      "CCDC186"    "OTOGL"     
[206] "CLMN"       "WDR72"      "CDH16"      "LDHD"       "GLYATL1"   
[211] "MTMR10"     "CA4"        "ACOX2"      "GJB1"       "PKHD1"     
[216] "FUT3"       "UGT2B7"     "CLCN5"      "GPHN"       "GATM"      
[221] "TLN2"       "SUCLG2"     "SLC22A13"   "NUDT4"      "JUP"       
[226] "SLC25A30"   "ZHX3"       "SLC6A19"    "MFSD4A"     "PCCA"      
[231] "TOM1L2"     "KDF1"       "MSRA"       "HSD11B2"    "GNG7"      
[236] "RNF152"     "GCNT4"      "SHMT1"      "GRAMD1C"    ""          
[241] "KLHDC7A"    "TCAIM"      "MTURN"      "WDFY3-AS2"  "PAQR7"     
[246] "C11orf54"   "SLC8A1"     "ZNRF3"      "LRRC55"     "ST6GALNAC3"
[251] "PRKD1"      "CCSER1"     "LRRC19"     "ROBO2"      "HS6ST3"    
[256] "PBX1"       "SYN3"       "SOWAHB"     "PPARA"      "AKR1C1"    
[261] "TSPYL4"     "TCL6"       "MEIS3P2"    "SHISA6"     "TSPYL1"    
[266] "KAZN"       "ACADSB"     "AJAP1"      "MYO6"       "SMIM10L2B" 
[271] "OGDHL"      "OCLN"       "SLC22A12"   "KIF13B"     "SLC22A6"   
[276] "HIBCH"      "PEG3"       "ARC"        "LRBA"       "ECI2"      
[281] "MTOR"       "BHLHB9"     "SLC44A4"    "ZNF204P"    "CYS1"      
[286] "SYNJ2BP"    "B3GNT10"    "TTC3P1"     "ZNF844"     "PSMG3-AS1" 
[291] "LINC00271"  ""           "RAP2C-AS1"  ""           ""          
[296] "RPL34-AS1"  ""           "MKLN1-AS"   "SUCLG2-AS1" "LINC02027" 
[301] "C1orf210"   ""           ""           ""           ""          
[306] ""           ""           ""           "DYNLL2"     ""          
[311] ""           ""           ""           "PWAR5"     
> result_survP_LB$hgnc_symbol
 [1] "CLDN11"   "GPRC5A"   "GYG2"     "STYK1"    "BCAS1"    "IGF2BP2" 
 [7] "SULT2B1"  "EPB41L4B" "CAPS"     "PTGDS"    "DNAJC12"  "VTN"     
[13] "SLPI"     "CHAC1"    "PSAT1"    "PPP1R1A"  "KCNH3"    "WNT10A"  
[19] "TFAP2A"   "CILP"     "BMPR1B"   "NECTIN4"  "SUSD4"    "ATP6V1C2"
[25] "SSC4D"    "PLEKHG4B" "FAM167A"  "PROM2"    "PPM1J"    "SIM2"    
[31] "TLCD1"    "BNIPL"    "LIPH"     "MELTF"    "SHOC1"    "SCNN1B"  
[37] "PHYHIP"   "LRRN2"    "HOXB9"    "CEL"      "MUC13"    "B3GNT8"  
[43] "SMCO3"    "WT1"      "CLCNKA"   "DNER"     "SERPINA5" "L1CAM"   
[49] "GEMIN8P4" "MRPS6"    "TRNP1"

有了这个基因列表，后续可以进行富集分析或者GSEA分析。

  • 本文作者：括囊无誉
  • 本文链接： TCGA/TCGA13Survival/
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