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Output - mRNA data (correlation)
Dataset:
mRNAseq_325
Gene A:
ADAMTSL4
Gene B:
CD274
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CGGA.ID PRS.type Histology Grade Gender OS Censor Age IDH.mutation.status 1p19q.codel.status Gene.A.Expression Gene.B.Expression CGGA_1001 Primary GBM WHO IV Male 3817 0 11 Wildtype Non-codel 6.78 3.68 CGGA_1006 Primary AA WHO III Male 254 1 42 Wildtype Non-codel 2.06 3.39 CGGA_1007 Primary GBM WHO IV Female 345 1 57 Wildtype Non-codel 3.94 0.85 CGGA_1011 Primary GBM WHO IV Female 109 1 46 Wildtype Non-codel 3.16 4.12 CGGA_1015 Primary GBM WHO IV Male 164 1 62 Wildtype Non-codel 3.53 4.46 CGGA_1019 Recurrent rGBM WHO IV Male 212 1 60 Wildtype Non-codel 5 2.18 CGGA_1022 Recurrent rA WHO II Female 518 0 62 Wildtype Non-codel 5.81 7.11 CGGA_1023 Primary GBM WHO IV Female 681 1 56 Wildtype Non-codel 5.9 0.94 CGGA_1024 Primary GBM WHO IV Male 3074 1 64 Wildtype Non-codel 2.8 1.39 CGGA_1026 Primary GBM WHO IV Male 1570 1 57 Wildtype Non-codel 0.91 1.5 CGGA_1034 Primary AA WHO III Male 753 1 23 Wildtype Non-codel 3.96 3.04 CGGA_1035 Primary GBM WHO IV Female 567 1 60 Wildtype Non-codel 17.63 8.03 CGGA_1039 Primary GBM WHO IV Male 727 1 40 Wildtype Non-codel 1.1 0.55 CGGA_1045 Primary GBM WHO IV Male 348 1 79 Wildtype Non-codel 6.27 12.2 CGGA_1049 Primary GBM WHO IV Male 809 1 58 Wildtype Non-codel 15.79 2.46 CGGA_1052 Primary O WHO II Male NA NA 41 Mutant Codel 0.56 0.58 CGGA_1072 Primary GBM WHO IV Male 1090 1 26 Wildtype Non-codel 2.4 1.8 CGGA_1077 Primary GBM WHO IV Male 591 1 47 Wildtype Non-codel 4.26 2.05 CGGA_1078 Recurrent rGBM WHO IV Female 315 1 61 Wildtype Non-codel 1.97 3.85 CGGA_1079 Primary AA WHO III Male 471 1 38 Wildtype Non-codel 3.87 2.42 CGGA_1081 Recurrent rAA WHO III Female 216 1 30 Wildtype Non-codel 1.69 0.57 CGGA_1083 Primary GBM WHO IV Male 450 1 59 Wildtype Non-codel 4.48 2.43 CGGA_1091 Primary GBM WHO IV Female 1116 1 51 Wildtype Non-codel 2.73 0.86 CGGA_1109 Primary GBM WHO IV Male 1348 1 42 Wildtype Non-codel 1.87 2.97 CGGA_1124 Primary GBM WHO IV Male 484 1 47 Wildtype Non-codel 5.77 10.63 CGGA_1139 Primary GBM WHO IV Female 1196 1 53 Wildtype Non-codel 2.51 0.23 CGGA_1140 Recurrent rAA WHO III Female 921 1 49 Wildtype Non-codel 0.13 0.98 CGGA_1145 Recurrent rAA WHO III Male 239 1 41 Wildtype Non-codel 2.92 18.06 CGGA_1171 Primary GBM WHO IV Male 412 1 40 Wildtype Non-codel 9.37 2.5 CGGA_1177 Recurrent rGBM WHO IV Male 449 1 40 Wildtype Non-codel 6.75 3.69 CGGA_1180 Primary GBM WHO IV Female 1226 0 48 Wildtype Non-codel 3.39 2.32 CGGA_1188 Secondary sGBM WHO IV Female 256 1 30 Mutant Non-codel 3.37 1.19 CGGA_1214 Primary GBM WHO IV Female 604 1 49 Wildtype Non-codel 4.06 0.63 CGGA_1216 Primary GBM WHO IV Male 312 1 44 Wildtype Non-codel 8.44 1.06 CGGA_1218 Secondary sGBM WHO IV Male 286 1 53 Wildtype Non-codel 4.29 3.93 CGGA_1224 Primary GBM WHO IV Male 271 1 57 Wildtype Non-codel 9.17 2.56 CGGA_1234 Primary GBM WHO IV Male 705 1 32 Wildtype Non-codel 2.72 3.94 CGGA_1237 Primary GBM WHO IV Male 296 1 62 Wildtype Non-codel 1.55 2.75 CGGA_1240 Primary GBM WHO IV Male 19 1 33 Wildtype Non-codel 4.13 9.12 CGGA_1251 Primary GBM WHO IV Female 272 1 42 Wildtype Non-codel 2.08 1.06 CGGA_1258 Primary GBM WHO IV Male 114 1 42 Wildtype Non-codel 6.24 0.98 CGGA_1263 Primary AA WHO III Male 772 1 50 Wildtype Non-codel 3.3 1.17 CGGA_1270 Primary GBM WHO IV Female 188 1 60 Wildtype Non-codel 5.96 1.94 CGGA_1271 Recurrent rGBM WHO IV Male 523 1 17 Wildtype Non-codel 6.3 1.38 CGGA_1272 Secondary sGBM WHO IV Male 124 1 32 Mutant Non-codel 1.45 1.02 CGGA_1280 Primary AA WHO III Male 447 1 74 Wildtype Non-codel 7.55 0.9 CGGA_1281 Primary AA WHO III Male 2909 0 45 Wildtype Codel 0.43 0.86 CGGA_1283 Secondary sGBM WHO IV Male 20 1 17 Wildtype Non-codel 0.72 0.22 CGGA_1284 Primary AA WHO III Male 97 1 73 Wildtype Non-codel 6.52 7.23 CGGA_1285 Recurrent rGBM WHO IV Female 79 1 58 Wildtype Non-codel 17.61 0.31 CGGA_1292 Primary AA WHO III Male 2901 0 17 Wildtype Non-codel 0.55 0.67 CGGA_1299 Primary GBM WHO IV Male 550 1 54 Wildtype Non-codel 2.29 0.58 CGGA_1301 Secondary sGBM WHO IV Male 239 1 48 Wildtype Non-codel 1.39 2.56 CGGA_1313 Primary GBM WHO IV Male 379 1 42 Wildtype Non-codel 4.25 11.51 CGGA_1320 Primary GBM WHO IV Male 59 1 19 Wildtype Non-codel 30.45 0.44 CGGA_1332 Primary GBM WHO IV Female 510 0 55 Wildtype Non-codel 3.04 0.22 CGGA_1338 Primary GBM WHO IV Female 1122 1 61 Wildtype Non-codel 7.21 5.06 CGGA_1340 Primary AA WHO III Male 1109 1 35 Wildtype Non-codel 2.01 0.86 CGGA_1342 Primary GBM WHO IV Male 186 1 47 Wildtype Non-codel 6.13 4.64 CGGA_1343 Recurrent rGBM WHO IV Male 94 1 34 Wildtype Non-codel 1.36 2 CGGA_1346 Secondary sGBM WHO IV Female 284 1 57 Wildtype Non-codel 3.91 3.21 CGGA_1370 Recurrent rGBM WHO IV Male 325 0 43 Wildtype Non-codel 3.81 0.21 CGGA_1393 Secondary sGBM WHO IV Male 275 1 41 Wildtype Non-codel 3.84 3.75 CGGA_1408 Primary AA WHO III Female 1362 1 64 Wildtype Non-codel 2.57 1.41 CGGA_1411 Recurrent rAA WHO III Female 329 1 40 Wildtype Non-codel 3.99 2.05 CGGA_235 Primary O WHO II Male 2340 1 24 Mutant Codel 0.59 0.36 CGGA_269 Primary A WHO II Female 2932 0 45 Wildtype Non-codel 2.44 2.21 CGGA_272 Secondary sGBM WHO IV Male 217 1 51 Wildtype Non-codel 0.96 7.77 CGGA_274 Primary GBM WHO IV Female 610 0 55 Wildtype Non-codel 3.85 0.66 CGGA_276 Primary O WHO II Male 529 0 44 Mutant Non-codel 1.02 1.23 CGGA_309 NA NA NA Male 139 1 44 Wildtype NA 0.95 2.82 CGGA_318 Secondary sGBM WHO IV Female 222 1 40 Wildtype Non-codel 9.3 15.89 CGGA_323 Primary O WHO II Female 4338 0 48 Wildtype Non-codel 1.43 1.8 CGGA_330 Primary AA WHO III Male 1121 1 45 Wildtype Non-codel 3.04 2.87 CGGA_413 Primary GBM WHO IV Male 183 0 54 Wildtype Non-codel 2.11 1.83 CGGA_426 Primary AA WHO III Male 1560 1 50 Wildtype Non-codel 5.08 4.33 CGGA_448 Primary AA WHO III Male 354 1 64 Wildtype Non-codel 2.11 10.12 CGGA_483 Primary GBM WHO IV Female 277 1 59 Wildtype Non-codel 2.55 5.64 CGGA_488 Primary AA WHO III Male 435 1 23 Wildtype Non-codel 0.37 0.38 CGGA_493 Primary A WHO II Female 2382 1 32 Mutant Non-codel 0.47 0.82 CGGA_494 Primary GBM WHO IV Female 4435 0 58 Wildtype Non-codel 0.47 1.28 CGGA_495 NA NA NA Male 295 1 53 Wildtype NA 6.18 0.27 CGGA_499 Primary GBM WHO IV Male 122 1 51 Wildtype Non-codel 2.31 1.09 CGGA_525 Primary GBM WHO IV Male 138 1 61 Wildtype Non-codel 7.62 0.95 CGGA_541 Primary A WHO II Female 4376 0 36 Wildtype Non-codel 1.47 2.6 CGGA_564 Primary AA WHO III Male 679 1 47 Wildtype Non-codel 3.26 1.9 CGGA_565 Primary AA WHO III Male 3605 0 51 Wildtype Non-codel 0.52 0.74 CGGA_578 Primary AA WHO III Female 362 1 61 Wildtype Non-codel 7.43 0.82 CGGA_599 Primary AO WHO III Female 418 1 66 Wildtype Non-codel 1.84 0.58 CGGA_604 Primary GBM WHO IV Male 381 1 46 Wildtype Non-codel 9.28 12.85 CGGA_616 Primary AA WHO III Male 952 1 43 Wildtype Non-codel 5.14 1.8 CGGA_624 Recurrent rGBM WHO IV Female 122 1 50 Wildtype Non-codel 8.98 3.74 CGGA_630 Recurrent rO WHO III Male 4300 0 43 Mutant Codel 0.51 0.75 CGGA_633 Primary O WHO II Female 1812 1 56 Wildtype Non-codel 3.09 1.36 CGGA_638 Primary O WHO II Male 2386 0 42 Mutant Codel 1.4 0.89 CGGA_643 Primary AA WHO III Male 331 1 56 Wildtype Non-codel 1.42 1.65 CGGA_658 Primary GBM WHO IV Male 372 1 55 Wildtype Non-codel 2.76 0.94 CGGA_659 Primary O WHO II Female 730 0 50 Wildtype Non-codel 1.24 1.01 CGGA_661 Primary AA WHO III Male NA 1 42 Wildtype Non-codel 5.78 6.51 CGGA_669 Recurrent rGBM WHO IV Female 607 1 56 Wildtype Codel 0.37 0.76 CGGA_676 Primary GBM WHO IV Male 376 1 60 Wildtype Non-codel 3.08 6.01 CGGA_678 Recurrent rAA WHO III Male 386 1 56 Wildtype Non-codel 5.14 7.18 CGGA_679 Primary GBM WHO IV Female 263 1 63 Wildtype Non-codel 2.3 2.76 CGGA_680 Primary GBM WHO IV Male 2373 1 44 Wildtype Non-codel 0.54 0.91 CGGA_681 NA NA NA Male 110 1 42 Wildtype NA 1.28 3.02 CGGA_700 Primary GBM WHO IV Female 170 0 24 Mutant Non-codel 0.8 1.68 CGGA_727 Primary AA WHO III Male 1023 1 45 Wildtype Non-codel 1.22 2.02 CGGA_731 Primary GBM WHO IV Male 503 1 50 Wildtype Non-codel 5.25 3.38 CGGA_732 Primary AA WHO III Female NA NA 35 Wildtype Non-codel 0.53 0.59 CGGA_766 Primary O WHO II Male 4103 0 32 Mutant Codel 0.48 0.47 CGGA_773 Secondary sGBM WHO IV Female 443 1 51 Mutant Non-codel 0.72 1.11 CGGA_782 Primary GBM WHO IV Male 289 1 60 Wildtype Non-codel 6.78 1.62 CGGA_789 Primary GBM WHO IV Male 345 1 50 Wildtype Non-codel 9.14 2.13 CGGA_791 Primary AA WHO III Male 252 1 55 Wildtype Non-codel 1.05 1.05 CGGA_796 Primary A WHO II Male 559 0 60 Wildtype Non-codel 3.86 1.17 CGGA_802 Primary GBM WHO IV Male 681 1 42 Wildtype Non-codel 7.75 7.25 CGGA_804 Primary GBM WHO IV Female 614 0 53 Wildtype Non-codel 1.55 0.56 CGGA_807 Primary A WHO II Male 4040 0 42 Wildtype Non-codel 0.35 0.32 CGGA_808 Primary GBM WHO IV Male 1167 0 38 Wildtype Non-codel 1.5 2.05 CGGA_837 Primary GBM WHO IV Male 432 1 57 Wildtype Non-codel 3.39 3.78 CGGA_842 Primary GBM WHO IV Female 204 1 63 Wildtype Non-codel 7.43 3.2 CGGA_848 Primary GBM WHO IV Female 239 0 54 Wildtype Non-codel 3.25 0.84 CGGA_850 Primary GBM WHO IV Female 564 0 52 Wildtype Non-codel 2.06 1.79 CGGA_859 Primary GBM WHO IV Male 387 1 56 Wildtype Non-codel 8.78 7.04 CGGA_871 Primary O WHO II Male 3964 0 37 Mutant Codel 1.39 1.45 CGGA_876 Primary GBM WHO IV Female 159 1 60 Wildtype Non-codel 7.15 4.41 CGGA_878 Primary GBM WHO IV Male 863 1 42 Wildtype Non-codel 3.14 8.18 CGGA_902 Primary GBM WHO IV Male 193 1 54 Wildtype Non-codel 2.06 1.27 CGGA_D02 Recurrent rGBM WHO IV Male 484 1 44 Wildtype Non-codel 8.8 0.65 CGGA_D03 Primary GBM WHO IV Male 423 1 44 Wildtype Non-codel 2.35 9.02 CGGA_D06 Recurrent rAA WHO III Female NA 1 49 Wildtype Codel 1.6 0.77 CGGA_D09 Primary GBM WHO IV Male 233 1 57 Wildtype Non-codel 8.12 1.77 CGGA_D11 Primary AA WHO III Female 827 1 53 Wildtype Non-codel 2.53 2.5 CGGA_D16 Primary AA WHO III Female 261 1 59 Wildtype Non-codel 3.62 1.32 CGGA_D18 Primary AA WHO III Male NA NA 20 Wildtype Non-codel 0.64 2.08 CGGA_D26 Recurrent rGBM WHO IV Male 263 1 55 Wildtype Non-codel 7.3 6.47 CGGA_D32 Recurrent rGBM WHO IV Male 358 1 61 Wildtype Non-codel 2.64 2.01 CGGA_D35 Primary GBM WHO IV Female 661 1 68 Wildtype Non-codel 7.44 3.47 CGGA_D36 Recurrent rGBM WHO IV Male 34 1 58 Wildtype Non-codel 5.36 1.33 CGGA_D37 Primary GBM WHO IV Male 965 1 55 Wildtype Non-codel 13.48 2.4 CGGA_D44 Primary AA WHO III Female 313 1 18 Wildtype Non-codel 9.07 1.66 CGGA_D51 Recurrent rGBM WHO IV Female 135 1 60 Wildtype Non-codel 7.08 5.97 CGGA_D57 Primary GBM WHO IV Male 766 1 40 Wildtype Non-codel 5.15 1.36 CGGA_D58 Recurrent rAA WHO III Male 181 1 24 Wildtype Codel 0.54 0.63 CGGA_342 Primary GBM WHO IV Female 500 1 49 Wildtype NA 1.91 3.02 CGGA_719 Secondary sGBM WHO IV Male 101 1 51 Mutant NA 0.3 0.7 CGGA_J030 Primary O WHO II Male 3389 0 38 Mutant Codel 0.25 0.8 CGGA_J130 Recurrent rA WHO II Male 3116 0 40 Wildtype Non-codel 1.09 1.44 CGGA_1005 Primary A WHO II Female 3815 0 41 Mutant Non-codel 0.4 0.67 CGGA_1013 Primary A WHO II Female 1725 1 38 Mutant Non-codel 0.94 0.71 CGGA_1020 Primary A WHO II Female 1120 1 38 Mutant Non-codel 1.12 0.94 CGGA_1027 Primary AO WHO III Male 2688 0 37 Mutant Codel 2.18 2.37 CGGA_1031 Primary A WHO II Female 2457 1 31 Mutant Non-codel 0.6 0.64 CGGA_1046 Primary A WHO II Male 3559 0 21 NA NA 0.43 0.36 CGGA_1050 Primary O WHO II Male NA 0 39 Mutant Codel 0.38 0.54 CGGA_1060 Recurrent rGBM WHO IV Male 227 1 42 Mutant Non-codel 0.99 0.58 CGGA_1061 Recurrent rAA WHO III Female 532 1 43 Mutant Non-codel 1.16 0.25 CGGA_1068 Secondary sGBM WHO IV Male 68 1 29 Mutant Non-codel 2.12 1.01 CGGA_1094 Recurrent rAA WHO III Female 252 1 40 Mutant Non-codel 1.06 1.74 CGGA_1105 Secondary sGBM WHO IV Male 609 1 29 Mutant Non-codel 2.88 6.42 CGGA_1113 Primary AO WHO III Male 1265 1 34 Mutant Codel 0.52 0.45 CGGA_1129 Secondary sGBM WHO IV Male 168 1 34 Mutant Non-codel 3.12 0.4 CGGA_1136 Secondary sGBM WHO IV Female 236 1 38 Mutant Non-codel 1.44 1.12 CGGA_1146 Primary AA WHO III Male 2498 0 35 Mutant Non-codel 1.48 1.46 CGGA_1160 Primary AA WHO III Female 426 1 43 Mutant Non-codel 1.4 1.49 CGGA_1170 Secondary sGBM WHO IV Male 346 1 25 Mutant Non-codel 0.33 0.75 CGGA_1175 Secondary sGBM WHO IV Female 441 1 36 Mutant Non-codel 0.8 0.56 CGGA_1189 Primary AO WHO III Female 3082 0 34 Mutant Codel 0.9 0.59 CGGA_1190 Primary AA WHO III Female 3082 0 45 Mutant Non-codel 0.95 1.85 CGGA_1215 Recurrent rAA WHO III Male 29 1 37 Mutant Non-codel 2.24 0.73 CGGA_1219 Primary GBM WHO IV Female 2120 1 57 Mutant Non-codel 0.92 0.29 CGGA_1227 Recurrent rGBM WHO IV Female 1197 1 46 Wildtype Non-codel 5.98 2.36 CGGA_1231 Recurrent rAA WHO III Female 2279 1 31 Wildtype Non-codel 10.6 4.5 CGGA_1287 Primary GBM WHO IV Male 533 1 29 Mutant Non-codel 0.7 0.88 CGGA_1307 Primary AA WHO III Female 965 0 25 Mutant Non-codel 3.71 1.95 CGGA_1314 Primary GBM WHO IV Female 172 1 27 Mutant Non-codel 1.9 0.79 CGGA_1322 Primary AA WHO III Male 253 1 10 Mutant Non-codel 1.04 0.34 CGGA_1324 Secondary sGBM WHO IV Male 848 1 42 Mutant Codel 0.65 0.88 CGGA_1329 Recurrent rAA WHO III Female 326 1 43 Mutant Non-codel 0.2 2.3 CGGA_1330 Primary A WHO II Male 2846 0 47 Mutant Non-codel 1.35 0.81 CGGA_1374 Recurrent rAA WHO III Male 141 1 22 Mutant Non-codel 0.56 4.17 CGGA_1375 Secondary sGBM WHO IV Female 92 1 50 Mutant Non-codel 0.35 0.18 CGGA_1381 Recurrent rGBM WHO IV Female 46 1 36 Mutant Non-codel 1.2 0.36 CGGA_1384 Primary GBM WHO IV Female 191 1 39 Mutant Non-codel 0.28 1.41 CGGA_1388 Recurrent rAA WHO III Male 485 1 37 Mutant Non-codel 0.94 4.82 CGGA_1394 Recurrent rGBM WHO IV Male 139 1 37 Mutant Non-codel 0.33 0.43 CGGA_1406 Primary A WHO II Male 2154 1 34 Mutant Non-codel 3.21 0.77 CGGA_1409 Primary GBM WHO IV Female 2727 0 24 Mutant Non-codel 0.67 0.98 CGGA_1412 Secondary sGBM WHO IV Female 296 1 48 Mutant Codel 0.78 2.39 CGGA_171 Primary O WHO II Female NA NA 37 Mutant Codel 1.36 0.62 CGGA_236 Primary O WHO II Male 706 0 47 Mutant Codel 0.36 0.16 CGGA_241 Primary A WHO II Male 4809 0 34 Mutant Non-codel 1.84 1.29 CGGA_245 Recurrent rAA WHO III Female 318 1 39 Mutant Non-codel 1.55 1.91 CGGA_251 Primary A WHO II Male 1299 0 45 Mutant Non-codel 1.67 1.44 CGGA_252 Primary A WHO II Female 165 0 24 Mutant Non-codel 0.48 1.13 CGGA_254 Primary O WHO II Male 4793 0 38 Mutant Codel 1.15 0.5 CGGA_256 Primary A WHO II Male 158 0 39 Mutant Non-codel 0.91 1.3 CGGA_261 Primary A WHO II Male 4130 0 27 Mutant Non-codel 0.39 0.36 CGGA_267 Primary A WHO II Male 1374 1 36 Mutant Non-codel 0.68 0.38 CGGA_273 Primary A WHO II Female 2635 1 35 Mutant Non-codel 1.67 2.79 CGGA_283 Primary O WHO II Female 3470 1 47 Mutant Codel 1.07 1.08 CGGA_300 Primary A WHO II Female 2199 1 35 Mutant Non-codel 0.73 0.79 CGGA_314 Recurrent rO WHO III Male 2568 1 39 Mutant Codel 0.6 1.42 CGGA_333 Primary A WHO II Male 1783 0 40 Mutant Non-codel 1.76 1.56 CGGA_337 Primary AA WHO III Female 1008 1 50 Mutant Non-codel 2.07 2.53 CGGA_374 Secondary sGBM WHO IV Male 493 1 37 Mutant Non-codel 0.34 0.53 CGGA_400 Recurrent rAA WHO III Female 1321 1 38 Mutant Non-codel 1.4 0.96 CGGA_431 Recurrent rO WHO III Male 4515 0 41 Mutant Codel 0.77 0.57 CGGA_446 Primary O WHO II Female 4508 0 35 Mutant Codel 0.67 0.25 CGGA_458 Recurrent rA WHO II Male 419 1 51 Mutant Non-codel 0.43 1 CGGA_479 Primary O WHO II Female 4445 0 36 Mutant Codel 0.77 0.64 CGGA_485 Primary O WHO II Male 2437 0 31 Mutant Codel 0.59 0.77 CGGA_490 Primary AO WHO III Female 3804 0 37 Mutant Codel 0.72 0.74 CGGA_491 Primary GBM WHO IV Female 1074 1 36 Mutant Non-codel 1.31 0.84 CGGA_501 Primary O WHO II Male 4427 0 40 Mutant Codel 0.61 1.82 CGGA_502 Primary A WHO II Male 4414 0 39 Mutant Non-codel 0.46 0.92 CGGA_510 Primary AO WHO III Male 4403 0 42 Mutant Codel 0.4 0.91 CGGA_538 Primary O WHO II Female NA NA 43 Mutant Codel 1.22 0.74 CGGA_543 Primary O WHO II Male 4371 0 43 Mutant Codel 0.58 0.66 CGGA_545 Recurrent rGBM WHO IV Female 555 1 38 Mutant Non-codel 1.92 4.63 CGGA_551 Primary O WHO II Male 4363 0 44 Mutant Codel 0.36 0.39 CGGA_560 Primary AA WHO III Male 4354 0 43 Mutant Non-codel 1.39 1.38 CGGA_580 Primary A WHO II Male 1394 1 43 Mutant Non-codel 0.26 1.49 CGGA_591 Primary AA WHO III Female 1654 1 50 Mutant Non-codel 1.21 2.07 CGGA_598 Primary AO WHO III Female 3677 1 61 Mutant Codel 0.23 0.59 CGGA_601 Primary A WHO II Male 1133 1 36 Mutant Non-codel 1.78 0.91 CGGA_603 Recurrent rAA WHO III Male 168 0 32 Mutant Non-codel 1.63 1.48 CGGA_605 Recurrent rA WHO III Male 4300 0 43 Mutant Non-codel 2.9 3.16 CGGA_607 Primary A WHO II Male 1389 0 25 Mutant Non-codel 0.5 1.01 CGGA_632 Primary A WHO II Female 576 1 29 Mutant Non-codel 0.86 0.45 CGGA_635 Primary O WHO II Male 4263 0 45 Mutant Codel 0.49 0.9 CGGA_641 Primary AO WHO III Female 3411 1 51 Mutant Codel 0.57 0.35 CGGA_642 Primary A WHO II Male 4249 0 29 Mutant Non-codel 0.43 0.96 CGGA_655 Primary O WHO II Male 4231 0 35 Mutant Codel 1.07 0.7 CGGA_662 Primary O WHO II Female 284 1 59 Mutant Codel 0.41 0.82 CGGA_666 Primary O WHO II Female 2499 1 45 Mutant Codel 0.58 1.2 CGGA_671 Primary O WHO II Female 4215 0 36 Mutant Codel 0.79 0.64 CGGA_675 Primary O WHO II Female 4210 0 23 Mutant Codel 0.61 0.42 CGGA_685 Primary A WHO II Female 3239 1 20 Mutant Non-codel 0.91 0.65 CGGA_689 Primary O WHO II Female 4194 0 36 Mutant Codel 1.08 0.7 CGGA_694 Recurrent rA WHO II Male 1194 1 34 Mutant Non-codel 1.78 1.05 CGGA_698 Primary A WHO II Female 1851 1 61 Mutant Non-codel 0.89 1.02 CGGA_704 Primary A WHO II Male 2572 1 36 Mutant Non-codel 0.99 1.26 CGGA_710 Primary GBM WHO IV Male 660 1 41 Mutant Non-codel 1.42 1.57 CGGA_715 Primary O WHO II Male 3429 0 43 Mutant Codel 0.54 0.69 CGGA_725 Primary O WHO II Male 4147 0 58 Mutant Codel 0.94 0.93 CGGA_747 Primary GBM WHO IV Male 970 1 29 Mutant Non-codel 0.6 0.25 CGGA_752 Primary O WHO II Male 3680 0 39 Mutant Codel 0.54 1.69 CGGA_757 Primary A WHO II Male 1047 1 45 Mutant Non-codel 0.41 0.75 CGGA_760 Primary O WHO II Female 4110 0 34 Mutant Codel 0.4 0.66 CGGA_761 Primary GBM WHO IV Male 1840 1 45 Mutant Non-codel 1.06 0.8 CGGA_762 Primary O WHO II Female 4105 0 40 Mutant Codel 0.59 0.62 CGGA_785 Primary O WHO II Male 3517 1 43 Mutant Codel 0.28 0.76 CGGA_812 Primary O WHO II Male 4035 0 27 Mutant Codel 0.88 1.21 CGGA_815 Primary A WHO II Female 2219 1 53 Mutant Non-codel 1.67 2.23 CGGA_818 Primary A WHO II Male 4027 0 46 Mutant Non-codel 1.08 4.53 CGGA_822 Secondary sGBM WHO IV Male 2237 1 46 Mutant Non-codel 0.32 0.21 CGGA_834 Primary A WHO II Male 4013 0 24 Wildtype Non-codel 3.57 1.56 CGGA_835 Primary O WHO II Male 517 0 31 Mutant Codel 0.59 0.69 CGGA_838 Primary O WHO II Female 4011 0 36 Mutant Codel 0.34 0.42 CGGA_843 Primary O WHO II Male 4005 0 29 Mutant Codel 0.84 0.37 CGGA_856 Primary O WHO II Male 1297 0 53 Mutant Codel 0.24 0.22 CGGA_858 Primary O WHO II Male 3984 0 42 Mutant Codel 0.22 0.72 CGGA_864 Primary O WHO II Male 3977 0 34 Mutant Codel 0.45 0.69 CGGA_884 Primary A WHO II Female 1131 1 48 Mutant Non-codel 0.79 0.41 CGGA_892 Primary O WHO II Male 448 0 34 Mutant Codel 1.01 0.62 CGGA_893 Primary A WHO II Female 3160 1 36 Mutant Non-codel 0.63 0.49 CGGA_898 Primary A WHO II Male 1663 1 38 Mutant Non-codel 0.57 0.58 CGGA_899 Recurrent rGBM WHO IV Male 231 1 48 Mutant Non-codel 0.7 0.36 CGGA_904 Primary A WHO II Male 774 1 33 Mutant Non-codel 0.31 0.55 CGGA_905 Primary A WHO II Male 3174 1 46 Mutant Non-codel 0.74 1.05 CGGA_908 Primary A WHO II Male 2436 1 35 Mutant Non-codel 0.45 0.85 CGGA_909 Primary A WHO II Female 3920 0 39 Mutant Non-codel 2.43 1.95 CGGA_D04 Primary A WHO II Male 3697 0 37 Mutant Non-codel 0.18 0.36 CGGA_D07 Primary O WHO II Male 3691 0 36 Mutant Codel 1.35 0.95 CGGA_D14 Recurrent rAA WHO III Male NA NA 27 Mutant Non-codel 0.98 0.61 CGGA_D15 Primary O WHO II Female 3669 0 38 Mutant Codel 0.47 0.26 CGGA_D20 Primary A WHO II Female 2367 1 40 Mutant Non-codel 0.3 0.82 CGGA_D21 Primary AA WHO III Female 1208 1 37 Mutant Non-codel 1.1 1.68 CGGA_D24 Primary AA WHO III Female 837 1 37 Mutant Non-codel 1.13 1.08 CGGA_D27 Recurrent rO WHO III Male 3650 0 33 Mutant Codel 1.34 1.22 CGGA_D29 Primary O WHO II Male 3643 0 36 Mutant Codel 0.38 0.26 CGGA_D33 Recurrent rAA WHO III Male 116 1 38 Mutant Non-codel 1.36 1.11 CGGA_D34 Secondary sGBM WHO IV Male 147 1 45 Mutant Non-codel 0.82 1.06 CGGA_D38 Recurrent rGBM WHO IV Female 689 1 41 Mutant Codel 0.43 0.81 CGGA_D39 Recurrent rA WHO II Female NA NA 27 Mutant Non-codel 0.99 1.93 CGGA_D40 Recurrent rA WHO II Male 3557 0 44 Mutant Non-codel 1.7 0.73 CGGA_D45 Recurrent rAA WHO III Male 856 0 32 Mutant Non-codel 1.43 3.06 CGGA_D46 Recurrent rAA WHO III Female 300 1 36 Mutant Non-codel 1.15 2.37 CGGA_D47 Primary O WHO II Male 1048 1 36 Mutant Codel 2.06 1.34 CGGA_D48 Recurrent rAA WHO III Female 221 1 23 Mutant Non-codel 0.57 0.63 CGGA_D52 Primary AO WHO III Male 3529 0 46 Mutant Codel 0.34 0.7 CGGA_D56 Recurrent rAA WHO III Male 64 1 45 Mutant Non-codel 2.64 2.06 CGGA_D59 Secondary sGBM WHO IV Female NA NA 30 Mutant Non-codel 0.52 0.75 CGGA_277 Primary AO WHO III Male 4739 0 40 Mutant NA 1.06 0.8 CGGA_518 Secondary sGBM WHO IV Male 212 1 27 Mutant NA 0.53 0.17 CGGA_J023 Primary AO WHO III Male 1028 1 36 Mutant Non-codel 0.23 0.31 CGGA_J024 Recurrent rA WHO II Female 3410 0 29 Mutant Non-codel 0.62 2.13 CGGA_J042 Recurrent rA WHO II Male 1409 1 38 Mutant Non-codel 3.53 0.99 CGGA_J100 Recurrent rGBM WHO IV Male NA NA 55 Mutant Non-codel 1.43 0.82 CGGA_1004 Primary A WHO II Female 899 1 63 Wildtype Non-codel 17.04 1.96 CGGA_1008 Primary GBM WHO IV Female 315 1 54 Wildtype Non-codel 1.95 2.5 CGGA_1053 Primary GBM WHO IV Female 370 1 63 Wildtype Non-codel 2.81 2.38 CGGA_1059 Recurrent rA WHO II Female 21 1 54 Mutant Non-codel 0.86 0.69 CGGA_1070 Primary GBM WHO IV Male 333 1 37 Wildtype Non-codel 3.38 0.97 CGGA_1071 Primary A WHO II Male 3252 1 42 Wildtype Non-codel 4.32 2.25 CGGA_1073 Primary GBM WHO IV Female 270 1 42 Wildtype Non-codel 2.63 4.82 CGGA_1074 Primary GBM WHO IV Male 86 1 50 Wildtype Non-codel 8.23 2.38 CGGA_1095 NA NA NA Male 2778 1 29 Mutant Non-codel 0.42 0.71 CGGA_1099 Secondary sGBM WHO IV Male 122 1 8 Wildtype Non-codel 2.25 1.52 CGGA_1114 Primary GBM WHO IV Male 460 1 53 Wildtype Non-codel 7.19 2.58 CGGA_1116 Recurrent rGBM WHO IV Female 248 1 43 Mutant Non-codel 0.32 1.76 CGGA_1118 Recurrent rAA WHO III Male 398 1 31 Mutant Non-codel 0.79 0.46 CGGA_1119 Recurrent rGBM WHO IV Male 422 1 52 Mutant Codel 3.61 0.27 CGGA_1197 Secondary sGBM WHO IV Male 942 1 43 Mutant Codel 0.66 1.1 CGGA_1246 Primary AO WHO III Male 2972 0 53 Mutant Codel 0.49 0.87 CGGA_1275 Primary GBM WHO IV Male 183 1 70 Wildtype Non-codel 2.55 0.99 CGGA_1450 Secondary sGBM WHO IV Male 957 1 37 Mutant Codel 0.42 0.43 CGGA_1460 Secondary sGBM WHO IV Male 209 1 51 Wildtype Non-codel 1.58 0.82 CGGA_1475 Secondary sGBM WHO IV Male 182 1 38 Mutant Non-codel 1.38 1.34 CGGA_243 Primary O WHO II Female 2977 0 30 Mutant Codel 0.53 0.49 CGGA_247 Primary AA WHO III Male 609 1 60 Mutant Non-codel 1.28 0.48 CGGA_738 Primary A WHO II Male 4132 0 43 Mutant Non-codel 3.44 5.89 CGGA_759 Primary GBM WHO IV Male 1263 1 30 Mutant Non-codel 1.13 0.7 CGGA_D30 Primary GBM WHO IV Male 215 1 70 Wildtype Non-codel 3.28 0.82
data.file<-"data.txt" geneA<-"ADAMTSL4" geneB<-"CD274" ## load R package library(ggplot2) library(ggpubr) library(gridExtra) ## import data dat<-read.table(data.file, sep='\t', head=T) rownames(dat)<-dat$CGGA.ID #head(dat) mat<-dat[!is.na(dat$PRS.type)&(dat$PRS.type=="Primary"|dat$PRS.type=="Recurrent")& !is.na(dat$Histology)& !is.na(dat$Grade)& !is.na(dat$Gender)& !is.na(dat$Age)& !is.na(dat$IDH.mutation.status)& !is.na(dat$X1p19q.codel.status),] mat$Gene.A.Expression<-log1p(mat$Gene.A.Expression) mat$Gene.B.Expression<-log1p(mat$Gene.B.Expression) ### 1.primary tmp.data<-mat[mat$PRS.type=="Primary",] cortest<-cor.test(tmp.data$Gene.A.Expression,tmp.data$Gene.B.Expression) R.value<-round(cortest$estimate[[1]],3) P.value<-format(cortest$p.value,scientific=T,digits=3) ptext<-paste0("R = ",R.value,", P = ",P.value) dat_text <- data.frame(Gene.A.Expression=min(tmp.data$Gene.A.Expression)+1, Gene.B.Expression=max(tmp.data$Gene.B.Expression)+0.5, label = ptext, IDH.mutation.status=NA, Histology=NA, Grade = NA, fill_color=NA, CGGA.ID=NA, X1p19q.codel.status=NA, Age=NA, Gender=NA, PRS.type=NA ) mat.all.Primary.plot<-ggplot(tmp.data,aes(x=Gene.A.Expression, y=Gene.B.Expression, Sample=CGGA.ID, Histology=Histology, Grade=Grade, X1p19q.codel.status=X1p19q.codel.status, IDH.mutation.status=IDH.mutation.status, Age=Age, Gender=Gender, PRS.type=PRS.type))+ geom_point()+ geom_text(data=dat_text,aes(label = label))+ geom_smooth(formula = y~x,aes(group=1),method='lm')+ xlab(paste0('Gene expression of ',geneA))+ ylab(paste0('Gene expression of ',geneB))+ labs(title = 'All WHO grade (primary glioma)')+ theme(text = element_text(size=10),plot.margin = unit(c(1,1,1,1), 'cm')) ### 2. Recurrent tmp.data<-mat[mat$PRS.type=="Recurrent",] cortest<-cor.test(tmp.data$Gene.A.Expression,tmp.data$Gene.B.Expression) R.value<-round(cortest$estimate[[1]],3) P.value<-format(cortest$p.value,scientific=T,digits=3) ptext<-paste0("R = ",R.value,", P = ",P.value) dat_text <- data.frame(Gene.A.Expression=min(tmp.data$Gene.A.Expression)+1, Gene.B.Expression=max(tmp.data$Gene.B.Expression)+0.5, label = ptext, IDH.mutation.status=NA, Histology=NA, Grade = NA, fill_color=NA, CGGA.ID=NA, X1p19q.codel.status=NA, Age=NA, Gender=NA, PRS.type=NA ) mat.all.Recurrent.plot<-ggplot(tmp.data,aes(x=Gene.A.Expression, y=Gene.B.Expression, Sample=CGGA.ID, Histology=Histology, Grade=Grade, X1p19q.codel.status=X1p19q.codel.status, IDH.mutation.status=IDH.mutation.status, Age=Age, Gender=Gender, PRS.type=PRS.type))+ geom_point()+ geom_text(data=dat_text,aes(label = label))+ geom_smooth(formula = y~x,aes(group=1),method='lm')+ xlab(paste0('Gene expression of ',geneA))+ ylab(paste0('Gene expression of ',geneB))+ labs(title = 'All WHO grade (recurrent glioma)')+ theme(text = element_text(size=10),plot.margin = unit(c(1,1,1,1), 'cm')) ### 3.Primary.II tmp.data<-mat[mat$PRS.type=="Primary"&mat$Grade=="WHO II",] cortest<-cor.test(tmp.data$Gene.A.Expression,tmp.data$Gene.B.Expression) R.value<-round(cortest$estimate[[1]],3) P.value<-format(cortest$p.value,scientific=T,digits=3) ptext<-paste0("R = ",R.value,", P = ",P.value) dat_text <- data.frame(Gene.A.Expression=min(tmp.data$Gene.A.Expression)+1, Gene.B.Expression=max(tmp.data$Gene.B.Expression)+0.5, label = ptext, IDH.mutation.status=NA, Histology=NA, Grade = NA, fill_color=NA, CGGA.ID=NA, X1p19q.codel.status=NA, Age=NA, Gender=NA, PRS.type=NA ) mat.Primary.II.plot<-ggplot(tmp.data,aes(x=Gene.A.Expression, y=Gene.B.Expression, Sample=CGGA.ID, Histology=Histology, Grade=Grade, X1p19q.codel.status=X1p19q.codel.status, IDH.mutation.status=IDH.mutation.status, Age=Age, Gender=Gender, PRS.type=PRS.type))+ geom_point()+ geom_text(data=dat_text,aes(label = label))+ geom_smooth(formula = y~x,aes(group=1),method='lm')+ xlab(paste0('Gene expression of ',geneA))+ ylab(paste0('Gene expression of ',geneB))+ labs(title = 'WHO grade II (primary glioma)') theme(text = element_text(size=10),plot.margin = unit(c(1,1,1,1), 'cm')) ### 4.Recurrent.II tmp.data<-mat[mat$PRS.type=="Recurrent"&mat$Grade=="WHO II",] cortest<-cor.test(tmp.data$Gene.A.Expression,tmp.data$Gene.B.Expression) R.value<-round(cortest$estimate[[1]],3) P.value<-format(cortest$p.value,scientific=T,digits=3) ptext<-paste0("R = ",R.value,", P = ",P.value) dat_text <- data.frame(Gene.A.Expression=min(tmp.data$Gene.A.Expression)+1, Gene.B.Expression=max(tmp.data$Gene.B.Expression)+0.5, label = ptext, IDH.mutation.status=NA, Histology=NA, Grade = NA, fill_color=NA, CGGA.ID=NA, X1p19q.codel.status=NA, Age=NA, Gender=NA, PRS.type=NA ) mat.Recurrent.II.plot<-ggplot(tmp.data,aes(x=Gene.A.Expression, y=Gene.B.Expression, Sample=CGGA.ID, Histology=Histology, Grade=Grade, X1p19q.codel.status=X1p19q.codel.status, IDH.mutation.status=IDH.mutation.status, Age=Age, Gender=Gender, PRS.type=PRS.type))+ geom_point()+ geom_text(data=dat_text,aes(label = label))+ geom_smooth(formula = y~x,aes(group=1),method='lm')+ xlab(paste0('Gene expression of ',geneA))+ ylab(paste0('Gene expression of ',geneB))+ labs(title = 'WHO grade II (recurrent glioma)')+ theme(text = element_text(size=10),plot.margin = unit(c(1,1,1,1), 'cm')) ### 5.Primary.III tmp.data<-mat[mat$PRS.type=="Primary"&mat$Grade=="WHO III",] cortest<-cor.test(tmp.data$Gene.A.Expression,tmp.data$Gene.B.Expression) R.value<-round(cortest$estimate[[1]],3) P.value<-format(cortest$p.value,scientific=T,digits=3) ptext<-paste0("R = ",R.value,", P = ",P.value) dat_text <- data.frame(Gene.A.Expression=min(tmp.data$Gene.A.Expression)+1, Gene.B.Expression=max(tmp.data$Gene.B.Expression)+0.5, label = ptext, IDH.mutation.status=NA, Histology=NA, Grade = NA, fill_color=NA, CGGA.ID=NA, X1p19q.codel.status=NA, Age=NA, Gender=NA, PRS.type=NA ) mat.Primary.III.plot<-ggplot(tmp.data,aes(x=Gene.A.Expression, y=Gene.B.Expression, Sample=CGGA.ID, Histology=Histology, Grade=Grade, X1p19q.codel.status=X1p19q.codel.status, IDH.mutation.status=IDH.mutation.status, Age=Age, Gender=Gender, PRS.type=PRS.type))+ geom_point()+ geom_text(data=dat_text,aes(label = label))+ geom_smooth(formula = y~x,aes(group=1),method='lm')+ xlab(paste0('Gene expression of ',geneA))+ ylab(paste0('Gene expression of ',geneB))+ labs(title = 'WHO grade III (primary glioma)')+ theme(text = element_text(size=10),plot.margin = unit(c(1,1,1,1), 'cm')) ### 6.Recurrent.III tmp.data<-mat[mat$PRS.type=="Recurrent"&mat$Grade=="WHO III",] cortest<-cor.test(tmp.data$Gene.A.Expression,tmp.data$Gene.B.Expression) R.value<-round(cortest$estimate[[1]],3) P.value<-format(cortest$p.value,scientific=T,digits=3) ptext<-paste0("R = ",R.value,", P = ",P.value) dat_text <- data.frame(Gene.A.Expression=min(tmp.data$Gene.A.Expression)+1, Gene.B.Expression=max(tmp.data$Gene.B.Expression)+0.5, label = ptext, IDH.mutation.status=NA, Histology=NA, Grade = NA, fill_color=NA, CGGA.ID=NA, X1p19q.codel.status=NA, Age=NA, Gender=NA, PRS.type=NA ) mat.Recurrent.III.plot<-ggplot(tmp.data,aes(x=Gene.A.Expression, y=Gene.B.Expression, Sample=CGGA.ID, Histology=Histology, Grade=Grade, X1p19q.codel.status=X1p19q.codel.status, IDH.mutation.status=IDH.mutation.status, Age=Age, Gender=Gender, PRS.type=PRS.type))+ geom_point()+ geom_text(data=dat_text,aes(label = label))+ geom_smooth(formula = y~x,aes(group=1),method='lm')+ xlab(paste0('Gene expression of ',geneA))+ ylab(paste0('Gene expression of ',geneB))+ labs(title = 'WHO grade III (recurrent glioma)')+ theme(text = element_text(size=10),plot.margin = unit(c(1,1,1,1), 'cm')) ### 7.Primary.IV tmp.data<-mat[mat$PRS.type=="Primary"&mat$Grade=="WHO IV",] cortest<-cor.test(tmp.data$Gene.A.Expression,tmp.data$Gene.B.Expression) R.value<-round(cortest$estimate[[1]],3) P.value<-format(cortest$p.value,scientific=T,digits=3) ptext<-paste0("R = ",R.value,", P = ",P.value) dat_text <- data.frame(Gene.A.Expression=min(tmp.data$Gene.A.Expression)+1, Gene.B.Expression=max(tmp.data$Gene.B.Expression)+0.5, label = ptext, IDH.mutation.status=NA, Histology=NA, Grade = NA, fill_color=NA, CGGA.ID=NA, X1p19q.codel.status=NA, Age=NA, Gender=NA, PRS.type=NA ) mat.Primary.IV.plot<-ggplot(tmp.data,aes(x=Gene.A.Expression, y=Gene.B.Expression, Sample=CGGA.ID, Histology=Histology, Grade=Grade, X1p19q.codel.status=X1p19q.codel.status, IDH.mutation.status=IDH.mutation.status, Age=Age, Gender=Gender, PRS.type=PRS.type))+ geom_point()+ geom_text(data=dat_text,aes(label = label))+ geom_smooth(formula = y~x,aes(group=1),method='lm')+ xlab(paste0('Gene expression of ',geneA))+ ylab(paste0('Gene expression of ',geneB))+ labs(title = 'WHO grade IV (primary glioma)')+ theme(text = element_text(size=10),plot.margin = unit(c(1,1,1,1), 'cm')) ### 8.Recurrent.IV tmp.data<-mat[mat$PRS.type=="Recurrent"&mat$Grade=="WHO IV",] cortest<-cor.test(tmp.data$Gene.A.Expression,tmp.data$Gene.B.Expression) R.value<-round(cortest$estimate[[1]],3) P.value<-format(cortest$p.value,scientific=T,digits=3) ptext<-paste0("R = ",R.value,", P = ",P.value) dat_text <- data.frame(Gene.A.Expression=min(tmp.data$Gene.A.Expression)+1, Gene.B.Expression=max(tmp.data$Gene.B.Expression)+0.5, label = ptext, IDH.mutation.status=NA, Histology=NA, Grade = NA, fill_color=NA, CGGA.ID=NA, X1p19q.codel.status=NA, Age=NA, Gender=NA, PRS.type=NA ) mat.Recurrent.IV.plot<-ggplot(tmp.data,aes(x=Gene.A.Expression, y=Gene.B.Expression, Sample=CGGA.ID, Histology=Histology, Grade=Grade, X1p19q.codel.status=X1p19q.codel.status, IDH.mutation.status=IDH.mutation.status, Age=Age, Gender=Gender, PRS.type=PRS.type))+ geom_point()+ geom_text(data=dat_text,aes(label = label))+ geom_smooth(formula = y~x,aes(group=1),method='lm')+ xlab(paste0('Gene expression of ',geneA))+ ylab(paste0('Gene expression of ',geneB))+ labs(title = 'WHO grade IV (recurrent glioma)')+ theme(text = element_text(size=10),plot.margin = unit(c(1,1,1,1), 'cm')) ## output pdf grid.arrange(mat.all.Primary.plot, mat.all.Recurrent.plot, mat.Primary.II.plot, mat.Recurrent.II.plot, mat.Primary.III.plot, mat.Recurrent.III.plot, mat.Primary.IV.plot, mat.Recurrent.IV.plot, ncol = 2,nrow=4)
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