(primary solid tumor cohort)
This pipeline computes the correlation between significant arm-level copy number variations (cnvs) and subtypes.
Testing the association between copy number variation 80 arm-level results and 12 molecular subtypes across 569 patients, 60 significant findings detected with Q value < 0.25.
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1q gain cnv correlated to 'CN_CNMF'.
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2p gain cnv correlated to 'MRNA_CNMF', 'MRNA_CHIERARCHICAL', 'MIR_CHIERARCHICAL', 'CN_CNMF', 'METHLYATION_CNMF', and 'MRNASEQ_CNMF'.
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2q gain cnv correlated to 'MRNA_CNMF', 'MRNA_CHIERARCHICAL', 'CN_CNMF', and 'METHLYATION_CNMF'.
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3q gain cnv correlated to 'CN_CNMF'.
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5p gain cnv correlated to 'CN_CNMF'.
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6p gain cnv correlated to 'CN_CNMF' and 'METHLYATION_CNMF'.
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6q gain cnv correlated to 'CN_CNMF' and 'METHLYATION_CNMF'.
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7p gain cnv correlated to 'CN_CNMF' and 'METHLYATION_CNMF'.
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7q gain cnv correlated to 'CN_CNMF'.
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10p gain cnv correlated to 'MRNA_CHIERARCHICAL' and 'CN_CNMF'.
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11q gain cnv correlated to 'CN_CNMF'.
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12p gain cnv correlated to 'MRNA_CNMF', 'MRNA_CHIERARCHICAL', 'MIR_CHIERARCHICAL', 'CN_CNMF', 'METHLYATION_CNMF', and 'MRNASEQ_CNMF'.
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12q gain cnv correlated to 'MRNA_CHIERARCHICAL', 'CN_CNMF', and 'METHLYATION_CNMF'.
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13q gain cnv correlated to 'METHLYATION_CNMF'.
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18p gain cnv correlated to 'METHLYATION_CNMF'.
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19p gain cnv correlated to 'CN_CNMF'.
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19q gain cnv correlated to 'CN_CNMF'.
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20p gain cnv correlated to 'MRNA_CHIERARCHICAL', 'MIR_CHIERARCHICAL', 'CN_CNMF', and 'METHLYATION_CNMF'.
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20q gain cnv correlated to 'MRNA_CNMF', 'MRNA_CHIERARCHICAL', 'MIR_CHIERARCHICAL', 'CN_CNMF', and 'METHLYATION_CNMF'.
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21q gain cnv correlated to 'CN_CNMF' and 'METHLYATION_CNMF'.
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4q loss cnv correlated to 'MIRSEQ_CHIERARCHICAL'.
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5q loss cnv correlated to 'MRNA_CNMF', 'MRNA_CHIERARCHICAL', 'CN_CNMF', and 'METHLYATION_CNMF'.
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9q loss cnv correlated to 'CN_CNMF'.
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13q loss cnv correlated to 'METHLYATION_CNMF'.
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14q loss cnv correlated to 'CN_CNMF'.
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15q loss cnv correlated to 'CN_CNMF' and 'METHLYATION_CNMF'.
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22q loss cnv correlated to 'MRNA_CNMF', 'MRNA_CHIERARCHICAL', and 'CN_CNMF'.
Table 1. Get Full Table Overview of the association between significant copy number variation of 80 arm-level results and 12 molecular subtypes. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 60 significant findings detected.
Molecular subtypes |
MRNA CNMF |
MRNA CHIERARCHICAL |
MIR CNMF |
MIR CHIERARCHICAL |
CN CNMF |
METHLYATION CNMF |
RPPA CNMF |
RPPA CHIERARCHICAL |
MRNASEQ CNMF |
MRNASEQ CHIERARCHICAL |
MIRSEQ CNMF |
MIRSEQ CHIERARCHICAL |
||
nCNV (%) | nWild-Type | Fisher's exact test | Fisher's exact test | Fisher's exact test | Chi-square test | Fisher's exact test | Fisher's exact test | Fisher's exact test | Fisher's exact test | Fisher's exact test | Fisher's exact test | Fisher's exact test | Fisher's exact test | |
2p gain | 129 (23%) | 440 |
5.21e-09 (4.91e-06) |
1.03e-10 (9.71e-08) |
0.615 (1.00) |
1.31e-05 (0.0121) |
3.02e-11 (2.87e-08) |
3.13e-11 (2.97e-08) |
0.0363 (1.00) |
0.439 (1.00) |
8.7e-05 (0.0791) |
0.00457 (1.00) |
0.426 (1.00) |
0.209 (1.00) |
12p gain | 208 (37%) | 361 |
7.56e-05 (0.0689) |
1.27e-05 (0.0117) |
0.306 (1.00) |
4.46e-05 (0.0408) |
4.27e-13 (4.07e-10) |
3.95e-09 (3.73e-06) |
0.362 (1.00) |
0.825 (1.00) |
1.46e-05 (0.0135) |
0.00033 (0.297) |
0.183 (1.00) |
0.194 (1.00) |
20q gain | 273 (48%) | 296 |
1.94e-05 (0.0178) |
3.35e-13 (3.2e-10) |
0.497 (1.00) |
1.6e-06 (0.00149) |
3.3e-20 (3.17e-17) |
9.65e-17 (9.23e-14) |
0.456 (1.00) |
0.175 (1.00) |
0.0033 (1.00) |
0.395 (1.00) |
0.351 (1.00) |
0.877 (1.00) |
2q gain | 103 (18%) | 466 |
1.53e-06 (0.00142) |
6.48e-07 (0.000606) |
0.648 (1.00) |
0.00255 (1.00) |
1.43e-08 (1.34e-05) |
2e-06 (0.00186) |
0.0338 (1.00) |
0.329 (1.00) |
0.00183 (1.00) |
0.00447 (1.00) |
0.535 (1.00) |
0.481 (1.00) |
20p gain | 234 (41%) | 335 |
0.00174 (1.00) |
5.26e-07 (0.000493) |
0.207 (1.00) |
4.08e-06 (0.00379) |
3.87e-15 (3.7e-12) |
4.1e-12 (3.9e-09) |
0.322 (1.00) |
0.572 (1.00) |
0.00375 (1.00) |
0.144 (1.00) |
0.569 (1.00) |
1 (1.00) |
5q loss | 172 (30%) | 397 |
0.000144 (0.131) |
2.22e-05 (0.0203) |
0.655 (1.00) |
0.00138 (1.00) |
0.000173 (0.157) |
1.7e-07 (0.00016) |
0.00843 (1.00) |
0.0604 (1.00) |
0.000664 (0.592) |
0.284 (1.00) |
0.533 (1.00) |
0.595 (1.00) |
12q gain | 122 (21%) | 447 |
0.000834 (0.741) |
5.65e-06 (0.00524) |
0.533 (1.00) |
0.00204 (1.00) |
1.22e-14 (1.17e-11) |
9.49e-06 (0.00877) |
0.00933 (1.00) |
0.663 (1.00) |
0.000731 (0.65) |
0.00235 (1.00) |
0.102 (1.00) |
0.119 (1.00) |
22q loss | 387 (68%) | 182 |
0.00012 (0.109) |
1.8e-05 (0.0166) |
0.056 (1.00) |
0.0363 (1.00) |
0.000176 (0.16) |
0.0095 (1.00) |
0.0395 (1.00) |
0.101 (1.00) |
0.0806 (1.00) |
0.191 (1.00) |
0.00279 (1.00) |
0.39 (1.00) |
6p gain | 121 (21%) | 448 |
0.492 (1.00) |
0.00412 (1.00) |
0.873 (1.00) |
0.0212 (1.00) |
1.19e-06 (0.00111) |
0.000238 (0.214) |
0.546 (1.00) |
0.744 (1.00) |
0.154 (1.00) |
0.619 (1.00) |
0.291 (1.00) |
0.147 (1.00) |
6q gain | 62 (11%) | 507 |
0.751 (1.00) |
0.00709 (1.00) |
0.896 (1.00) |
0.0396 (1.00) |
1.01e-05 (0.00936) |
6.58e-05 (0.0601) |
0.14 (1.00) |
0.857 (1.00) |
0.00314 (1.00) |
0.354 (1.00) |
0.93 (1.00) |
0.416 (1.00) |
7p gain | 125 (22%) | 444 |
0.214 (1.00) |
0.151 (1.00) |
0.0456 (1.00) |
0.00843 (1.00) |
9.19e-08 (8.64e-05) |
1.05e-06 (0.000984) |
0.407 (1.00) |
0.158 (1.00) |
0.0836 (1.00) |
0.109 (1.00) |
0.944 (1.00) |
0.371 (1.00) |
10p gain | 132 (23%) | 437 |
0.0106 (1.00) |
5.38e-05 (0.0492) |
0.783 (1.00) |
0.00763 (1.00) |
2.95e-09 (2.79e-06) |
0.00123 (1.00) |
0.294 (1.00) |
0.454 (1.00) |
0.0126 (1.00) |
0.865 (1.00) |
0.507 (1.00) |
0.963 (1.00) |
21q gain | 70 (12%) | 499 |
0.666 (1.00) |
0.0322 (1.00) |
0.986 (1.00) |
0.906 (1.00) |
7.07e-06 (0.00655) |
0.000186 (0.168) |
0.29 (1.00) |
0.259 (1.00) |
0.371 (1.00) |
0.171 (1.00) |
0.231 (1.00) |
0.683 (1.00) |
15q loss | 220 (39%) | 349 |
0.00346 (1.00) |
0.00872 (1.00) |
0.000914 (0.81) |
0.0035 (1.00) |
7.17e-11 (6.8e-08) |
0.000185 (0.167) |
0.884 (1.00) |
0.885 (1.00) |
0.0245 (1.00) |
0.449 (1.00) |
0.00638 (1.00) |
0.375 (1.00) |
1q gain | 161 (28%) | 408 |
0.521 (1.00) |
0.518 (1.00) |
0.728 (1.00) |
0.563 (1.00) |
1.07e-05 (0.00984) |
0.209 (1.00) |
0.365 (1.00) |
0.798 (1.00) |
0.64 (1.00) |
0.619 (1.00) |
0.206 (1.00) |
0.457 (1.00) |
3q gain | 208 (37%) | 361 |
0.948 (1.00) |
0.00133 (1.00) |
0.735 (1.00) |
0.284 (1.00) |
1.02e-09 (9.62e-07) |
0.00325 (1.00) |
0.447 (1.00) |
0.248 (1.00) |
0.352 (1.00) |
0.678 (1.00) |
0.387 (1.00) |
0.449 (1.00) |
5p gain | 147 (26%) | 422 |
0.641 (1.00) |
0.276 (1.00) |
0.688 (1.00) |
0.485 (1.00) |
2.09e-07 (0.000196) |
0.348 (1.00) |
0.599 (1.00) |
0.196 (1.00) |
0.544 (1.00) |
0.905 (1.00) |
0.0767 (1.00) |
0.3 (1.00) |
7q gain | 153 (27%) | 416 |
0.0877 (1.00) |
0.303 (1.00) |
0.353 (1.00) |
0.357 (1.00) |
1.05e-05 (0.00968) |
0.0005 (0.447) |
0.266 (1.00) |
0.0944 (1.00) |
0.175 (1.00) |
0.173 (1.00) |
0.24 (1.00) |
0.492 (1.00) |
11q gain | 62 (11%) | 507 |
0.383 (1.00) |
0.776 (1.00) |
0.94 (1.00) |
0.0125 (1.00) |
7.92e-05 (0.0722) |
0.000679 (0.605) |
0.369 (1.00) |
0.451 (1.00) |
0.577 (1.00) |
0.221 (1.00) |
0.281 (1.00) |
0.436 (1.00) |
13q gain | 41 (7%) | 528 |
0.0168 (1.00) |
0.221 (1.00) |
0.889 (1.00) |
0.00174 (1.00) |
0.00588 (1.00) |
0.000254 (0.229) |
0.829 (1.00) |
0.336 (1.00) |
0.451 (1.00) |
0.949 (1.00) |
0.289 (1.00) |
0.618 (1.00) |
18p gain | 74 (13%) | 495 |
0.00725 (1.00) |
0.00119 (1.00) |
0.852 (1.00) |
0.157 (1.00) |
0.00147 (1.00) |
8.22e-05 (0.0748) |
0.00283 (1.00) |
0.0731 (1.00) |
0.527 (1.00) |
0.611 (1.00) |
0.271 (1.00) |
0.589 (1.00) |
19p gain | 99 (17%) | 470 |
0.0238 (1.00) |
0.0208 (1.00) |
0.664 (1.00) |
0.192 (1.00) |
1.95e-08 (1.84e-05) |
0.000683 (0.607) |
0.0151 (1.00) |
0.235 (1.00) |
0.741 (1.00) |
0.822 (1.00) |
0.677 (1.00) |
0.311 (1.00) |
19q gain | 92 (16%) | 477 |
0.0226 (1.00) |
0.047 (1.00) |
0.624 (1.00) |
0.16 (1.00) |
6.85e-07 (0.00064) |
0.000364 (0.327) |
0.0242 (1.00) |
0.266 (1.00) |
0.558 (1.00) |
0.525 (1.00) |
0.328 (1.00) |
0.217 (1.00) |
4q loss | 302 (53%) | 267 |
0.0489 (1.00) |
0.021 (1.00) |
0.269 (1.00) |
0.0147 (1.00) |
0.0101 (1.00) |
0.763 (1.00) |
0.286 (1.00) |
0.0925 (1.00) |
0.47 (1.00) |
0.0357 (1.00) |
0.0471 (1.00) |
0.000253 (0.227) |
9q loss | 240 (42%) | 329 |
0.00133 (1.00) |
0.000371 (0.332) |
0.142 (1.00) |
0.00651 (1.00) |
1.51e-11 (1.44e-08) |
0.00232 (1.00) |
0.653 (1.00) |
0.881 (1.00) |
0.00276 (1.00) |
0.212 (1.00) |
0.109 (1.00) |
0.0309 (1.00) |
13q loss | 262 (46%) | 307 |
0.12 (1.00) |
0.74 (1.00) |
0.907 (1.00) |
0.0687 (1.00) |
0.000857 (0.76) |
1.26e-06 (0.00118) |
0.00299 (1.00) |
0.00436 (1.00) |
0.297 (1.00) |
0.985 (1.00) |
0.418 (1.00) |
0.896 (1.00) |
14q loss | 164 (29%) | 405 |
0.0842 (1.00) |
0.16 (1.00) |
0.875 (1.00) |
0.917 (1.00) |
0.000118 (0.107) |
0.0256 (1.00) |
0.966 (1.00) |
0.479 (1.00) |
0.0454 (1.00) |
0.557 (1.00) |
0.43 (1.00) |
0.356 (1.00) |
1p gain | 104 (18%) | 465 |
0.0537 (1.00) |
0.337 (1.00) |
0.0931 (1.00) |
0.436 (1.00) |
0.336 (1.00) |
0.898 (1.00) |
0.04 (1.00) |
0.333 (1.00) |
0.694 (1.00) |
0.344 (1.00) |
0.125 (1.00) |
0.714 (1.00) |
3p gain | 109 (19%) | 460 |
0.407 (1.00) |
0.118 (1.00) |
0.102 (1.00) |
0.619 (1.00) |
0.00102 (0.902) |
0.893 (1.00) |
0.201 (1.00) |
0.464 (1.00) |
0.633 (1.00) |
0.889 (1.00) |
0.797 (1.00) |
0.618 (1.00) |
4p gain | 31 (5%) | 538 |
0.888 (1.00) |
0.499 (1.00) |
0.0047 (1.00) |
0.688 (1.00) |
0.0876 (1.00) |
0.051 (1.00) |
0.0149 (1.00) |
0.458 (1.00) |
0.953 (1.00) |
0.573 (1.00) |
0.272 (1.00) |
0.286 (1.00) |
4q gain | 16 (3%) | 553 |
0.948 (1.00) |
0.805 (1.00) |
0.853 (1.00) |
0.938 (1.00) |
0.332 (1.00) |
0.0214 (1.00) |
0.0208 (1.00) |
0.257 (1.00) |
0.913 (1.00) |
0.585 (1.00) |
0.00385 (1.00) |
0.0479 (1.00) |
5q gain | 34 (6%) | 535 |
0.0365 (1.00) |
0.118 (1.00) |
0.499 (1.00) |
0.356 (1.00) |
0.597 (1.00) |
0.416 (1.00) |
0.157 (1.00) |
0.58 (1.00) |
0.316 (1.00) |
0.658 (1.00) |
0.039 (1.00) |
0.422 (1.00) |
8p gain | 86 (15%) | 483 |
0.355 (1.00) |
0.125 (1.00) |
0.977 (1.00) |
0.0131 (1.00) |
0.264 (1.00) |
0.956 (1.00) |
0.83 (1.00) |
0.232 (1.00) |
0.547 (1.00) |
0.232 (1.00) |
0.579 (1.00) |
0.345 (1.00) |
8q gain | 204 (36%) | 365 |
0.184 (1.00) |
0.417 (1.00) |
0.128 (1.00) |
0.0883 (1.00) |
0.0087 (1.00) |
0.975 (1.00) |
0.786 (1.00) |
0.125 (1.00) |
0.00385 (1.00) |
0.38 (1.00) |
0.812 (1.00) |
0.795 (1.00) |
9p gain | 61 (11%) | 508 |
0.0325 (1.00) |
0.505 (1.00) |
0.28 (1.00) |
0.319 (1.00) |
0.00446 (1.00) |
0.0217 (1.00) |
0.173 (1.00) |
0.596 (1.00) |
0.896 (1.00) |
0.587 (1.00) |
0.157 (1.00) |
0.748 (1.00) |
9q gain | 27 (5%) | 542 |
0.397 (1.00) |
0.275 (1.00) |
0.104 (1.00) |
0.619 (1.00) |
0.0726 (1.00) |
0.224 (1.00) |
0.611 (1.00) |
0.208 (1.00) |
0.813 (1.00) |
0.0484 (1.00) |
0.829 (1.00) |
0.738 (1.00) |
10q gain | 68 (12%) | 501 |
0.0085 (1.00) |
0.00254 (1.00) |
0.959 (1.00) |
0.0166 (1.00) |
0.0135 (1.00) |
0.0297 (1.00) |
0.283 (1.00) |
0.511 (1.00) |
0.08 (1.00) |
0.312 (1.00) |
0.38 (1.00) |
0.57 (1.00) |
11p gain | 40 (7%) | 529 |
0.244 (1.00) |
0.404 (1.00) |
0.223 (1.00) |
0.34 (1.00) |
0.043 (1.00) |
0.016 (1.00) |
0.0225 (1.00) |
0.00441 (1.00) |
0.0427 (1.00) |
0.284 (1.00) |
0.121 (1.00) |
0.183 (1.00) |
14q gain | 34 (6%) | 535 |
0.011 (1.00) |
0.0521 (1.00) |
0.348 (1.00) |
0.0546 (1.00) |
0.975 (1.00) |
0.188 (1.00) |
0.0644 (1.00) |
0.00978 (1.00) |
0.273 (1.00) |
0.0362 (1.00) |
0.46 (1.00) |
0.642 (1.00) |
15q gain | 25 (4%) | 544 |
0.382 (1.00) |
0.64 (1.00) |
0.337 (1.00) |
0.459 (1.00) |
0.27 (1.00) |
0.662 (1.00) |
0.166 (1.00) |
0.824 (1.00) |
1 (1.00) |
1 (1.00) |
0.638 (1.00) |
0.54 (1.00) |
16p gain | 31 (5%) | 538 |
0.0368 (1.00) |
0.0224 (1.00) |
0.919 (1.00) |
0.355 (1.00) |
0.149 (1.00) |
0.148 (1.00) |
0.675 (1.00) |
0.101 (1.00) |
1 (1.00) |
1 (1.00) |
0.926 (1.00) |
0.513 (1.00) |
16q gain | 16 (3%) | 553 |
0.0183 (1.00) |
0.000961 (0.85) |
0.219 (1.00) |
0.491 (1.00) |
0.597 (1.00) |
0.042 (1.00) |
0.512 (1.00) |
0.124 (1.00) |
0.119 (1.00) |
0.269 (1.00) |
||
17p gain | 11 (2%) | 558 |
0.433 (1.00) |
0.129 (1.00) |
0.509 (1.00) |
0.27 (1.00) |
0.064 (1.00) |
0.434 (1.00) |
0.414 (1.00) |
0.795 (1.00) |
0.352 (1.00) |
0.632 (1.00) |
0.58 (1.00) |
0.365 (1.00) |
17q gain | 23 (4%) | 546 |
0.729 (1.00) |
0.285 (1.00) |
0.271 (1.00) |
0.245 (1.00) |
0.0705 (1.00) |
0.339 (1.00) |
0.509 (1.00) |
0.922 (1.00) |
0.591 (1.00) |
0.683 (1.00) |
0.695 (1.00) |
0.466 (1.00) |
18q gain | 41 (7%) | 528 |
0.25 (1.00) |
0.615 (1.00) |
0.531 (1.00) |
0.565 (1.00) |
0.042 (1.00) |
0.0213 (1.00) |
0.206 (1.00) |
0.454 (1.00) |
0.614 (1.00) |
0.44 (1.00) |
0.136 (1.00) |
0.792 (1.00) |
22q gain | 9 (2%) | 560 |
0.379 (1.00) |
0.833 (1.00) |
0.692 (1.00) |
0.641 (1.00) |
0.205 (1.00) |
0.84 (1.00) |
0.604 (1.00) |
0.701 (1.00) |
0.833 (1.00) |
1 (1.00) |
0.0433 (1.00) |
0.474 (1.00) |
Xq gain | 34 (6%) | 535 |
0.194 (1.00) |
0.0261 (1.00) |
0.949 (1.00) |
0.603 (1.00) |
0.0139 (1.00) |
0.105 (1.00) |
0.0904 (1.00) |
0.328 (1.00) |
0.393 (1.00) |
0.5 (1.00) |
0.203 (1.00) |
0.767 (1.00) |
1p loss | 35 (6%) | 534 |
0.00443 (1.00) |
0.0112 (1.00) |
0.284 (1.00) |
0.49 (1.00) |
0.779 (1.00) |
0.218 (1.00) |
0.503 (1.00) |
0.514 (1.00) |
0.736 (1.00) |
0.361 (1.00) |
1 (1.00) |
1 (1.00) |
1q loss | 22 (4%) | 547 |
0.018 (1.00) |
0.00428 (1.00) |
0.00412 (1.00) |
0.347 (1.00) |
0.337 (1.00) |
0.497 (1.00) |
0.648 (1.00) |
0.189 (1.00) |
0.796 (1.00) |
0.0964 (1.00) |
0.329 (1.00) |
0.843 (1.00) |
2p loss | 26 (5%) | 543 |
0.761 (1.00) |
0.871 (1.00) |
0.905 (1.00) |
0.181 (1.00) |
0.572 (1.00) |
0.383 (1.00) |
0.332 (1.00) |
0.585 (1.00) |
0.178 (1.00) |
0.29 (1.00) |
0.833 (1.00) |
0.229 (1.00) |
2q loss | 30 (5%) | 539 |
0.789 (1.00) |
0.53 (1.00) |
0.816 (1.00) |
0.0858 (1.00) |
0.53 (1.00) |
0.139 (1.00) |
0.287 (1.00) |
0.668 (1.00) |
0.546 (1.00) |
0.243 (1.00) |
0.676 (1.00) |
0.109 (1.00) |
3p loss | 61 (11%) | 508 |
0.0592 (1.00) |
0.0121 (1.00) |
0.925 (1.00) |
0.0476 (1.00) |
0.00469 (1.00) |
0.118 (1.00) |
0.87 (1.00) |
0.25 (1.00) |
0.0181 (1.00) |
0.458 (1.00) |
0.194 (1.00) |
0.534 (1.00) |
3q loss | 23 (4%) | 546 |
0.239 (1.00) |
0.0866 (1.00) |
0.964 (1.00) |
0.182 (1.00) |
0.198 (1.00) |
0.198 (1.00) |
0.592 (1.00) |
0.606 (1.00) |
0.0803 (1.00) |
0.276 (1.00) |
0.489 (1.00) |
0.684 (1.00) |
4p loss | 262 (46%) | 307 |
0.0989 (1.00) |
0.0801 (1.00) |
0.516 (1.00) |
0.0236 (1.00) |
0.0312 (1.00) |
0.889 (1.00) |
0.155 (1.00) |
0.177 (1.00) |
0.152 (1.00) |
0.292 (1.00) |
0.0344 (1.00) |
0.0104 (1.00) |
5p loss | 85 (15%) | 484 |
0.378 (1.00) |
0.088 (1.00) |
0.188 (1.00) |
0.162 (1.00) |
0.0129 (1.00) |
0.0047 (1.00) |
0.204 (1.00) |
0.156 (1.00) |
0.000407 (0.364) |
0.562 (1.00) |
0.919 (1.00) |
0.699 (1.00) |
6p loss | 126 (22%) | 443 |
0.923 (1.00) |
0.0524 (1.00) |
0.716 (1.00) |
0.794 (1.00) |
0.19 (1.00) |
0.0511 (1.00) |
0.212 (1.00) |
0.407 (1.00) |
0.48 (1.00) |
0.797 (1.00) |
0.18 (1.00) |
1 (1.00) |
6q loss | 198 (35%) | 371 |
0.96 (1.00) |
0.0238 (1.00) |
0.829 (1.00) |
0.844 (1.00) |
0.079 (1.00) |
0.0202 (1.00) |
0.0986 (1.00) |
0.653 (1.00) |
0.124 (1.00) |
0.194 (1.00) |
0.211 (1.00) |
0.812 (1.00) |
7p loss | 91 (16%) | 478 |
0.614 (1.00) |
0.246 (1.00) |
0.184 (1.00) |
0.304 (1.00) |
0.0746 (1.00) |
0.146 (1.00) |
0.382 (1.00) |
0.767 (1.00) |
0.944 (1.00) |
0.0347 (1.00) |
0.0259 (1.00) |
0.718 (1.00) |
7q loss | 48 (8%) | 521 |
0.337 (1.00) |
0.855 (1.00) |
0.431 (1.00) |
0.652 (1.00) |
0.267 (1.00) |
0.0267 (1.00) |
0.349 (1.00) |
0.756 (1.00) |
0.579 (1.00) |
0.22 (1.00) |
0.0537 (1.00) |
0.837 (1.00) |
8p loss | 235 (41%) | 334 |
0.756 (1.00) |
0.571 (1.00) |
0.454 (1.00) |
0.86 (1.00) |
0.00151 (1.00) |
0.0744 (1.00) |
0.199 (1.00) |
0.351 (1.00) |
0.34 (1.00) |
0.914 (1.00) |
0.471 (1.00) |
0.191 (1.00) |
8q loss | 63 (11%) | 506 |
0.0697 (1.00) |
0.035 (1.00) |
0.201 (1.00) |
0.369 (1.00) |
0.00207 (1.00) |
0.0675 (1.00) |
0.0766 (1.00) |
0.485 (1.00) |
0.0393 (1.00) |
0.044 (1.00) |
0.789 (1.00) |
0.38 (1.00) |
9p loss | 212 (37%) | 357 |
0.000585 (0.523) |
0.00456 (1.00) |
0.737 (1.00) |
0.0603 (1.00) |
0.0297 (1.00) |
0.00103 (0.913) |
0.674 (1.00) |
0.976 (1.00) |
0.567 (1.00) |
0.134 (1.00) |
0.0402 (1.00) |
0.331 (1.00) |
10p loss | 67 (12%) | 502 |
0.436 (1.00) |
0.623 (1.00) |
0.328 (1.00) |
0.806 (1.00) |
0.895 (1.00) |
0.695 (1.00) |
0.193 (1.00) |
0.205 (1.00) |
0.964 (1.00) |
0.659 (1.00) |
0.109 (1.00) |
0.613 (1.00) |
10q loss | 90 (16%) | 479 |
0.642 (1.00) |
0.38 (1.00) |
0.0994 (1.00) |
0.799 (1.00) |
0.118 (1.00) |
0.591 (1.00) |
0.259 (1.00) |
0.227 (1.00) |
0.763 (1.00) |
0.26 (1.00) |
0.298 (1.00) |
0.218 (1.00) |
11p loss | 146 (26%) | 423 |
0.00609 (1.00) |
0.00524 (1.00) |
0.0964 (1.00) |
0.262 (1.00) |
0.0816 (1.00) |
0.00802 (1.00) |
0.558 (1.00) |
0.133 (1.00) |
0.0213 (1.00) |
0.687 (1.00) |
0.787 (1.00) |
0.809 (1.00) |
11q loss | 108 (19%) | 461 |
0.135 (1.00) |
0.392 (1.00) |
0.0135 (1.00) |
0.258 (1.00) |
0.187 (1.00) |
0.103 (1.00) |
0.822 (1.00) |
0.0791 (1.00) |
0.0733 (1.00) |
0.797 (1.00) |
0.295 (1.00) |
0.137 (1.00) |
12p loss | 51 (9%) | 518 |
0.294 (1.00) |
0.0891 (1.00) |
1 (1.00) |
0.12 (1.00) |
0.00812 (1.00) |
0.242 (1.00) |
0.971 (1.00) |
0.0597 (1.00) |
0.296 (1.00) |
0.44 (1.00) |
0.591 (1.00) |
0.277 (1.00) |
12q loss | 76 (13%) | 493 |
0.192 (1.00) |
0.00199 (1.00) |
0.389 (1.00) |
0.277 (1.00) |
0.00274 (1.00) |
0.0942 (1.00) |
0.839 (1.00) |
0.266 (1.00) |
0.149 (1.00) |
0.0162 (1.00) |
0.421 (1.00) |
0.335 (1.00) |
16p loss | 271 (48%) | 298 |
0.912 (1.00) |
0.969 (1.00) |
0.196 (1.00) |
0.677 (1.00) |
0.0275 (1.00) |
0.105 (1.00) |
0.964 (1.00) |
0.931 (1.00) |
0.353 (1.00) |
0.611 (1.00) |
0.271 (1.00) |
0.561 (1.00) |
16q loss | 360 (63%) | 209 |
0.918 (1.00) |
0.887 (1.00) |
0.041 (1.00) |
0.362 (1.00) |
0.0263 (1.00) |
0.0886 (1.00) |
0.733 (1.00) |
0.973 (1.00) |
0.492 (1.00) |
0.812 (1.00) |
0.269 (1.00) |
0.0826 (1.00) |
17p loss | 429 (75%) | 140 |
0.188 (1.00) |
0.0406 (1.00) |
0.891 (1.00) |
0.545 (1.00) |
0.243 (1.00) |
0.0463 (1.00) |
0.525 (1.00) |
0.178 (1.00) |
0.295 (1.00) |
0.119 (1.00) |
0.339 (1.00) |
0.418 (1.00) |
17q loss | 332 (58%) | 237 |
0.011 (1.00) |
0.00449 (1.00) |
0.0246 (1.00) |
0.663 (1.00) |
0.597 (1.00) |
0.186 (1.00) |
0.188 (1.00) |
0.127 (1.00) |
0.128 (1.00) |
0.109 (1.00) |
0.00734 (1.00) |
0.288 (1.00) |
18p loss | 187 (33%) | 382 |
0.767 (1.00) |
0.932 (1.00) |
0.33 (1.00) |
0.413 (1.00) |
0.216 (1.00) |
0.0128 (1.00) |
0.941 (1.00) |
0.24 (1.00) |
0.018 (1.00) |
0.206 (1.00) |
0.881 (1.00) |
0.917 (1.00) |
18q loss | 236 (41%) | 333 |
0.202 (1.00) |
0.753 (1.00) |
0.7 (1.00) |
0.608 (1.00) |
0.845 (1.00) |
0.453 (1.00) |
0.963 (1.00) |
0.14 (1.00) |
0.00285 (1.00) |
0.103 (1.00) |
0.669 (1.00) |
0.467 (1.00) |
19p loss | 145 (25%) | 424 |
0.532 (1.00) |
0.809 (1.00) |
0.152 (1.00) |
0.225 (1.00) |
0.179 (1.00) |
0.0996 (1.00) |
0.027 (1.00) |
0.108 (1.00) |
0.466 (1.00) |
0.71 (1.00) |
0.907 (1.00) |
0.778 (1.00) |
19q loss | 145 (25%) | 424 |
0.126 (1.00) |
0.448 (1.00) |
0.315 (1.00) |
0.296 (1.00) |
0.278 (1.00) |
0.723 (1.00) |
0.0706 (1.00) |
0.363 (1.00) |
1 (1.00) |
0.871 (1.00) |
0.201 (1.00) |
0.313 (1.00) |
20p loss | 38 (7%) | 531 |
0.304 (1.00) |
0.529 (1.00) |
0.625 (1.00) |
0.361 (1.00) |
0.172 (1.00) |
0.0962 (1.00) |
0.657 (1.00) |
0.447 (1.00) |
0.0208 (1.00) |
0.0759 (1.00) |
0.0116 (1.00) |
0.891 (1.00) |
20q loss | 22 (4%) | 547 |
0.717 (1.00) |
0.188 (1.00) |
0.276 (1.00) |
0.737 (1.00) |
0.518 (1.00) |
0.737 (1.00) |
0.352 (1.00) |
0.269 (1.00) |
0.245 (1.00) |
0.625 (1.00) |
0.248 (1.00) |
1 (1.00) |
21q loss | 151 (27%) | 418 |
0.343 (1.00) |
0.248 (1.00) |
0.31 (1.00) |
0.0634 (1.00) |
0.793 (1.00) |
0.0515 (1.00) |
0.286 (1.00) |
0.387 (1.00) |
0.46 (1.00) |
0.563 (1.00) |
0.464 (1.00) |
0.966 (1.00) |
Xq loss | 101 (18%) | 468 |
0.0795 (1.00) |
0.161 (1.00) |
0.0363 (1.00) |
0.15 (1.00) |
0.0851 (1.00) |
0.316 (1.00) |
1 (1.00) |
0.466 (1.00) |
0.295 (1.00) |
0.822 (1.00) |
0.975 (1.00) |
0.384 (1.00) |
P value = 1.07e-05 (Fisher's exact test), Q value = 0.0098
Table S1. Gene #2: '1q gain mutation analysis' versus Clinical Feature #5: 'CN_CNMF'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 |
---|---|---|---|
ALL | 166 | 204 | 199 |
1Q GAIN MUTATED | 38 | 42 | 81 |
1Q GAIN WILD-TYPE | 128 | 162 | 118 |
Figure S1. Get High-res Image Gene #2: '1q gain mutation analysis' versus Clinical Feature #5: 'CN_CNMF'
![](D2V5.png)
P value = 5.21e-09 (Fisher's exact test), Q value = 4.9e-06
Table S2. Gene #3: '2p gain mutation analysis' versus Clinical Feature #1: 'MRNA_CNMF'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 |
---|---|---|---|
ALL | 215 | 213 | 129 |
2P GAIN MUTATED | 76 | 23 | 26 |
2P GAIN WILD-TYPE | 139 | 190 | 103 |
Figure S2. Get High-res Image Gene #3: '2p gain mutation analysis' versus Clinical Feature #1: 'MRNA_CNMF'
![](D3V1.png)
P value = 1.03e-10 (Fisher's exact test), Q value = 9.7e-08
Table S3. Gene #3: '2p gain mutation analysis' versus Clinical Feature #2: 'MRNA_CHIERARCHICAL'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 |
---|---|---|---|
ALL | 233 | 199 | 125 |
2P GAIN MUTATED | 34 | 77 | 14 |
2P GAIN WILD-TYPE | 199 | 122 | 111 |
Figure S3. Get High-res Image Gene #3: '2p gain mutation analysis' versus Clinical Feature #2: 'MRNA_CHIERARCHICAL'
![](D3V2.png)
P value = 1.31e-05 (Chi-square test), Q value = 0.012
Table S4. Gene #3: '2p gain mutation analysis' versus Clinical Feature #4: 'MIR_CHIERARCHICAL'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4 | CLUS_5 | CLUS_6 |
---|---|---|---|---|---|---|
ALL | 65 | 115 | 125 | 99 | 57 | 94 |
2P GAIN MUTATED | 11 | 17 | 24 | 20 | 12 | 41 |
2P GAIN WILD-TYPE | 54 | 98 | 101 | 79 | 45 | 53 |
Figure S4. Get High-res Image Gene #3: '2p gain mutation analysis' versus Clinical Feature #4: 'MIR_CHIERARCHICAL'
![](D3V4.png)
P value = 3.02e-11 (Fisher's exact test), Q value = 2.9e-08
Table S5. Gene #3: '2p gain mutation analysis' versus Clinical Feature #5: 'CN_CNMF'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 |
---|---|---|---|
ALL | 166 | 204 | 199 |
2P GAIN MUTATED | 22 | 28 | 79 |
2P GAIN WILD-TYPE | 144 | 176 | 120 |
Figure S5. Get High-res Image Gene #3: '2p gain mutation analysis' versus Clinical Feature #5: 'CN_CNMF'
![](D3V5.png)
P value = 3.13e-11 (Fisher's exact test), Q value = 3e-08
Table S6. Gene #3: '2p gain mutation analysis' versus Clinical Feature #6: 'METHLYATION_CNMF'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 |
---|---|---|---|
ALL | 171 | 176 | 221 |
2P GAIN MUTATED | 70 | 34 | 25 |
2P GAIN WILD-TYPE | 101 | 142 | 196 |
Figure S6. Get High-res Image Gene #3: '2p gain mutation analysis' versus Clinical Feature #6: 'METHLYATION_CNMF'
![](D3V6.png)
P value = 8.7e-05 (Fisher's exact test), Q value = 0.079
Table S7. Gene #3: '2p gain mutation analysis' versus Clinical Feature #9: 'MRNASEQ_CNMF'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 |
---|---|---|---|
ALL | 100 | 67 | 91 |
2P GAIN MUTATED | 18 | 8 | 36 |
2P GAIN WILD-TYPE | 82 | 59 | 55 |
Figure S7. Get High-res Image Gene #3: '2p gain mutation analysis' versus Clinical Feature #9: 'MRNASEQ_CNMF'
![](D3V9.png)
P value = 1.53e-06 (Fisher's exact test), Q value = 0.0014
Table S8. Gene #4: '2q gain mutation analysis' versus Clinical Feature #1: 'MRNA_CNMF'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 |
---|---|---|---|
ALL | 215 | 213 | 129 |
2Q GAIN MUTATED | 61 | 21 | 17 |
2Q GAIN WILD-TYPE | 154 | 192 | 112 |
Figure S8. Get High-res Image Gene #4: '2q gain mutation analysis' versus Clinical Feature #1: 'MRNA_CNMF'
![](D4V1.png)
P value = 6.48e-07 (Fisher's exact test), Q value = 0.00061
Table S9. Gene #4: '2q gain mutation analysis' versus Clinical Feature #2: 'MRNA_CHIERARCHICAL'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 |
---|---|---|---|
ALL | 233 | 199 | 125 |
2Q GAIN MUTATED | 26 | 59 | 14 |
2Q GAIN WILD-TYPE | 207 | 140 | 111 |
Figure S9. Get High-res Image Gene #4: '2q gain mutation analysis' versus Clinical Feature #2: 'MRNA_CHIERARCHICAL'
![](D4V2.png)
P value = 1.43e-08 (Fisher's exact test), Q value = 1.3e-05
Table S10. Gene #4: '2q gain mutation analysis' versus Clinical Feature #5: 'CN_CNMF'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 |
---|---|---|---|
ALL | 166 | 204 | 199 |
2Q GAIN MUTATED | 17 | 23 | 63 |
2Q GAIN WILD-TYPE | 149 | 181 | 136 |
Figure S10. Get High-res Image Gene #4: '2q gain mutation analysis' versus Clinical Feature #5: 'CN_CNMF'
![](D4V5.png)
P value = 2e-06 (Fisher's exact test), Q value = 0.0019
Table S11. Gene #4: '2q gain mutation analysis' versus Clinical Feature #6: 'METHLYATION_CNMF'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 |
---|---|---|---|
ALL | 171 | 176 | 221 |
2Q GAIN MUTATED | 53 | 25 | 25 |
2Q GAIN WILD-TYPE | 118 | 151 | 196 |
Figure S11. Get High-res Image Gene #4: '2q gain mutation analysis' versus Clinical Feature #6: 'METHLYATION_CNMF'
![](D4V6.png)
P value = 1.02e-09 (Fisher's exact test), Q value = 9.6e-07
Table S12. Gene #6: '3q gain mutation analysis' versus Clinical Feature #5: 'CN_CNMF'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 |
---|---|---|---|
ALL | 166 | 204 | 199 |
3Q GAIN MUTATED | 38 | 63 | 107 |
3Q GAIN WILD-TYPE | 128 | 141 | 92 |
Figure S12. Get High-res Image Gene #6: '3q gain mutation analysis' versus Clinical Feature #5: 'CN_CNMF'
![](D6V5.png)
P value = 2.09e-07 (Fisher's exact test), Q value = 2e-04
Table S13. Gene #9: '5p gain mutation analysis' versus Clinical Feature #5: 'CN_CNMF'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 |
---|---|---|---|
ALL | 166 | 204 | 199 |
5P GAIN MUTATED | 18 | 63 | 66 |
5P GAIN WILD-TYPE | 148 | 141 | 133 |
Figure S13. Get High-res Image Gene #9: '5p gain mutation analysis' versus Clinical Feature #5: 'CN_CNMF'
![](D9V5.png)
P value = 1.19e-06 (Fisher's exact test), Q value = 0.0011
Table S14. Gene #11: '6p gain mutation analysis' versus Clinical Feature #5: 'CN_CNMF'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 |
---|---|---|---|
ALL | 166 | 204 | 199 |
6P GAIN MUTATED | 15 | 45 | 61 |
6P GAIN WILD-TYPE | 151 | 159 | 138 |
Figure S14. Get High-res Image Gene #11: '6p gain mutation analysis' versus Clinical Feature #5: 'CN_CNMF'
![](D11V5.png)
P value = 0.000238 (Fisher's exact test), Q value = 0.21
Table S15. Gene #11: '6p gain mutation analysis' versus Clinical Feature #6: 'METHLYATION_CNMF'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 |
---|---|---|---|
ALL | 171 | 176 | 221 |
6P GAIN MUTATED | 55 | 27 | 39 |
6P GAIN WILD-TYPE | 116 | 149 | 182 |
Figure S15. Get High-res Image Gene #11: '6p gain mutation analysis' versus Clinical Feature #6: 'METHLYATION_CNMF'
![](D11V6.png)
P value = 1.01e-05 (Fisher's exact test), Q value = 0.0094
Table S16. Gene #12: '6q gain mutation analysis' versus Clinical Feature #5: 'CN_CNMF'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 |
---|---|---|---|
ALL | 166 | 204 | 199 |
6Q GAIN MUTATED | 5 | 21 | 36 |
6Q GAIN WILD-TYPE | 161 | 183 | 163 |
Figure S16. Get High-res Image Gene #12: '6q gain mutation analysis' versus Clinical Feature #5: 'CN_CNMF'
![](D12V5.png)
P value = 6.58e-05 (Fisher's exact test), Q value = 0.06
Table S17. Gene #12: '6q gain mutation analysis' versus Clinical Feature #6: 'METHLYATION_CNMF'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 |
---|---|---|---|
ALL | 171 | 176 | 221 |
6Q GAIN MUTATED | 34 | 10 | 18 |
6Q GAIN WILD-TYPE | 137 | 166 | 203 |
Figure S17. Get High-res Image Gene #12: '6q gain mutation analysis' versus Clinical Feature #6: 'METHLYATION_CNMF'
![](D12V6.png)
P value = 9.19e-08 (Fisher's exact test), Q value = 8.6e-05
Table S18. Gene #13: '7p gain mutation analysis' versus Clinical Feature #5: 'CN_CNMF'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 |
---|---|---|---|
ALL | 166 | 204 | 199 |
7P GAIN MUTATED | 26 | 28 | 71 |
7P GAIN WILD-TYPE | 140 | 176 | 128 |
Figure S18. Get High-res Image Gene #13: '7p gain mutation analysis' versus Clinical Feature #5: 'CN_CNMF'
![](D13V5.png)
P value = 1.05e-06 (Fisher's exact test), Q value = 0.00098
Table S19. Gene #13: '7p gain mutation analysis' versus Clinical Feature #6: 'METHLYATION_CNMF'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 |
---|---|---|---|
ALL | 171 | 176 | 221 |
7P GAIN MUTATED | 62 | 26 | 37 |
7P GAIN WILD-TYPE | 109 | 150 | 184 |
Figure S19. Get High-res Image Gene #13: '7p gain mutation analysis' versus Clinical Feature #6: 'METHLYATION_CNMF'
![](D13V6.png)
P value = 1.05e-05 (Fisher's exact test), Q value = 0.0097
Table S20. Gene #14: '7q gain mutation analysis' versus Clinical Feature #5: 'CN_CNMF'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 |
---|---|---|---|
ALL | 166 | 204 | 199 |
7Q GAIN MUTATED | 35 | 40 | 78 |
7Q GAIN WILD-TYPE | 131 | 164 | 121 |
Figure S20. Get High-res Image Gene #14: '7q gain mutation analysis' versus Clinical Feature #5: 'CN_CNMF'
![](D14V5.png)
P value = 5.38e-05 (Fisher's exact test), Q value = 0.049
Table S21. Gene #19: '10p gain mutation analysis' versus Clinical Feature #2: 'MRNA_CHIERARCHICAL'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 |
---|---|---|---|
ALL | 233 | 199 | 125 |
10P GAIN MUTATED | 54 | 64 | 14 |
10P GAIN WILD-TYPE | 179 | 135 | 111 |
Figure S21. Get High-res Image Gene #19: '10p gain mutation analysis' versus Clinical Feature #2: 'MRNA_CHIERARCHICAL'
![](D19V2.png)
P value = 2.95e-09 (Fisher's exact test), Q value = 2.8e-06
Table S22. Gene #19: '10p gain mutation analysis' versus Clinical Feature #5: 'CN_CNMF'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 |
---|---|---|---|
ALL | 166 | 204 | 199 |
10P GAIN MUTATED | 20 | 36 | 76 |
10P GAIN WILD-TYPE | 146 | 168 | 123 |
Figure S22. Get High-res Image Gene #19: '10p gain mutation analysis' versus Clinical Feature #5: 'CN_CNMF'
![](D19V5.png)
P value = 7.92e-05 (Fisher's exact test), Q value = 0.072
Table S23. Gene #22: '11q gain mutation analysis' versus Clinical Feature #5: 'CN_CNMF'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 |
---|---|---|---|
ALL | 166 | 204 | 199 |
11Q GAIN MUTATED | 5 | 32 | 25 |
11Q GAIN WILD-TYPE | 161 | 172 | 174 |
Figure S23. Get High-res Image Gene #22: '11q gain mutation analysis' versus Clinical Feature #5: 'CN_CNMF'
![](D22V5.png)
P value = 7.56e-05 (Fisher's exact test), Q value = 0.069
Table S24. Gene #23: '12p gain mutation analysis' versus Clinical Feature #1: 'MRNA_CNMF'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 |
---|---|---|---|
ALL | 215 | 213 | 129 |
12P GAIN MUTATED | 102 | 60 | 40 |
12P GAIN WILD-TYPE | 113 | 153 | 89 |
Figure S24. Get High-res Image Gene #23: '12p gain mutation analysis' versus Clinical Feature #1: 'MRNA_CNMF'
![](D23V1.png)
P value = 1.27e-05 (Fisher's exact test), Q value = 0.012
Table S25. Gene #23: '12p gain mutation analysis' versus Clinical Feature #2: 'MRNA_CHIERARCHICAL'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 |
---|---|---|---|
ALL | 233 | 199 | 125 |
12P GAIN MUTATED | 70 | 98 | 34 |
12P GAIN WILD-TYPE | 163 | 101 | 91 |
Figure S25. Get High-res Image Gene #23: '12p gain mutation analysis' versus Clinical Feature #2: 'MRNA_CHIERARCHICAL'
![](D23V2.png)
P value = 4.46e-05 (Chi-square test), Q value = 0.041
Table S26. Gene #23: '12p gain mutation analysis' versus Clinical Feature #4: 'MIR_CHIERARCHICAL'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4 | CLUS_5 | CLUS_6 |
---|---|---|---|---|---|---|
ALL | 65 | 115 | 125 | 99 | 57 | 94 |
12P GAIN MUTATED | 21 | 31 | 42 | 28 | 25 | 54 |
12P GAIN WILD-TYPE | 44 | 84 | 83 | 71 | 32 | 40 |
Figure S26. Get High-res Image Gene #23: '12p gain mutation analysis' versus Clinical Feature #4: 'MIR_CHIERARCHICAL'
![](D23V4.png)
P value = 4.27e-13 (Fisher's exact test), Q value = 4.1e-10
Table S27. Gene #23: '12p gain mutation analysis' versus Clinical Feature #5: 'CN_CNMF'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 |
---|---|---|---|
ALL | 166 | 204 | 199 |
12P GAIN MUTATED | 38 | 56 | 114 |
12P GAIN WILD-TYPE | 128 | 148 | 85 |
Figure S27. Get High-res Image Gene #23: '12p gain mutation analysis' versus Clinical Feature #5: 'CN_CNMF'
![](D23V5.png)
P value = 3.95e-09 (Fisher's exact test), Q value = 3.7e-06
Table S28. Gene #23: '12p gain mutation analysis' versus Clinical Feature #6: 'METHLYATION_CNMF'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 |
---|---|---|---|
ALL | 171 | 176 | 221 |
12P GAIN MUTATED | 95 | 56 | 57 |
12P GAIN WILD-TYPE | 76 | 120 | 164 |
Figure S28. Get High-res Image Gene #23: '12p gain mutation analysis' versus Clinical Feature #6: 'METHLYATION_CNMF'
![](D23V6.png)
P value = 1.46e-05 (Fisher's exact test), Q value = 0.013
Table S29. Gene #23: '12p gain mutation analysis' versus Clinical Feature #9: 'MRNASEQ_CNMF'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 |
---|---|---|---|
ALL | 100 | 67 | 91 |
12P GAIN MUTATED | 23 | 20 | 50 |
12P GAIN WILD-TYPE | 77 | 47 | 41 |
Figure S29. Get High-res Image Gene #23: '12p gain mutation analysis' versus Clinical Feature #9: 'MRNASEQ_CNMF'
![](D23V9.png)
P value = 5.65e-06 (Fisher's exact test), Q value = 0.0052
Table S30. Gene #24: '12q gain mutation analysis' versus Clinical Feature #2: 'MRNA_CHIERARCHICAL'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 |
---|---|---|---|
ALL | 233 | 199 | 125 |
12Q GAIN MUTATED | 34 | 65 | 18 |
12Q GAIN WILD-TYPE | 199 | 134 | 107 |
Figure S30. Get High-res Image Gene #24: '12q gain mutation analysis' versus Clinical Feature #2: 'MRNA_CHIERARCHICAL'
![](D24V2.png)
P value = 1.22e-14 (Fisher's exact test), Q value = 1.2e-11
Table S31. Gene #24: '12q gain mutation analysis' versus Clinical Feature #5: 'CN_CNMF'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 |
---|---|---|---|
ALL | 166 | 204 | 199 |
12Q GAIN MUTATED | 24 | 18 | 80 |
12Q GAIN WILD-TYPE | 142 | 186 | 119 |
Figure S31. Get High-res Image Gene #24: '12q gain mutation analysis' versus Clinical Feature #5: 'CN_CNMF'
![](D24V5.png)
P value = 9.49e-06 (Fisher's exact test), Q value = 0.0088
Table S32. Gene #24: '12q gain mutation analysis' versus Clinical Feature #6: 'METHLYATION_CNMF'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 |
---|---|---|---|
ALL | 171 | 176 | 221 |
12Q GAIN MUTATED | 59 | 28 | 35 |
12Q GAIN WILD-TYPE | 112 | 148 | 186 |
Figure S32. Get High-res Image Gene #24: '12q gain mutation analysis' versus Clinical Feature #6: 'METHLYATION_CNMF'
![](D24V6.png)
P value = 0.000254 (Fisher's exact test), Q value = 0.23
Table S33. Gene #25: '13q gain mutation analysis' versus Clinical Feature #6: 'METHLYATION_CNMF'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 |
---|---|---|---|
ALL | 171 | 176 | 221 |
13Q GAIN MUTATED | 23 | 12 | 6 |
13Q GAIN WILD-TYPE | 148 | 164 | 215 |
Figure S33. Get High-res Image Gene #25: '13q gain mutation analysis' versus Clinical Feature #6: 'METHLYATION_CNMF'
![](D25V6.png)
P value = 8.22e-05 (Fisher's exact test), Q value = 0.075
Table S34. Gene #32: '18p gain mutation analysis' versus Clinical Feature #6: 'METHLYATION_CNMF'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 |
---|---|---|---|
ALL | 171 | 176 | 221 |
18P GAIN MUTATED | 38 | 12 | 24 |
18P GAIN WILD-TYPE | 133 | 164 | 197 |
Figure S34. Get High-res Image Gene #32: '18p gain mutation analysis' versus Clinical Feature #6: 'METHLYATION_CNMF'
![](D32V6.png)
P value = 1.95e-08 (Fisher's exact test), Q value = 1.8e-05
Table S35. Gene #34: '19p gain mutation analysis' versus Clinical Feature #5: 'CN_CNMF'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 |
---|---|---|---|
ALL | 166 | 204 | 199 |
19P GAIN MUTATED | 17 | 21 | 61 |
19P GAIN WILD-TYPE | 149 | 183 | 138 |
Figure S35. Get High-res Image Gene #34: '19p gain mutation analysis' versus Clinical Feature #5: 'CN_CNMF'
![](D34V5.png)
P value = 6.85e-07 (Fisher's exact test), Q value = 0.00064
Table S36. Gene #35: '19q gain mutation analysis' versus Clinical Feature #5: 'CN_CNMF'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 |
---|---|---|---|
ALL | 166 | 204 | 199 |
19Q GAIN MUTATED | 15 | 22 | 55 |
19Q GAIN WILD-TYPE | 151 | 182 | 144 |
Figure S36. Get High-res Image Gene #35: '19q gain mutation analysis' versus Clinical Feature #5: 'CN_CNMF'
![](D35V5.png)
P value = 5.26e-07 (Fisher's exact test), Q value = 0.00049
Table S37. Gene #36: '20p gain mutation analysis' versus Clinical Feature #2: 'MRNA_CHIERARCHICAL'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 |
---|---|---|---|
ALL | 233 | 199 | 125 |
20P GAIN MUTATED | 90 | 108 | 31 |
20P GAIN WILD-TYPE | 143 | 91 | 94 |
Figure S37. Get High-res Image Gene #36: '20p gain mutation analysis' versus Clinical Feature #2: 'MRNA_CHIERARCHICAL'
![](D36V2.png)
P value = 4.08e-06 (Chi-square test), Q value = 0.0038
Table S38. Gene #36: '20p gain mutation analysis' versus Clinical Feature #4: 'MIR_CHIERARCHICAL'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4 | CLUS_5 | CLUS_6 |
---|---|---|---|---|---|---|
ALL | 65 | 115 | 125 | 99 | 57 | 94 |
20P GAIN MUTATED | 24 | 41 | 37 | 36 | 30 | 60 |
20P GAIN WILD-TYPE | 41 | 74 | 88 | 63 | 27 | 34 |
Figure S38. Get High-res Image Gene #36: '20p gain mutation analysis' versus Clinical Feature #4: 'MIR_CHIERARCHICAL'
![](D36V4.png)
P value = 3.87e-15 (Fisher's exact test), Q value = 3.7e-12
Table S39. Gene #36: '20p gain mutation analysis' versus Clinical Feature #5: 'CN_CNMF'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 |
---|---|---|---|
ALL | 166 | 204 | 199 |
20P GAIN MUTATED | 43 | 64 | 127 |
20P GAIN WILD-TYPE | 123 | 140 | 72 |
Figure S39. Get High-res Image Gene #36: '20p gain mutation analysis' versus Clinical Feature #5: 'CN_CNMF'
![](D36V5.png)
P value = 4.1e-12 (Fisher's exact test), Q value = 3.9e-09
Table S40. Gene #36: '20p gain mutation analysis' versus Clinical Feature #6: 'METHLYATION_CNMF'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 |
---|---|---|---|
ALL | 171 | 176 | 221 |
20P GAIN MUTATED | 109 | 61 | 64 |
20P GAIN WILD-TYPE | 62 | 115 | 157 |
Figure S40. Get High-res Image Gene #36: '20p gain mutation analysis' versus Clinical Feature #6: 'METHLYATION_CNMF'
![](D36V6.png)
P value = 1.94e-05 (Fisher's exact test), Q value = 0.018
Table S41. Gene #37: '20q gain mutation analysis' versus Clinical Feature #1: 'MRNA_CNMF'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 |
---|---|---|---|
ALL | 215 | 213 | 129 |
20Q GAIN MUTATED | 127 | 78 | 62 |
20Q GAIN WILD-TYPE | 88 | 135 | 67 |
Figure S41. Get High-res Image Gene #37: '20q gain mutation analysis' versus Clinical Feature #1: 'MRNA_CNMF'
![](D37V1.png)
P value = 3.35e-13 (Fisher's exact test), Q value = 3.2e-10
Table S42. Gene #37: '20q gain mutation analysis' versus Clinical Feature #2: 'MRNA_CHIERARCHICAL'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 |
---|---|---|---|
ALL | 233 | 199 | 125 |
20Q GAIN MUTATED | 110 | 129 | 28 |
20Q GAIN WILD-TYPE | 123 | 70 | 97 |
Figure S42. Get High-res Image Gene #37: '20q gain mutation analysis' versus Clinical Feature #2: 'MRNA_CHIERARCHICAL'
![](D37V2.png)
P value = 1.6e-06 (Chi-square test), Q value = 0.0015
Table S43. Gene #37: '20q gain mutation analysis' versus Clinical Feature #4: 'MIR_CHIERARCHICAL'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4 | CLUS_5 | CLUS_6 |
---|---|---|---|---|---|---|
ALL | 65 | 115 | 125 | 99 | 57 | 94 |
20Q GAIN MUTATED | 26 | 47 | 48 | 43 | 34 | 68 |
20Q GAIN WILD-TYPE | 39 | 68 | 77 | 56 | 23 | 26 |
Figure S43. Get High-res Image Gene #37: '20q gain mutation analysis' versus Clinical Feature #4: 'MIR_CHIERARCHICAL'
![](D37V4.png)
P value = 3.3e-20 (Fisher's exact test), Q value = 3.2e-17
Table S44. Gene #37: '20q gain mutation analysis' versus Clinical Feature #5: 'CN_CNMF'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 |
---|---|---|---|
ALL | 166 | 204 | 199 |
20Q GAIN MUTATED | 46 | 80 | 147 |
20Q GAIN WILD-TYPE | 120 | 124 | 52 |
Figure S44. Get High-res Image Gene #37: '20q gain mutation analysis' versus Clinical Feature #5: 'CN_CNMF'
![](D37V5.png)
P value = 9.65e-17 (Fisher's exact test), Q value = 9.2e-14
Table S45. Gene #37: '20q gain mutation analysis' versus Clinical Feature #6: 'METHLYATION_CNMF'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 |
---|---|---|---|
ALL | 171 | 176 | 221 |
20Q GAIN MUTATED | 128 | 70 | 75 |
20Q GAIN WILD-TYPE | 43 | 106 | 146 |
Figure S45. Get High-res Image Gene #37: '20q gain mutation analysis' versus Clinical Feature #6: 'METHLYATION_CNMF'
![](D37V6.png)
P value = 7.07e-06 (Fisher's exact test), Q value = 0.0065
Table S46. Gene #38: '21q gain mutation analysis' versus Clinical Feature #5: 'CN_CNMF'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 |
---|---|---|---|
ALL | 166 | 204 | 199 |
21Q GAIN MUTATED | 10 | 17 | 43 |
21Q GAIN WILD-TYPE | 156 | 187 | 156 |
Figure S46. Get High-res Image Gene #38: '21q gain mutation analysis' versus Clinical Feature #5: 'CN_CNMF'
![](D38V5.png)
P value = 0.000186 (Fisher's exact test), Q value = 0.17
Table S47. Gene #38: '21q gain mutation analysis' versus Clinical Feature #6: 'METHLYATION_CNMF'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 |
---|---|---|---|
ALL | 171 | 176 | 221 |
21Q GAIN MUTATED | 36 | 12 | 22 |
21Q GAIN WILD-TYPE | 135 | 164 | 199 |
Figure S47. Get High-res Image Gene #38: '21q gain mutation analysis' versus Clinical Feature #6: 'METHLYATION_CNMF'
![](D38V6.png)
P value = 0.000253 (Fisher's exact test), Q value = 0.23
Table S48. Gene #48: '4q loss mutation analysis' versus Clinical Feature #12: 'MIRSEQ_CHIERARCHICAL'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 |
---|---|---|---|
ALL | 5 | 281 | 161 |
4Q LOSS MUTATED | 0 | 133 | 101 |
4Q LOSS WILD-TYPE | 5 | 148 | 60 |
Figure S48. Get High-res Image Gene #48: '4q loss mutation analysis' versus Clinical Feature #12: 'MIRSEQ_CHIERARCHICAL'
![](D48V12.png)
P value = 0.000144 (Fisher's exact test), Q value = 0.13
Table S49. Gene #50: '5q loss mutation analysis' versus Clinical Feature #1: 'MRNA_CNMF'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 |
---|---|---|---|
ALL | 215 | 213 | 129 |
5Q LOSS MUTATED | 87 | 55 | 27 |
5Q LOSS WILD-TYPE | 128 | 158 | 102 |
Figure S49. Get High-res Image Gene #50: '5q loss mutation analysis' versus Clinical Feature #1: 'MRNA_CNMF'
![](D50V1.png)
P value = 2.22e-05 (Fisher's exact test), Q value = 0.02
Table S50. Gene #50: '5q loss mutation analysis' versus Clinical Feature #2: 'MRNA_CHIERARCHICAL'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 |
---|---|---|---|
ALL | 233 | 199 | 125 |
5Q LOSS MUTATED | 51 | 84 | 34 |
5Q LOSS WILD-TYPE | 182 | 115 | 91 |
Figure S50. Get High-res Image Gene #50: '5q loss mutation analysis' versus Clinical Feature #2: 'MRNA_CHIERARCHICAL'
![](D50V2.png)
P value = 0.000173 (Fisher's exact test), Q value = 0.16
Table S51. Gene #50: '5q loss mutation analysis' versus Clinical Feature #5: 'CN_CNMF'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 |
---|---|---|---|
ALL | 166 | 204 | 199 |
5Q LOSS MUTATED | 38 | 52 | 82 |
5Q LOSS WILD-TYPE | 128 | 152 | 117 |
Figure S51. Get High-res Image Gene #50: '5q loss mutation analysis' versus Clinical Feature #5: 'CN_CNMF'
![](D50V5.png)
P value = 1.7e-07 (Fisher's exact test), Q value = 0.00016
Table S52. Gene #50: '5q loss mutation analysis' versus Clinical Feature #6: 'METHLYATION_CNMF'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 |
---|---|---|---|
ALL | 171 | 176 | 221 |
5Q LOSS MUTATED | 79 | 34 | 59 |
5Q LOSS WILD-TYPE | 92 | 142 | 162 |
Figure S52. Get High-res Image Gene #50: '5q loss mutation analysis' versus Clinical Feature #6: 'METHLYATION_CNMF'
![](D50V6.png)
P value = 1.51e-11 (Fisher's exact test), Q value = 1.4e-08
Table S53. Gene #58: '9q loss mutation analysis' versus Clinical Feature #5: 'CN_CNMF'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 |
---|---|---|---|
ALL | 166 | 204 | 199 |
9Q LOSS MUTATED | 62 | 56 | 122 |
9Q LOSS WILD-TYPE | 104 | 148 | 77 |
Figure S53. Get High-res Image Gene #58: '9q loss mutation analysis' versus Clinical Feature #5: 'CN_CNMF'
![](D58V5.png)
P value = 1.26e-06 (Fisher's exact test), Q value = 0.0012
Table S54. Gene #65: '13q loss mutation analysis' versus Clinical Feature #6: 'METHLYATION_CNMF'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 |
---|---|---|---|
ALL | 171 | 176 | 221 |
13Q LOSS MUTATED | 78 | 56 | 128 |
13Q LOSS WILD-TYPE | 93 | 120 | 93 |
Figure S54. Get High-res Image Gene #65: '13q loss mutation analysis' versus Clinical Feature #6: 'METHLYATION_CNMF'
![](D65V6.png)
P value = 0.000118 (Fisher's exact test), Q value = 0.11
Table S55. Gene #66: '14q loss mutation analysis' versus Clinical Feature #5: 'CN_CNMF'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 |
---|---|---|---|
ALL | 166 | 204 | 199 |
14Q LOSS MUTATED | 42 | 43 | 79 |
14Q LOSS WILD-TYPE | 124 | 161 | 120 |
Figure S55. Get High-res Image Gene #66: '14q loss mutation analysis' versus Clinical Feature #5: 'CN_CNMF'
![](D66V5.png)
P value = 7.17e-11 (Fisher's exact test), Q value = 6.8e-08
Table S56. Gene #67: '15q loss mutation analysis' versus Clinical Feature #5: 'CN_CNMF'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 |
---|---|---|---|
ALL | 166 | 204 | 199 |
15Q LOSS MUTATED | 48 | 57 | 115 |
15Q LOSS WILD-TYPE | 118 | 147 | 84 |
Figure S56. Get High-res Image Gene #67: '15q loss mutation analysis' versus Clinical Feature #5: 'CN_CNMF'
![](D67V5.png)
P value = 0.000185 (Fisher's exact test), Q value = 0.17
Table S57. Gene #67: '15q loss mutation analysis' versus Clinical Feature #6: 'METHLYATION_CNMF'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 |
---|---|---|---|
ALL | 171 | 176 | 221 |
15Q LOSS MUTATED | 87 | 52 | 81 |
15Q LOSS WILD-TYPE | 84 | 124 | 140 |
Figure S57. Get High-res Image Gene #67: '15q loss mutation analysis' versus Clinical Feature #6: 'METHLYATION_CNMF'
![](D67V6.png)
P value = 0.00012 (Fisher's exact test), Q value = 0.11
Table S58. Gene #79: '22q loss mutation analysis' versus Clinical Feature #1: 'MRNA_CNMF'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 |
---|---|---|---|
ALL | 215 | 213 | 129 |
22Q LOSS MUTATED | 168 | 129 | 80 |
22Q LOSS WILD-TYPE | 47 | 84 | 49 |
Figure S58. Get High-res Image Gene #79: '22q loss mutation analysis' versus Clinical Feature #1: 'MRNA_CNMF'
![](D79V1.png)
P value = 1.8e-05 (Fisher's exact test), Q value = 0.017
Table S59. Gene #79: '22q loss mutation analysis' versus Clinical Feature #2: 'MRNA_CHIERARCHICAL'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 |
---|---|---|---|
ALL | 233 | 199 | 125 |
22Q LOSS MUTATED | 134 | 156 | 87 |
22Q LOSS WILD-TYPE | 99 | 43 | 38 |
Figure S59. Get High-res Image Gene #79: '22q loss mutation analysis' versus Clinical Feature #2: 'MRNA_CHIERARCHICAL'
![](D79V2.png)
P value = 0.000176 (Fisher's exact test), Q value = 0.16
Table S60. Gene #79: '22q loss mutation analysis' versus Clinical Feature #5: 'CN_CNMF'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 |
---|---|---|---|
ALL | 166 | 204 | 199 |
22Q LOSS MUTATED | 103 | 127 | 157 |
22Q LOSS WILD-TYPE | 63 | 77 | 42 |
Figure S60. Get High-res Image Gene #79: '22q loss mutation analysis' versus Clinical Feature #5: 'CN_CNMF'
![](D79V5.png)
-
Mutation data file = broad_values_by_arm.mutsig.cluster.txt
-
Molecular subtypes file = OV-TP.transferedmergedcluster.txt
-
Number of patients = 569
-
Number of significantly arm-level cnvs = 80
-
Number of molecular subtypes = 12
-
Exclude genes that fewer than K tumors have mutations, K = 3
For binary or multi-class clinical features (nominal or ordinal), two-tailed Fisher's exact tests (Fisher 1922) were used to estimate the P values using the 'fisher.test' function in R
For multi-class clinical features (nominal or ordinal), Chi-square tests (Greenwood and Nikulin 1996) were used to estimate the P values using the 'chisq.test' function in R
For multiple hypothesis correction, Q value is the False Discovery Rate (FDR) analogue of the P value (Benjamini and Hochberg 1995), defined as the minimum FDR at which the test may be called significant. We used the 'Benjamini and Hochberg' method of 'p.adjust' function in R to convert P values into Q values.
This is an experimental feature. The full results of the analysis summarized in this report can be downloaded from the TCGA Data Coordination Center.