This pipeline computes the correlation between significant arm-level copy number variations (cnvs) and subtypes.
Testing the association between copy number variation 73 arm-level results and 6 molecular subtypes across 126 patients, 6 significant findings detected with Q value < 0.25.
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3q gain cnv correlated to 'CN_CNMF'.
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20q gain cnv correlated to 'CN_CNMF'.
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3p loss cnv correlated to 'MRNASEQ_CHIERARCHICAL'.
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4q loss cnv correlated to 'CN_CNMF'.
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16q loss cnv correlated to 'MRNASEQ_CHIERARCHICAL'.
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18q loss cnv correlated to 'MRNASEQ_CNMF'.
Table 1. Get Full Table Overview of the association between significant copy number variation of 73 arm-level results and 6 molecular subtypes. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 6 significant findings detected.
Molecular subtypes |
CN CNMF |
METHLYATION CNMF |
MRNASEQ CNMF |
MRNASEQ CHIERARCHICAL |
MIRSEQ CNMF |
MIRSEQ CHIERARCHICAL |
||
nCNV (%) | nWild-Type | Fisher's exact test | Fisher's exact test | Fisher's exact test | Fisher's exact test | Fisher's exact test | Fisher's exact test | |
3q gain | 0 (0%) | 64 |
1.3e-05 (0.0057) |
0.362 (1.00) |
0.0191 (1.00) |
0.0478 (1.00) |
0.0537 (1.00) |
0.177 (1.00) |
20q gain | 0 (0%) | 88 |
0.000534 (0.231) |
0.362 (1.00) |
0.512 (1.00) |
0.167 (1.00) |
0.632 (1.00) |
0.145 (1.00) |
3p loss | 0 (0%) | 99 |
0.32 (1.00) |
0.0016 (0.687) |
0.198 (1.00) |
0.000436 (0.19) |
0.0284 (1.00) |
0.0038 (1.00) |
4q loss | 0 (0%) | 102 |
6.4e-06 (0.0028) |
0.773 (1.00) |
0.0976 (1.00) |
0.297 (1.00) |
0.627 (1.00) |
1 (1.00) |
16q loss | 0 (0%) | 112 |
0.821 (1.00) |
0.0237 (1.00) |
0.00107 (0.46) |
0.000523 (0.227) |
0.0574 (1.00) |
0.00554 (1.00) |
18q loss | 0 (0%) | 102 |
0.112 (1.00) |
0.0214 (1.00) |
0.000428 (0.187) |
0.00334 (1.00) |
0.0132 (1.00) |
0.00661 (1.00) |
1p gain | 0 (0%) | 92 |
0.415 (1.00) |
0.764 (1.00) |
0.274 (1.00) |
0.904 (1.00) |
0.982 (1.00) |
0.828 (1.00) |
1q gain | 0 (0%) | 78 |
0.0208 (1.00) |
0.479 (1.00) |
0.345 (1.00) |
0.568 (1.00) |
0.252 (1.00) |
0.0764 (1.00) |
2p gain | 0 (0%) | 109 |
0.0833 (1.00) |
0.303 (1.00) |
0.1 (1.00) |
0.0951 (1.00) |
0.271 (1.00) |
0.0441 (1.00) |
2q gain | 0 (0%) | 121 |
0.0843 (1.00) |
0.611 (1.00) |
0.0694 (1.00) |
0.153 (1.00) |
1 (1.00) |
0.637 (1.00) |
3p gain | 0 (0%) | 105 |
0.568 (1.00) |
0.685 (1.00) |
0.717 (1.00) |
0.0367 (1.00) |
0.483 (1.00) |
1 (1.00) |
4q gain | 0 (0%) | 123 |
0.115 (1.00) |
0.11 (1.00) |
0.453 (1.00) |
0.485 (1.00) |
0.487 (1.00) |
0.216 (1.00) |
5p gain | 0 (0%) | 85 |
0.0204 (1.00) |
1 (1.00) |
0.935 (1.00) |
0.728 (1.00) |
0.881 (1.00) |
0.304 (1.00) |
5q gain | 0 (0%) | 113 |
0.572 (1.00) |
0.394 (1.00) |
1 (1.00) |
1 (1.00) |
0.759 (1.00) |
0.53 (1.00) |
6p gain | 0 (0%) | 108 |
0.108 (1.00) |
0.00399 (1.00) |
0.0262 (1.00) |
0.0987 (1.00) |
0.188 (1.00) |
0.172 (1.00) |
6q gain | 0 (0%) | 117 |
0.501 (1.00) |
0.00852 (1.00) |
0.0536 (1.00) |
0.00601 (1.00) |
0.0953 (1.00) |
0.0216 (1.00) |
7p gain | 0 (0%) | 119 |
0.48 (1.00) |
0.195 (1.00) |
0.198 (1.00) |
0.41 (1.00) |
0.316 (1.00) |
0.101 (1.00) |
7q gain | 0 (0%) | 115 |
0.109 (1.00) |
0.34 (1.00) |
0.285 (1.00) |
1 (1.00) |
0.482 (1.00) |
1 (1.00) |
8p gain | 0 (0%) | 116 |
0.644 (1.00) |
0.41 (1.00) |
0.12 (1.00) |
0.167 (1.00) |
0.38 (1.00) |
1 (1.00) |
8q gain | 0 (0%) | 104 |
0.0349 (1.00) |
0.0253 (1.00) |
0.104 (1.00) |
0.383 (1.00) |
0.104 (1.00) |
0.21 (1.00) |
9p gain | 0 (0%) | 114 |
0.32 (1.00) |
0.748 (1.00) |
0.47 (1.00) |
0.0148 (1.00) |
0.412 (1.00) |
0.509 (1.00) |
9q gain | 0 (0%) | 115 |
0.669 (1.00) |
0.239 (1.00) |
0.434 (1.00) |
0.0361 (1.00) |
0.128 (1.00) |
1 (1.00) |
10p gain | 0 (0%) | 118 |
0.653 (1.00) |
0.901 (1.00) |
0.883 (1.00) |
0.725 (1.00) |
0.156 (1.00) |
1 (1.00) |
10q gain | 0 (0%) | 122 |
0.457 (1.00) |
0.568 (1.00) |
0.81 (1.00) |
0.145 (1.00) |
0.33 (1.00) |
0.583 (1.00) |
12p gain | 0 (0%) | 112 |
0.0103 (1.00) |
0.418 (1.00) |
0.385 (1.00) |
0.00322 (1.00) |
0.378 (1.00) |
0.354 (1.00) |
12q gain | 0 (0%) | 116 |
0.0213 (1.00) |
0.841 (1.00) |
0.637 (1.00) |
0.0515 (1.00) |
0.244 (1.00) |
1 (1.00) |
13q gain | 0 (0%) | 120 |
0.0397 (1.00) |
0.491 (1.00) |
0.168 (1.00) |
0.488 (1.00) |
0.88 (1.00) |
0.365 (1.00) |
14q gain | 0 (0%) | 116 |
0.305 (1.00) |
1 (1.00) |
0.201 (1.00) |
0.124 (1.00) |
0.402 (1.00) |
0.487 (1.00) |
15q gain | 0 (0%) | 113 |
0.00184 (0.787) |
1 (1.00) |
0.313 (1.00) |
0.794 (1.00) |
0.844 (1.00) |
1 (1.00) |
16p gain | 0 (0%) | 112 |
0.0456 (1.00) |
0.171 (1.00) |
0.506 (1.00) |
0.0615 (1.00) |
0.533 (1.00) |
0.121 (1.00) |
16q gain | 0 (0%) | 116 |
0.92 (1.00) |
0.546 (1.00) |
0.364 (1.00) |
0.0122 (1.00) |
0.402 (1.00) |
0.487 (1.00) |
17p gain | 0 (0%) | 121 |
0.616 (1.00) |
0.214 (1.00) |
0.269 (1.00) |
0.0126 (1.00) |
0.423 (1.00) |
0.0287 (1.00) |
17q gain | 0 (0%) | 113 |
0.0157 (1.00) |
0.0131 (1.00) |
0.0253 (1.00) |
0.0148 (1.00) |
0.394 (1.00) |
0.0208 (1.00) |
18p gain | 0 (0%) | 114 |
0.408 (1.00) |
0.692 (1.00) |
0.606 (1.00) |
0.0271 (1.00) |
0.24 (1.00) |
0.345 (1.00) |
18q gain | 0 (0%) | 119 |
0.0757 (1.00) |
1 (1.00) |
0.486 (1.00) |
0.00832 (1.00) |
0.391 (1.00) |
1 (1.00) |
19p gain | 0 (0%) | 118 |
0.53 (1.00) |
0.727 (1.00) |
0.547 (1.00) |
0.331 (1.00) |
0.558 (1.00) |
1 (1.00) |
19q gain | 0 (0%) | 103 |
0.218 (1.00) |
0.672 (1.00) |
0.409 (1.00) |
0.0309 (1.00) |
0.126 (1.00) |
0.138 (1.00) |
20p gain | 0 (0%) | 94 |
0.000689 (0.297) |
0.478 (1.00) |
0.856 (1.00) |
0.083 (1.00) |
0.946 (1.00) |
0.18 (1.00) |
21q gain | 0 (0%) | 112 |
0.556 (1.00) |
0.938 (1.00) |
0.266 (1.00) |
0.905 (1.00) |
0.332 (1.00) |
0.758 (1.00) |
22q gain | 0 (0%) | 118 |
0.0403 (1.00) |
0.901 (1.00) |
0.326 (1.00) |
0.00377 (1.00) |
0.313 (1.00) |
1 (1.00) |
Xq gain | 0 (0%) | 120 |
0.435 (1.00) |
0.199 (1.00) |
0.763 (1.00) |
0.332 (1.00) |
0.305 (1.00) |
0.365 (1.00) |
1q loss | 0 (0%) | 123 |
0.262 (1.00) |
0.786 (1.00) |
1 (1.00) |
0.485 (1.00) |
0.839 (1.00) |
1 (1.00) |
2p loss | 0 (0%) | 123 |
0.115 (1.00) |
0.182 (1.00) |
0.251 (1.00) |
0.673 (1.00) |
0.736 (1.00) |
0.553 (1.00) |
2q loss | 0 (0%) | 121 |
0.0843 (1.00) |
0.0295 (1.00) |
0.0859 (1.00) |
0.267 (1.00) |
0.723 (1.00) |
1 (1.00) |
4p loss | 0 (0%) | 85 |
0.00186 (0.792) |
0.0459 (1.00) |
0.279 (1.00) |
0.956 (1.00) |
0.351 (1.00) |
0.215 (1.00) |
5p loss | 0 (0%) | 123 |
0.346 (1.00) |
0.786 (1.00) |
0.79 (1.00) |
1 (1.00) |
0.356 (1.00) |
1 (1.00) |
5q loss | 0 (0%) | 106 |
0.0316 (1.00) |
0.0535 (1.00) |
0.527 (1.00) |
0.0345 (1.00) |
0.0788 (1.00) |
0.00686 (1.00) |
6p loss | 0 (0%) | 114 |
0.926 (1.00) |
0.0536 (1.00) |
0.384 (1.00) |
0.432 (1.00) |
0.725 (1.00) |
1 (1.00) |
6q loss | 0 (0%) | 103 |
0.208 (1.00) |
0.587 (1.00) |
0.287 (1.00) |
0.777 (1.00) |
0.395 (1.00) |
1 (1.00) |
7p loss | 0 (0%) | 120 |
0.0625 (1.00) |
0.875 (1.00) |
0.558 (1.00) |
0.332 (1.00) |
0.779 (1.00) |
0.365 (1.00) |
7q loss | 0 (0%) | 113 |
0.0129 (1.00) |
0.707 (1.00) |
0.0352 (1.00) |
0.188 (1.00) |
0.106 (1.00) |
0.753 (1.00) |
8p loss | 0 (0%) | 99 |
0.435 (1.00) |
0.259 (1.00) |
0.445 (1.00) |
0.795 (1.00) |
0.803 (1.00) |
1 (1.00) |
8q loss | 0 (0%) | 120 |
1 (1.00) |
0.491 (1.00) |
0.326 (1.00) |
0.332 (1.00) |
0.359 (1.00) |
0.0669 (1.00) |
9p loss | 0 (0%) | 114 |
0.32 (1.00) |
0.864 (1.00) |
0.74 (1.00) |
0.776 (1.00) |
0.97 (1.00) |
1 (1.00) |
9q loss | 0 (0%) | 115 |
0.669 (1.00) |
0.288 (1.00) |
0.0145 (1.00) |
0.275 (1.00) |
0.366 (1.00) |
0.0864 (1.00) |
10p loss | 0 (0%) | 104 |
0.0152 (1.00) |
0.795 (1.00) |
0.139 (1.00) |
0.102 (1.00) |
0.765 (1.00) |
0.61 (1.00) |
10q loss | 0 (0%) | 102 |
0.0129 (1.00) |
0.958 (1.00) |
0.79 (1.00) |
0.181 (1.00) |
0.477 (1.00) |
0.459 (1.00) |
11p loss | 0 (0%) | 99 |
0.0822 (1.00) |
0.332 (1.00) |
0.874 (1.00) |
0.941 (1.00) |
0.782 (1.00) |
0.644 (1.00) |
11q loss | 0 (0%) | 96 |
0.00965 (1.00) |
0.748 (1.00) |
0.771 (1.00) |
0.177 (1.00) |
0.952 (1.00) |
0.373 (1.00) |
12p loss | 0 (0%) | 107 |
0.00218 (0.926) |
0.209 (1.00) |
0.739 (1.00) |
0.72 (1.00) |
0.589 (1.00) |
0.18 (1.00) |
12q loss | 0 (0%) | 122 |
0.0356 (1.00) |
0.46 (1.00) |
0.286 (1.00) |
0.298 (1.00) |
1 (1.00) |
1 (1.00) |
13q loss | 0 (0%) | 103 |
0.43 (1.00) |
0.0341 (1.00) |
0.489 (1.00) |
0.0659 (1.00) |
0.0301 (1.00) |
0.208 (1.00) |
14q loss | 0 (0%) | 119 |
0.424 (1.00) |
0.143 (1.00) |
0.0234 (1.00) |
0.00355 (1.00) |
0.2 (1.00) |
0.0258 (1.00) |
15q loss | 0 (0%) | 118 |
0.00157 (0.676) |
1 (1.00) |
0.316 (1.00) |
0.116 (1.00) |
0.772 (1.00) |
0.697 (1.00) |
16p loss | 0 (0%) | 118 |
0.415 (1.00) |
0.144 (1.00) |
0.129 (1.00) |
0.00638 (1.00) |
0.117 (1.00) |
0.241 (1.00) |
17p loss | 0 (0%) | 99 |
0.0148 (1.00) |
0.00444 (1.00) |
0.0411 (1.00) |
0.0596 (1.00) |
0.0202 (1.00) |
0.0173 (1.00) |
17q loss | 0 (0%) | 121 |
0.616 (1.00) |
0.0295 (1.00) |
0.0859 (1.00) |
0.267 (1.00) |
0.296 (1.00) |
0.321 (1.00) |
18p loss | 0 (0%) | 110 |
0.55 (1.00) |
0.465 (1.00) |
0.0389 (1.00) |
0.0988 (1.00) |
0.1 (1.00) |
0.0818 (1.00) |
19p loss | 0 (0%) | 114 |
0.44 (1.00) |
0.375 (1.00) |
0.258 (1.00) |
0.397 (1.00) |
0.19 (1.00) |
0.509 (1.00) |
19q loss | 0 (0%) | 120 |
0.495 (1.00) |
0.569 (1.00) |
0.486 (1.00) |
0.173 (1.00) |
0.779 (1.00) |
0.365 (1.00) |
20p loss | 0 (0%) | 118 |
0.53 (1.00) |
0.418 (1.00) |
0.596 (1.00) |
0.376 (1.00) |
0.955 (1.00) |
0.697 (1.00) |
21q loss | 0 (0%) | 113 |
0.000976 (0.421) |
0.53 (1.00) |
0.858 (1.00) |
0.81 (1.00) |
0.328 (1.00) |
0.753 (1.00) |
22q loss | 0 (0%) | 113 |
0.87 (1.00) |
1 (1.00) |
0.867 (1.00) |
0.512 (1.00) |
0.759 (1.00) |
1 (1.00) |
P value = 1.3e-05 (Fisher's exact test), Q value = 0.0057
Table S1. Gene #6: '3q gain' versus Molecular Subtype #1: 'CN_CNMF'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 |
---|---|---|---|
ALL | 42 | 32 | 52 |
3Q GAIN CNV | 33 | 12 | 17 |
3Q GAIN WILD-TYPE | 9 | 20 | 35 |
Figure S1. Get High-res Image Gene #6: '3q gain' versus Molecular Subtype #1: 'CN_CNMF'
![](D6V1.png)
P value = 0.000534 (Fisher's exact test), Q value = 0.23
Table S2. Gene #34: '20q gain' versus Molecular Subtype #1: 'CN_CNMF'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 |
---|---|---|---|
ALL | 42 | 32 | 52 |
20Q GAIN CNV | 21 | 10 | 7 |
20Q GAIN WILD-TYPE | 21 | 22 | 45 |
Figure S2. Get High-res Image Gene #34: '20q gain' versus Molecular Subtype #1: 'CN_CNMF'
![](D34V1.png)
P value = 0.000436 (Fisher's exact test), Q value = 0.19
Table S3. Gene #41: '3p loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 |
---|---|---|---|
ALL | 11 | 64 | 36 |
3P LOSS CNV | 1 | 24 | 2 |
3P LOSS WILD-TYPE | 10 | 40 | 34 |
Figure S3. Get High-res Image Gene #41: '3p loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'
![](D41V4.png)
P value = 6.4e-06 (Fisher's exact test), Q value = 0.0028
Table S4. Gene #43: '4q loss' versus Molecular Subtype #1: 'CN_CNMF'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 |
---|---|---|---|
ALL | 42 | 32 | 52 |
4Q LOSS CNV | 7 | 15 | 2 |
4Q LOSS WILD-TYPE | 35 | 17 | 50 |
Figure S4. Get High-res Image Gene #43: '4q loss' versus Molecular Subtype #1: 'CN_CNMF'
![](D43V1.png)
P value = 0.000523 (Fisher's exact test), Q value = 0.23
Table S5. Gene #64: '16q loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 |
---|---|---|---|
ALL | 11 | 64 | 36 |
16Q LOSS CNV | 4 | 2 | 8 |
16Q LOSS WILD-TYPE | 7 | 62 | 28 |
Figure S5. Get High-res Image Gene #64: '16q loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'
![](D64V4.png)
P value = 0.000428 (Fisher's exact test), Q value = 0.19
Table S6. Gene #68: '18q loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'
nPatients | CLUS_1 | CLUS_2 | CLUS_3 |
---|---|---|---|
ALL | 50 | 30 | 31 |
18Q LOSS CNV | 3 | 6 | 13 |
18Q LOSS WILD-TYPE | 47 | 24 | 18 |
Figure S6. Get High-res Image Gene #68: '18q loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'
![](D68V3.png)
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Mutation data file = broad_values_by_arm.mutsig.cluster.txt
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Molecular subtypes file = CESC-TP.transferedmergedcluster.txt
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Number of patients = 126
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Number of significantly arm-level cnvs = 73
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Number of molecular subtypes = 6
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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 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.