This pipeline computes the correlation between significant arm-level copy number variations (cnvs) and subtypes.
Testing the association between copy number variation 65 arm-level results and 4 molecular subtypes across 51 patients, no significant finding detected with Q value < 0.25.
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No arm-level cnvs related to molecular subtypes.
Table 1. Get Full Table Overview of the association between significant copy number variation of 65 arm-level results and 4 molecular subtypes. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, no significant finding detected.
Molecular subtypes |
CN CNMF |
METHLYATION CNMF |
MIRSEQ CNMF |
MIRSEQ CHIERARCHICAL |
||
nCNV (%) | nWild-Type | Fisher's exact test | Fisher's exact test | Fisher's exact test | Fisher's exact test | |
1p gain | 0 (0%) | 43 |
0.119 (1.00) |
0.248 (1.00) |
0.573 (1.00) |
0.606 (1.00) |
1q gain | 0 (0%) | 44 |
0.224 (1.00) |
0.0127 (1.00) |
0.0783 (1.00) |
0.164 (1.00) |
4p gain | 0 (0%) | 46 |
0.588 (1.00) |
0.417 (1.00) |
||
5p gain | 0 (0%) | 39 |
0.0662 (1.00) |
1 (1.00) |
1 (1.00) |
1 (1.00) |
5q gain | 0 (0%) | 42 |
0.0624 (1.00) |
0.221 (1.00) |
1 (1.00) |
1 (1.00) |
6p gain | 0 (0%) | 44 |
0.0233 (1.00) |
0.111 (1.00) |
0.107 (1.00) |
0.235 (1.00) |
6q gain | 0 (0%) | 42 |
0.0346 (1.00) |
0.0354 (1.00) |
0.0476 (1.00) |
0.0926 (1.00) |
7p gain | 0 (0%) | 38 |
0.00452 (1.00) |
0.222 (1.00) |
0.632 (1.00) |
0.283 (1.00) |
7q gain | 0 (0%) | 40 |
0.0536 (1.00) |
0.114 (1.00) |
0.632 (1.00) |
0.283 (1.00) |
8p gain | 0 (0%) | 42 |
0.0205 (1.00) |
0.588 (1.00) |
0.632 (1.00) |
0.689 (1.00) |
8q gain | 0 (0%) | 43 |
0.498 (1.00) |
0.0569 (1.00) |
1 (1.00) |
1 (1.00) |
9p gain | 0 (0%) | 48 |
0.101 (1.00) |
0.502 (1.00) |
0.488 (1.00) |
|
9q gain | 0 (0%) | 45 |
0.0153 (1.00) |
0.484 (1.00) |
0.107 (1.00) |
0.235 (1.00) |
11p gain | 0 (0%) | 48 |
0.459 (1.00) |
1 (1.00) |
0.448 (1.00) |
|
12p gain | 0 (0%) | 44 |
1 (1.00) |
0.774 (1.00) |
1 (1.00) |
|
14q gain | 0 (0%) | 48 |
1 (1.00) |
0.282 (1.00) |
1 (1.00) |
|
15q gain | 0 (0%) | 43 |
0.202 (1.00) |
0.712 (1.00) |
1 (1.00) |
|
16p gain | 0 (0%) | 45 |
0.546 (1.00) |
0.14 (1.00) |
0.573 (1.00) |
0.606 (1.00) |
17p gain | 0 (0%) | 44 |
0.00158 (0.383) |
0.00216 (0.523) |
1 (1.00) |
|
17q gain | 0 (0%) | 46 |
0.0669 (1.00) |
0.417 (1.00) |
0.573 (1.00) |
0.103 (1.00) |
18p gain | 0 (0%) | 45 |
0.301 (1.00) |
0.484 (1.00) |
1 (1.00) |
|
18q gain | 0 (0%) | 43 |
0.498 (1.00) |
0.44 (1.00) |
1 (1.00) |
1 (1.00) |
19p gain | 0 (0%) | 42 |
0.0046 (1.00) |
0.588 (1.00) |
0.573 (1.00) |
0.103 (1.00) |
19q gain | 0 (0%) | 46 |
0.00241 (0.58) |
0.851 (1.00) |
||
20p gain | 0 (0%) | 40 |
0.316 (1.00) |
0.334 (1.00) |
1 (1.00) |
1 (1.00) |
20q gain | 0 (0%) | 37 |
0.251 (1.00) |
0.0463 (1.00) |
1 (1.00) |
1 (1.00) |
21q gain | 0 (0%) | 45 |
0.64 (1.00) |
0.164 (1.00) |
1 (1.00) |
|
22q gain | 0 (0%) | 46 |
1 (1.00) |
1 (1.00) |
0.448 (1.00) |
|
1p loss | 0 (0%) | 42 |
0.0624 (1.00) |
0.198 (1.00) |
0.144 (1.00) |
0.0558 (1.00) |
1q loss | 0 (0%) | 45 |
0.403 (1.00) |
1 (1.00) |
1 (1.00) |
1 (1.00) |
2p loss | 0 (0%) | 41 |
0.908 (1.00) |
0.163 (1.00) |
0.632 (1.00) |
0.689 (1.00) |
2q loss | 0 (0%) | 43 |
0.892 (1.00) |
0.311 (1.00) |
1 (1.00) |
1 (1.00) |
3p loss | 0 (0%) | 41 |
0.134 (1.00) |
0.559 (1.00) |
0.107 (1.00) |
0.235 (1.00) |
3q loss | 0 (0%) | 39 |
0.407 (1.00) |
0.6 (1.00) |
0.183 (1.00) |
0.363 (1.00) |
4p loss | 0 (0%) | 44 |
0.17 (1.00) |
0.111 (1.00) |
1 (1.00) |
1 (1.00) |
4q loss | 0 (0%) | 44 |
0.29 (1.00) |
0.111 (1.00) |
1 (1.00) |
1 (1.00) |
5p loss | 0 (0%) | 47 |
0.67 (1.00) |
0.533 (1.00) |
1 (1.00) |
1 (1.00) |
5q loss | 0 (0%) | 47 |
1 (1.00) |
1 (1.00) |
0.488 (1.00) |
|
6p loss | 0 (0%) | 43 |
0.62 (1.00) |
0.248 (1.00) |
0.364 (1.00) |
0.488 (1.00) |
6q loss | 0 (0%) | 47 |
0.67 (1.00) |
0.193 (1.00) |
1 (1.00) |
|
7p loss | 0 (0%) | 47 |
0.67 (1.00) |
0.193 (1.00) |
0.573 (1.00) |
0.606 (1.00) |
7q loss | 0 (0%) | 45 |
0.64 (1.00) |
0.14 (1.00) |
0.606 (1.00) |
0.667 (1.00) |
8p loss | 0 (0%) | 42 |
0.376 (1.00) |
0.43 (1.00) |
0.663 (1.00) |
0.119 (1.00) |
8q loss | 0 (0%) | 46 |
0.71 (1.00) |
0.115 (1.00) |
0.232 (1.00) |
0.317 (1.00) |
9p loss | 0 (0%) | 40 |
0.104 (1.00) |
0.162 (1.00) |
0.183 (1.00) |
0.0128 (1.00) |
9q loss | 0 (0%) | 45 |
0.64 (1.00) |
0.656 (1.00) |
0.606 (1.00) |
0.667 (1.00) |
10p loss | 0 (0%) | 34 |
0.155 (1.00) |
0.196 (1.00) |
1 (1.00) |
0.34 (1.00) |
10q loss | 0 (0%) | 31 |
0.0714 (1.00) |
0.0227 (1.00) |
0.0641 (1.00) |
0.0718 (1.00) |
11p loss | 0 (0%) | 36 |
0.363 (1.00) |
0.221 (1.00) |
0.41 (1.00) |
0.0647 (1.00) |
11q loss | 0 (0%) | 40 |
0.0668 (1.00) |
0.334 (1.00) |
0.183 (1.00) |
0.363 (1.00) |
12q loss | 0 (0%) | 47 |
0.45 (1.00) |
1 (1.00) |
0.488 (1.00) |
|
13q loss | 0 (0%) | 28 |
0.18 (1.00) |
0.334 (1.00) |
0.716 (1.00) |
0.56 (1.00) |
14q loss | 0 (0%) | 36 |
0.0792 (1.00) |
0.299 (1.00) |
0.226 (1.00) |
0.15 (1.00) |
15q loss | 0 (0%) | 42 |
0.376 (1.00) |
0.27 (1.00) |
0.00843 (1.00) |
0.0136 (1.00) |
16p loss | 0 (0%) | 42 |
0.65 (1.00) |
1 (1.00) |
0.343 (1.00) |
0.466 (1.00) |
16q loss | 0 (0%) | 31 |
0.934 (1.00) |
0.0457 (1.00) |
0.688 (1.00) |
0.368 (1.00) |
17p loss | 0 (0%) | 43 |
0.226 (1.00) |
0.248 (1.00) |
1 (1.00) |
1 (1.00) |
17q loss | 0 (0%) | 46 |
0.0353 (1.00) |
0.115 (1.00) |
0.573 (1.00) |
0.606 (1.00) |
18p loss | 0 (0%) | 43 |
1 (1.00) |
0.89 (1.00) |
0.606 (1.00) |
0.667 (1.00) |
18q loss | 0 (0%) | 41 |
0.818 (1.00) |
1 (1.00) |
0.606 (1.00) |
0.667 (1.00) |
19q loss | 0 (0%) | 46 |
0.71 (1.00) |
0.248 (1.00) |
1 (1.00) |
|
20p loss | 0 (0%) | 46 |
0.114 (1.00) |
0.851 (1.00) |
0.343 (1.00) |
0.466 (1.00) |
21q loss | 0 (0%) | 43 |
0.137 (1.00) |
0.89 (1.00) |
1 (1.00) |
1 (1.00) |
22q loss | 0 (0%) | 36 |
0.423 (1.00) |
0.639 (1.00) |
0.702 (1.00) |
0.817 (1.00) |
Xq loss | 0 (0%) | 41 |
0.035 (1.00) |
0.0715 (1.00) |
1 (1.00) |
1 (1.00) |
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Mutation data file = broad_values_by_arm.mutsig.cluster.txt
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Molecular subtypes file = SARC-TP.transferedmergedcluster.txt
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Number of patients = 51
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Number of significantly arm-level cnvs = 65
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Number of molecular subtypes = 4
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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.