This pipeline computes the correlation between significant arm-level copy number variations (cnvs) and molecular subtypes.
Testing the association between copy number variation 52 arm-level events and 10 molecular subtypes across 48 patients, 2 significant findings detected with P value < 0.05 and Q value < 0.25.
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7p gain cnv correlated to 'CN_CNMF'.
-
7q gain cnv correlated to 'CN_CNMF'.
Clinical Features |
CN CNMF |
METHLYATION CNMF |
RPPA CNMF |
RPPA CHIERARCHICAL |
MRNASEQ CNMF |
MRNASEQ CHIERARCHICAL |
MIRSEQ CNMF |
MIRSEQ CHIERARCHICAL |
MIRSEQ MATURE CNMF |
MIRSEQ MATURE 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 | Fisher's exact test | Fisher's exact test | Fisher's exact test | Fisher's exact test | |
7p gain | 15 (31%) | 33 |
1.04e-05 (0.0027) |
0.534 (1.00) |
1 (1.00) |
0.762 (1.00) |
1 (1.00) |
0.458 (1.00) |
0.925 (1.00) |
0.886 (1.00) |
1 (1.00) |
0.123 (1.00) |
7q gain | 13 (27%) | 35 |
7.71e-06 (0.0027) |
1 (1.00) |
0.653 (1.00) |
1 (1.00) |
0.67 (1.00) |
0.122 (1.00) |
0.661 (1.00) |
0.988 (1.00) |
1 (1.00) |
0.381 (1.00) |
1q gain | 6 (12%) | 42 |
0.197 (1.00) |
0.666 (1.00) |
0.449 (1.00) |
0.274 (1.00) |
1 (1.00) |
0.636 (1.00) |
0.416 (1.00) |
0.316 (1.00) |
1 (1.00) |
0.843 (1.00) |
2p gain | 6 (12%) | 42 |
0.669 (1.00) |
0.666 (1.00) |
0.696 (1.00) |
0.825 (1.00) |
1 (1.00) |
1 (1.00) |
0.605 (1.00) |
1 (1.00) |
0.219 (1.00) |
|
2q gain | 6 (12%) | 42 |
0.669 (1.00) |
0.666 (1.00) |
0.695 (1.00) |
0.824 (1.00) |
1 (1.00) |
1 (1.00) |
0.604 (1.00) |
1 (1.00) |
0.221 (1.00) |
|
3p gain | 10 (21%) | 38 |
0.0363 (0.773) |
0.286 (1.00) |
0.59 (1.00) |
0.247 (1.00) |
1 (1.00) |
0.676 (1.00) |
0.633 (1.00) |
0.403 (1.00) |
0.707 (1.00) |
0.35 (1.00) |
3q gain | 13 (27%) | 35 |
0.0188 (0.739) |
0.193 (1.00) |
0.131 (1.00) |
0.0371 (0.773) |
1 (1.00) |
0.514 (1.00) |
0.765 (1.00) |
0.565 (1.00) |
1 (1.00) |
0.248 (1.00) |
5p gain | 7 (15%) | 41 |
0.687 (1.00) |
1 (1.00) |
0.49 (1.00) |
0.687 (1.00) |
1 (1.00) |
0.339 (1.00) |
0.639 (1.00) |
0.356 (1.00) |
0.117 (1.00) |
|
5q gain | 6 (12%) | 42 |
1 (1.00) |
1 (1.00) |
0.488 (1.00) |
0.689 (1.00) |
0.464 (1.00) |
0.66 (1.00) |
0.796 (1.00) |
0.613 (1.00) |
0.533 (1.00) |
|
6p gain | 6 (12%) | 42 |
0.197 (1.00) |
1 (1.00) |
0.697 (1.00) |
0.824 (1.00) |
1 (1.00) |
1 (1.00) |
1 (1.00) |
0.862 (1.00) |
0.644 (1.00) |
0.882 (1.00) |
6q gain | 4 (8%) | 44 |
0.0199 (0.739) |
0.609 (1.00) |
1 (1.00) |
0.77 (1.00) |
1 (1.00) |
0.711 (1.00) |
1 (1.00) |
0.0844 (1.00) |
0.873 (1.00) |
|
8p gain | 7 (15%) | 41 |
0.687 (1.00) |
0.416 (1.00) |
1 (1.00) |
1 (1.00) |
0.206 (1.00) |
0.103 (1.00) |
0.00551 (0.716) |
0.428 (1.00) |
0.259 (1.00) |
|
8q gain | 8 (17%) | 40 |
0.451 (1.00) |
0.245 (1.00) |
0.829 (1.00) |
0.825 (1.00) |
0.206 (1.00) |
0.148 (1.00) |
0.0278 (0.772) |
0.428 (1.00) |
0.257 (1.00) |
|
9p gain | 7 (15%) | 41 |
0.687 (1.00) |
1 (1.00) |
1 (1.00) |
0.44 (1.00) |
1 (1.00) |
0.78 (1.00) |
0.64 (1.00) |
1 (1.00) |
0.469 (1.00) |
|
9q gain | 7 (15%) | 41 |
0.687 (1.00) |
1 (1.00) |
1 (1.00) |
0.441 (1.00) |
1 (1.00) |
0.479 (1.00) |
0.291 (1.00) |
1 (1.00) |
0.266 (1.00) |
|
10p gain | 4 (8%) | 44 |
0.0199 (0.739) |
1 (1.00) |
1 (1.00) |
1 (1.00) |
1 (1.00) |
0.581 (1.00) |
0.636 (1.00) |
|||
10q gain | 4 (8%) | 44 |
0.286 (1.00) |
0.609 (1.00) |
1 (1.00) |
0.767 (1.00) |
0.464 (1.00) |
0.424 (1.00) |
0.778 (1.00) |
0.0844 (1.00) |
0.258 (1.00) |
|
11p gain | 9 (19%) | 39 |
0.451 (1.00) |
0.461 (1.00) |
0.697 (1.00) |
0.379 (1.00) |
0.6 (1.00) |
0.146 (1.00) |
0.717 (1.00) |
0.165 (1.00) |
0.433 (1.00) |
0.227 (1.00) |
11q gain | 13 (27%) | 35 |
0.0959 (1.00) |
0.193 (1.00) |
0.328 (1.00) |
0.358 (1.00) |
0.686 (1.00) |
0.0876 (1.00) |
0.45 (1.00) |
0.0733 (1.00) |
0.468 (1.00) |
0.399 (1.00) |
12p gain | 7 (15%) | 41 |
1 (1.00) |
0.416 (1.00) |
0.831 (1.00) |
0.3 (1.00) |
0.583 (1.00) |
0.111 (1.00) |
0.815 (1.00) |
0.276 (1.00) |
0.384 (1.00) |
0.864 (1.00) |
12q gain | 9 (19%) | 39 |
1 (1.00) |
0.137 (1.00) |
0.87 (1.00) |
0.475 (1.00) |
1 (1.00) |
0.146 (1.00) |
0.644 (1.00) |
0.136 (1.00) |
0.433 (1.00) |
0.488 (1.00) |
13q gain | 5 (10%) | 43 |
1 (1.00) |
1 (1.00) |
1 (1.00) |
1 (1.00) |
0.206 (1.00) |
0.134 (1.00) |
0.661 (1.00) |
0.0346 (0.773) |
0.839 (1.00) |
|
16p gain | 7 (15%) | 41 |
0.0114 (0.739) |
0.416 (1.00) |
0.855 (1.00) |
1 (1.00) |
0.6 (1.00) |
0.208 (1.00) |
0.326 (1.00) |
0.0285 (0.772) |
0.384 (1.00) |
0.518 (1.00) |
16q gain | 7 (15%) | 41 |
0.0967 (1.00) |
0.0971 (1.00) |
0.855 (1.00) |
1 (1.00) |
0.6 (1.00) |
1 (1.00) |
0.328 (1.00) |
0.0146 (0.739) |
0.384 (1.00) |
0.709 (1.00) |
17q gain | 3 (6%) | 45 |
0.554 (1.00) |
0.234 (1.00) |
1 (1.00) |
0.769 (1.00) |
0.464 (1.00) |
0.604 (1.00) |
0.035 (0.773) |
0.581 (1.00) |
0.499 (1.00) |
|
18p gain | 13 (27%) | 35 |
0.0959 (1.00) |
1 (1.00) |
0.293 (1.00) |
0.78 (1.00) |
1 (1.00) |
0.675 (1.00) |
0.364 (1.00) |
0.123 (1.00) |
0.504 (1.00) |
0.523 (1.00) |
18q gain | 14 (29%) | 34 |
0.0491 (0.881) |
1 (1.00) |
0.453 (1.00) |
0.686 (1.00) |
0.655 (1.00) |
1 (1.00) |
0.451 (1.00) |
0.115 (1.00) |
0.323 (1.00) |
0.404 (1.00) |
19p gain | 3 (6%) | 45 |
0.554 (1.00) |
1 (1.00) |
0.464 (1.00) |
0.687 (1.00) |
0.688 (1.00) |
0.452 (1.00) |
||||
19q gain | 3 (6%) | 45 |
0.554 (1.00) |
1 (1.00) |
0.464 (1.00) |
0.689 (1.00) |
0.688 (1.00) |
0.452 (1.00) |
||||
20p gain | 5 (10%) | 43 |
0.372 (1.00) |
0.348 (1.00) |
0.258 (1.00) |
0.154 (1.00) |
1 (1.00) |
0.288 (1.00) |
0.378 (1.00) |
1 (1.00) |
0.698 (1.00) |
|
20q gain | 4 (8%) | 44 |
1 (1.00) |
0.609 (1.00) |
0.237 (1.00) |
0.119 (1.00) |
0.464 (1.00) |
0.655 (1.00) |
0.817 (1.00) |
0.581 (1.00) |
0.305 (1.00) |
|
21q gain | 10 (21%) | 38 |
1 (1.00) |
1 (1.00) |
0.0824 (1.00) |
0.0338 (0.773) |
1 (1.00) |
0.426 (1.00) |
0.0273 (0.772) |
0.187 (1.00) |
0.258 (1.00) |
0.374 (1.00) |
xp gain | 6 (12%) | 42 |
0.0297 (0.772) |
0.666 (1.00) |
0.806 (1.00) |
0.813 (1.00) |
0.484 (1.00) |
0.52 (1.00) |
0.176 (1.00) |
0.158 (1.00) |
0.013 (0.739) |
|
xq gain | 6 (12%) | 42 |
0.197 (1.00) |
0.666 (1.00) |
0.806 (1.00) |
0.816 (1.00) |
1 (1.00) |
0.386 (1.00) |
0.783 (1.00) |
0.0636 (1.00) |
0.384 (1.00) |
0.111 (1.00) |
1p loss | 3 (6%) | 45 |
0.554 (1.00) |
1 (1.00) |
0.313 (1.00) |
0.57 (1.00) |
1 (1.00) |
1 (1.00) |
1 (1.00) |
0.85 (1.00) |
1 (1.00) |
|
3p loss | 5 (10%) | 43 |
1 (1.00) |
1 (1.00) |
1 (1.00) |
1 (1.00) |
1 (1.00) |
0.854 (1.00) |
0.959 (1.00) |
1 (1.00) |
0.664 (1.00) |
|
3q loss | 4 (8%) | 44 |
1 (1.00) |
1 (1.00) |
1 (1.00) |
1 (1.00) |
1 (1.00) |
0.581 (1.00) |
0.524 (1.00) |
|||
4p loss | 3 (6%) | 45 |
0.554 (1.00) |
1 (1.00) |
0.464 (1.00) |
0.15 (1.00) |
0.688 (1.00) |
1 (1.00) |
||||
4q loss | 4 (8%) | 44 |
0.286 (1.00) |
0.609 (1.00) |
0.594 (1.00) |
0.572 (1.00) |
1 (1.00) |
0.465 (1.00) |
0.234 (1.00) |
0.613 (1.00) |
0.873 (1.00) |
|
6q loss | 7 (15%) | 41 |
1 (1.00) |
0.416 (1.00) |
1 (1.00) |
1 (1.00) |
1 (1.00) |
0.386 (1.00) |
0.706 (1.00) |
0.728 (1.00) |
0.0754 (1.00) |
0.515 (1.00) |
8p loss | 8 (17%) | 40 |
0.0446 (0.829) |
1 (1.00) |
0.0213 (0.739) |
0.0435 (0.829) |
0.311 (1.00) |
0.351 (1.00) |
0.201 (1.00) |
0.0267 (0.772) |
1 (1.00) |
0.934 (1.00) |
8q loss | 4 (8%) | 44 |
0.286 (1.00) |
1 (1.00) |
0.0409 (0.819) |
0.0763 (1.00) |
1 (1.00) |
0.652 (1.00) |
0.157 (1.00) |
1 (1.00) |
||
13q loss | 3 (6%) | 45 |
0.554 (1.00) |
1 (1.00) |
1 (1.00) |
1 (1.00) |
0.846 (1.00) |
1 (1.00) |
||||
15q loss | 7 (15%) | 41 |
0.0114 (0.739) |
0.416 (1.00) |
0.589 (1.00) |
0.568 (1.00) |
0.639 (1.00) |
0.45 (1.00) |
0.127 (1.00) |
0.368 (1.00) |
0.197 (1.00) |
0.745 (1.00) |
16q loss | 4 (8%) | 44 |
0.0199 (0.739) |
1 (1.00) |
0.59 (1.00) |
0.569 (1.00) |
1 (1.00) |
0.639 (1.00) |
0.0949 (1.00) |
0.128 (1.00) |
0.239 (1.00) |
0.664 (1.00) |
17p loss | 9 (19%) | 39 |
0.0195 (0.739) |
1 (1.00) |
1 (1.00) |
1 (1.00) |
1 (1.00) |
0.76 (1.00) |
0.887 (1.00) |
0.501 (1.00) |
0.384 (1.00) |
0.268 (1.00) |
17q loss | 4 (8%) | 44 |
0.286 (1.00) |
0.609 (1.00) |
1 (1.00) |
0.708 (1.00) |
0.492 (1.00) |
0.0844 (1.00) |
0.464 (1.00) |
|||
18p loss | 5 (10%) | 43 |
0.372 (1.00) |
0.348 (1.00) |
0.237 (1.00) |
0.275 (1.00) |
0.484 (1.00) |
0.554 (1.00) |
0.248 (1.00) |
0.158 (1.00) |
0.215 (1.00) |
|
18q loss | 4 (8%) | 44 |
0.286 (1.00) |
0.609 (1.00) |
1 (1.00) |
0.654 (1.00) |
1 (1.00) |
0.581 (1.00) |
0.524 (1.00) |
|||
22q loss | 3 (6%) | 45 |
0.056 (0.971) |
1 (1.00) |
1 (1.00) |
0.767 (1.00) |
1 (1.00) |
1 (1.00) |
0.436 (1.00) |
1 (1.00) |
||
xp loss | 5 (10%) | 43 |
0.372 (1.00) |
0.348 (1.00) |
0.592 (1.00) |
0.571 (1.00) |
0.583 (1.00) |
0.562 (1.00) |
0.333 (1.00) |
0.0138 (0.739) |
0.356 (1.00) |
0.284 (1.00) |
xq loss | 4 (8%) | 44 |
0.286 (1.00) |
0.109 (1.00) |
0.59 (1.00) |
0.572 (1.00) |
0.583 (1.00) |
0.565 (1.00) |
0.142 (1.00) |
0.00207 (0.359) |
0.613 (1.00) |
0.324 (1.00) |
P value = 1.04e-05 (Fisher's exact test), Q value = 0.0027
nPatients | CLUS_1 | CLUS_2 |
---|---|---|
ALL | 29 | 19 |
7P GAIN MUTATED | 2 | 13 |
7P GAIN WILD-TYPE | 27 | 6 |
P value = 7.71e-06 (Fisher's exact test), Q value = 0.0027
nPatients | CLUS_1 | CLUS_2 |
---|---|---|
ALL | 29 | 19 |
7Q GAIN MUTATED | 1 | 12 |
7Q GAIN WILD-TYPE | 28 | 7 |
-
Copy number data file = broad_values_by_arm.txt from GISTIC pipeline
-
Processed Copy number data file = /xchip/cga/gdac-prod/tcga-gdac/jobResults/GDAC_Correlate_Genomic_Events_Preprocess/DLBC-TP/15082594/transformed.cor.cli.txt
-
Molecular subtypes file = /xchip/cga/gdac-prod/tcga-gdac/jobResults/GDAC_mergedClustering/DLBC-TP/15092398/DLBC-TP.transferedmergedcluster.txt
-
Number of patients = 48
-
Number of significantly arm-level cnvs = 52
-
Number of molecular subtypes = 10
-
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.
In addition to the links below, the full results of the analysis summarized in this report can also be downloaded programmatically using firehose_get, or interactively from either the Broad GDAC website or TCGA Data Coordination Center Portal.