This pipeline computes the correlation between significant copy number variation (cnv focal) genes and selected clinical features.
Testing the association between copy number variation 28 focal events and 9 clinical features across 162 patients, no significant finding detected with Q value < 0.25.
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No focal cnvs related to clinical features.
Clinical Features |
Time to Death |
YEARS TO BIRTH |
TUMOR TISSUE SITE |
GENDER |
RADIATION THERAPY |
KARNOFSKY PERFORMANCE SCORE |
HISTOLOGICAL TYPE |
NUMBER OF LYMPH NODES |
RACE | ||
nCNV (%) | nWild-Type | logrank test | Wilcoxon-test | Fisher's exact test | Fisher's exact test | Fisher's exact test | Wilcoxon-test | Fisher's exact test | Wilcoxon-test | Fisher's exact test | |
amp 1q21 3 | 30 (19%) | 132 |
0.0298 (0.779) |
0.631 (1.00) |
0.178 (0.995) |
0.224 (0.995) |
0.00452 (0.569) |
0.922 (1.00) |
0.388 (1.00) |
0.284 (0.995) |
0.839 (1.00) |
amp 4q31 1 | 15 (9%) | 147 |
0.722 (1.00) |
0.175 (0.995) |
0.0758 (0.784) |
0.593 (1.00) |
1 (1.00) |
0.192 (0.995) |
0.386 (1.00) |
0.312 (0.995) |
0.835 (1.00) |
amp 11p15 2 | 8 (5%) | 154 |
0.579 (1.00) |
0.874 (1.00) |
0.353 (1.00) |
0.292 (0.995) |
1 (1.00) |
0.969 (1.00) |
1 (1.00) |
0.0542 (0.784) |
|
amp 12q13 3 | 16 (10%) | 146 |
0.434 (1.00) |
0.102 (0.879) |
0.0765 (0.784) |
1 (1.00) |
1 (1.00) |
0.799 (1.00) |
0.247 (0.995) |
0.411 (1.00) |
|
amp 14q24 3 | 10 (6%) | 152 |
0.172 (0.995) |
0.469 (1.00) |
0.213 (0.995) |
0.514 (1.00) |
1 (1.00) |
0.807 (1.00) |
0.0782 (0.784) |
||
amp 17q21 31 | 16 (10%) | 146 |
0.213 (0.995) |
0.232 (0.995) |
0.31 (0.995) |
0.0169 (0.709) |
0.0786 (0.784) |
0.501 (1.00) |
0.485 (1.00) |
0.531 (1.00) |
0.841 (1.00) |
del 1p12 | 113 (70%) | 49 |
0.8 (1.00) |
0.718 (1.00) |
0.823 (1.00) |
1 (1.00) |
1 (1.00) |
0.765 (1.00) |
0.115 (0.881) |
0.212 (0.995) |
0.0589 (0.784) |
del 1q44 | 21 (13%) | 141 |
0.067 (0.784) |
0.755 (1.00) |
1 (1.00) |
0.348 (1.00) |
1 (1.00) |
0.552 (1.00) |
1 (1.00) |
0.292 (0.995) |
0.876 (1.00) |
del 3p24 1 | 64 (40%) | 98 |
0.466 (1.00) |
0.197 (0.995) |
0.136 (0.95) |
0.108 (0.879) |
0.383 (1.00) |
0.455 (1.00) |
0.208 (0.995) |
0.737 (1.00) |
0.274 (0.995) |
del 3q26 1 | 93 (57%) | 69 |
0.252 (0.995) |
0.288 (0.995) |
0.834 (1.00) |
1 (1.00) |
1 (1.00) |
0.829 (1.00) |
0.949 (1.00) |
0.535 (1.00) |
1 (1.00) |
del 4q22 1 | 13 (8%) | 149 |
0.574 (1.00) |
0.832 (1.00) |
0.47 (1.00) |
0.573 (1.00) |
1 (1.00) |
0.17 (0.995) |
0.499 (1.00) |
0.801 (1.00) |
|
del 4q34 2 | 13 (8%) | 149 |
0.14 (0.954) |
0.274 (0.995) |
0.127 (0.942) |
1 (1.00) |
1 (1.00) |
0.17 (0.995) |
0.4 (1.00) |
0.8 (1.00) |
|
del 5q15 | 12 (7%) | 150 |
0.553 (1.00) |
0.428 (1.00) |
1 (1.00) |
0.772 (1.00) |
1 (1.00) |
0.247 (0.995) |
0.575 (1.00) |
0.652 (1.00) |
0.31 (0.995) |
del 6p12 3 | 10 (6%) | 152 |
0.459 (1.00) |
0.733 (1.00) |
0.684 (1.00) |
0.112 (0.879) |
0.279 (0.995) |
0.0309 (0.779) |
0.369 (1.00) |
0.515 (1.00) |
|
del 6q16 1 | 24 (15%) | 138 |
0.977 (1.00) |
0.459 (1.00) |
0.257 (0.995) |
0.267 (0.995) |
0.561 (1.00) |
0.472 (1.00) |
0.448 (1.00) |
1 (1.00) |
|
del 8p22 | 25 (15%) | 137 |
0.351 (1.00) |
0.149 (0.989) |
0.0809 (0.784) |
0.383 (1.00) |
0.577 (1.00) |
0.631 (1.00) |
0.0521 (0.784) |
0.818 (1.00) |
|
del 8q23 3 | 13 (8%) | 149 |
0.357 (1.00) |
0.583 (1.00) |
0.47 (1.00) |
0.773 (1.00) |
1 (1.00) |
0.848 (1.00) |
1 (1.00) |
||
del 9p24 2 | 15 (9%) | 147 |
0.00121 (0.306) |
0.919 (1.00) |
1 (1.00) |
0.284 (0.995) |
0.0697 (0.784) |
0.0309 (0.779) |
0.634 (1.00) |
1 (1.00) |
0.83 (1.00) |
del 9q21 12 | 14 (9%) | 148 |
0.638 (1.00) |
0.594 (1.00) |
1 (1.00) |
1 (1.00) |
0.0612 (0.784) |
0.0309 (0.779) |
0.622 (1.00) |
0.821 (1.00) |
|
del 11p15 4 | 58 (36%) | 104 |
0.0801 (0.784) |
0.218 (0.995) |
0.202 (0.995) |
0.417 (1.00) |
1 (1.00) |
0.992 (1.00) |
0.26 (0.995) |
0.617 (1.00) |
0.956 (1.00) |
del 11q22 1 | 50 (31%) | 112 |
0.683 (1.00) |
0.279 (0.995) |
0.826 (1.00) |
0.865 (1.00) |
0.326 (1.00) |
0.617 (1.00) |
0.838 (1.00) |
0.44 (1.00) |
0.812 (1.00) |
del 12q21 33 | 8 (5%) | 154 |
0.496 (1.00) |
0.754 (1.00) |
1 (1.00) |
0.728 (1.00) |
0.229 (0.995) |
0.298 (0.995) |
1 (1.00) |
1 (1.00) |
|
del 13q22 3 | 8 (5%) | 154 |
0.594 (1.00) |
0.923 (1.00) |
1 (1.00) |
1 (1.00) |
1 (1.00) |
0.805 (1.00) |
1 (1.00) |
0.23 (0.995) |
|
del 16q21 | 5 (3%) | 157 |
0.679 (1.00) |
0.397 (1.00) |
0.588 (1.00) |
1 (1.00) |
1 (1.00) |
1 (1.00) |
0.58 (1.00) |
||
del 17p13 2 | 64 (40%) | 98 |
0.896 (1.00) |
0.956 (1.00) |
0.0107 (0.709) |
0.63 (1.00) |
0.383 (1.00) |
0.109 (0.879) |
0.0513 (0.784) |
0.301 (0.995) |
0.196 (0.995) |
del 17q11 2 | 42 (26%) | 120 |
0.0627 (0.784) |
0.481 (1.00) |
0.0159 (0.709) |
0.721 (1.00) |
1 (1.00) |
0.777 (1.00) |
0.0526 (0.784) |
0.133 (0.95) |
0.154 (0.993) |
del 22q13 31 | 65 (40%) | 97 |
0.0136 (0.709) |
0.237 (0.995) |
0.0907 (0.839) |
0.873 (1.00) |
1 (1.00) |
0.651 (1.00) |
0.0932 (0.839) |
0.0506 (0.784) |
0.376 (1.00) |
del xp21 1 | 46 (28%) | 116 |
0.621 (1.00) |
0.879 (1.00) |
1 (1.00) |
1 (1.00) |
0.323 (1.00) |
0.533 (1.00) |
0.266 (0.995) |
0.946 (1.00) |
0.504 (1.00) |
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Copy number data file = all_lesions.txt from GISTIC pipeline
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Processed Copy number data file = /xchip/cga/gdac-prod/tcga-gdac/jobResults/GDAC_Correlate_Genomic_Events_Preprocess/PCPG-TP/22533877/transformed.cor.cli.txt
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Clinical data file = /xchip/cga/gdac-prod/tcga-gdac/jobResults/Append_Data/PCPG-TP/22506925/PCPG-TP.merged_data.txt
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Number of patients = 162
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Number of significantly focal cnvs = 28
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Number of selected clinical features = 9
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Exclude genes that fewer than K tumors have mutations, K = 3
For survival clinical features, the Kaplan-Meier survival curves of tumors with and without gene mutations were plotted and the statistical significance P values were estimated by logrank test (Bland and Altman 2004) using the 'survdiff' function in R
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.