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 3 clinical features across 57 patients, no significant finding detected with Q value < 0.25.
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No focal cnvs related to clinical features.
Table 1. Get Full Table Overview of the association between significant copy number variation of 28 focal events and 3 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, no significant finding detected.
|
Clinical Features |
AGE | GENDER | RACE | ||
| nCNV (%) | nWild-Type | Wilcoxon-test | Fisher's exact test | Fisher's exact test | |
| amp 1q21 3 | 7 (12%) | 50 |
0.568 (1.00) |
1 (1.00) |
0.704 (1.00) |
| amp 4q25 | 3 (5%) | 54 |
0.775 (1.00) |
1 (1.00) |
0.459 (1.00) |
| amp 4q31 1 | 4 (7%) | 53 |
0.925 (1.00) |
0.607 (1.00) |
1 (1.00) |
| amp 11p15 2 | 5 (9%) | 52 |
0.117 (1.00) |
0.647 (1.00) |
0.348 (1.00) |
| amp 12q13 3 | 8 (14%) | 49 |
0.434 (1.00) |
0.699 (1.00) |
0.42 (1.00) |
| amp 14q24 3 | 6 (11%) | 51 |
0.886 (1.00) |
1 (1.00) |
0.0624 (1.00) |
| amp 17q21 31 | 4 (7%) | 53 |
0.31 (1.00) |
0.119 (1.00) |
1 (1.00) |
| del 1p12 | 40 (70%) | 17 |
0.944 (1.00) |
0.078 (1.00) |
1 (1.00) |
| del 1q44 | 5 (9%) | 52 |
0.866 (1.00) |
1 (1.00) |
1 (1.00) |
| del 2q34 | 3 (5%) | 54 |
0.734 (1.00) |
0.279 (1.00) |
0.46 (1.00) |
| del 3p24 1 | 25 (44%) | 32 |
0.263 (1.00) |
0.782 (1.00) |
0.607 (1.00) |
| del 3q26 1 | 41 (72%) | 16 |
0.965 (1.00) |
0.0622 (1.00) |
0.612 (1.00) |
| del 4q22 1 | 8 (14%) | 49 |
0.414 (1.00) |
1 (1.00) |
1 (1.00) |
| del 4q35 2 | 7 (12%) | 50 |
0.789 (1.00) |
0.687 (1.00) |
1 (1.00) |
| del 5q15 | 6 (11%) | 51 |
0.55 (1.00) |
0.654 (1.00) |
1 (1.00) |
| del 6p12 3 | 5 (9%) | 52 |
0.374 (1.00) |
0.151 (1.00) |
0.563 (1.00) |
| del 6q16 1 | 9 (16%) | 48 |
0.278 (1.00) |
0.0201 (1.00) |
0.564 (1.00) |
| del 8p22 | 8 (14%) | 49 |
0.8 (1.00) |
0.699 (1.00) |
0.423 (1.00) |
| del 9p24 2 | 4 (7%) | 53 |
0.223 (1.00) |
0.286 (1.00) |
0.563 (1.00) |
| del 9q21 12 | 6 (11%) | 51 |
0.948 (1.00) |
0.0809 (1.00) |
0.423 (1.00) |
| del 11p15 4 | 19 (33%) | 38 |
0.267 (1.00) |
0.24 (1.00) |
0.639 (1.00) |
| del 11q22 1 | 16 (28%) | 41 |
0.894 (1.00) |
0.216 (1.00) |
0.693 (1.00) |
| del 12q21 33 | 4 (7%) | 53 |
0.381 (1.00) |
1 (1.00) |
1 (1.00) |
| del 16q21 | 3 (5%) | 54 |
0.592 (1.00) |
1 (1.00) |
0.457 (1.00) |
| del 17p13 2 | 23 (40%) | 34 |
0.672 (1.00) |
1 (1.00) |
0.439 (1.00) |
| del 17q11 2 | 17 (30%) | 40 |
0.747 (1.00) |
0.763 (1.00) |
1 (1.00) |
| del 22q13 31 | 26 (46%) | 31 |
0.706 (1.00) |
1 (1.00) |
0.77 (1.00) |
| del xp21 1 | 20 (35%) | 37 |
1 (1.00) |
0.383 (1.00) |
0.027 (1.00) |
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Copy number data file = transformed.cor.cli.txt
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Clinical data file = PCPG-TP.merged_data.txt
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Number of patients = 57
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Number of significantly focal cnvs = 28
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Number of selected clinical features = 3
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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.
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.