This pipeline computes the correlation between significant copy number variation (cnv focal) genes and selected clinical features.
Testing the association between copy number variation 21 focal events and 3 clinical features across 21 patients, one significant finding detected with Q value < 0.25.
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del_17q24.1 cnv correlated to 'Time to Death'.
Clinical Features |
Time to Death |
AGE | GENDER | ||
nCNV (%) | nWild-Type | logrank test | t-test | Fisher's exact test | |
del 17q24 1 | 3 (14%) | 18 |
3.74e-05 (0.00235) |
0.844 (1.00) |
1 (1.00) |
amp 1q31 1 | 7 (33%) | 14 |
0.222 (1.00) |
0.469 (1.00) |
1 (1.00) |
amp 2p15 | 7 (33%) | 14 |
0.0511 (1.00) |
0.913 (1.00) |
1 (1.00) |
amp 3q27 3 | 5 (24%) | 16 |
0.389 (1.00) |
0.808 (1.00) |
1 (1.00) |
amp 8q24 12 | 5 (24%) | 16 |
0.477 (1.00) |
0.28 (1.00) |
1 (1.00) |
amp 12q13 12 | 4 (19%) | 17 |
0.655 (1.00) |
0.353 (1.00) |
1 (1.00) |
amp 16p11 2 | 5 (24%) | 16 |
0.469 (1.00) |
0.21 (1.00) |
1 (1.00) |
amp xq27 3 | 4 (19%) | 17 |
0.655 (1.00) |
0.546 (1.00) |
1 (1.00) |
del 1p13 1 | 4 (19%) | 17 |
0.799 (1.00) |
0.719 (1.00) |
0.253 (1.00) |
del 1q43 | 4 (19%) | 17 |
0.569 (1.00) |
0.575 (1.00) |
0.131 (1.00) |
del 2q23 1 | 4 (19%) | 17 |
0.609 (1.00) |
0.743 (1.00) |
0.131 (1.00) |
del 6q14 1 | 6 (29%) | 15 |
0.27 (1.00) |
0.625 (1.00) |
0.631 (1.00) |
del 6q23 3 | 5 (24%) | 16 |
0.79 (1.00) |
0.105 (1.00) |
0.325 (1.00) |
del 9p21 3 | 7 (33%) | 14 |
0.27 (1.00) |
0.873 (1.00) |
1 (1.00) |
del 10q23 31 | 4 (19%) | 17 |
0.201 (1.00) |
0.565 (1.00) |
1 (1.00) |
del 13q14 2 | 3 (14%) | 18 |
0.0253 (1.00) |
0.173 (1.00) |
0.257 (1.00) |
del 13q33 3 | 4 (19%) | 17 |
0.389 (1.00) |
0.139 (1.00) |
0.131 (1.00) |
del 15q15 1 | 6 (29%) | 15 |
0.799 (1.00) |
0.799 (1.00) |
0.336 (1.00) |
del 15q21 1 | 6 (29%) | 15 |
0.799 (1.00) |
0.799 (1.00) |
0.336 (1.00) |
del 16p13 13 | 3 (14%) | 18 |
0.724 (1.00) |
0.881 (1.00) |
0.257 (1.00) |
del 16q23 1 | 3 (14%) | 18 |
0.724 (1.00) |
0.91 (1.00) |
0.257 (1.00) |
P value = 3.74e-05 (logrank test), Q value = 0.0024
nPatients | nDeath | Duration Range (Median), Month | |
---|---|---|---|
ALL | 21 | 4 | 2.0 - 211.2 (31.7) |
DEL PEAK 18(17Q24.1) MUTATED | 3 | 1 | 2.0 - 19.6 (4.6) |
DEL PEAK 18(17Q24.1) WILD-TYPE | 18 | 3 | 4.1 - 211.2 (38.3) |
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Copy number data file = transformed.cor.cli.txt
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Clinical data file = DLBC-TP.merged_data.txt
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Number of patients = 21
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Number of significantly focal cnvs = 21
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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 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 continuous numerical clinical features, two-tailed Student's t test with unequal variance (Lehmann and Romano 2005) was applied to compare the clinical values between tumors with and without gene mutations using 't.test' 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.