This pipeline computes the correlation between significant copy number variation (cnv) genes and selected clinical features.
Testing the association between copy number variation of 6 peak regions and 7 clinical features across 75 patients, one significant finding detected with Q value < 0.25.
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Del Peak 5(5q12.1) cnvs correlated to 'AGE'.
Table 1. Get Full Table Overview of the association between significant copy number variation of 6 regions and 7 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, one significant finding detected.
Clinical Features |
Time to Death |
AGE | GENDER |
KARNOFSKY PERFORMANCE SCORE |
PATHOLOGY T |
PATHOLOGY N |
PATHOLOGICSPREAD(M) | ||
nCNV (%) | nWild-Type | logrank test | t-test | Fisher's exact test | t-test | Fisher's exact test | Fisher's exact test | Fisher's exact test | |
Del Peak 5(5q12 1) | 5 (7%) | 70 |
0.116 (1.00) |
0.000898 (0.0287) |
0.627 (1.00) |
0.0166 (0.482) |
0.311 (1.00) |
0.038 (1.00) |
|
Del Peak 1(1p36 31) | 14 (19%) | 61 |
0.334 (1.00) |
0.826 (1.00) |
1 (1.00) |
0.416 (1.00) |
0.262 (1.00) |
1 (1.00) |
0.0604 (1.00) |
Del Peak 2(2q37 2) | 3 (4%) | 72 |
0.0228 (0.639) |
0.135 (1.00) |
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Del Peak 3(4q32 1) | 5 (7%) | 70 |
0.762 (1.00) |
0.567 (1.00) |
0.627 (1.00) |
0.677 (1.00) |
1 (1.00) |
||
Del Peak 4(4q32 1) | 5 (7%) | 70 |
0.762 (1.00) |
0.567 (1.00) |
0.627 (1.00) |
0.677 (1.00) |
1 (1.00) |
||
Del Peak 6(9p21 3) | 11 (15%) | 64 |
0.0105 (0.326) |
0.44 (1.00) |
0.0119 (0.356) |
0.416 (1.00) |
0.157 (1.00) |
0.67 (1.00) |
0.0963 (1.00) |
P value = 0.000898 (t-test), Q value = 0.029
Table S1. Gene #5: 'Del Peak 5(5q12.1) mutation analysis' versus Clinical Feature #2: 'AGE'
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 72 | 60.3 (12.4) |
DEL PEAK 5(5Q12.1) MUTATED | 4 | 36.5 (5.8) |
DEL PEAK 5(5Q12.1) WILD-TYPE | 68 | 61.7 (11.2) |
Figure S1. Get High-res Image Gene #5: 'Del Peak 5(5q12.1) mutation analysis' versus Clinical Feature #2: 'AGE'
![](D5V2.png)
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Copy number data file = All Lesions File (all_lesions.conf_##.txt, where ## is the confidence level). The all lesions file is from GISTIC pipeline and summarizes the results from the GISTIC run. It contains data about the significant regions of amplification and deletion as well as which samples are amplified or deleted in each of these regions. The identified regions are listed down the first column, and the samples are listed across the first row, starting in column 10.
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Clinical data file = KIRP.clin.merged.picked.txt
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Number of patients = 75
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Number of copy number variation regions = 6
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Number of selected clinical features = 7
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Exclude regions that fewer than K tumors have alterations, K = 3
For survival clinical features, the Kaplan-Meier survival curves of tumors with and without gene cnvs 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 cnvs 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.
This is an experimental feature. The full results of the analysis summarized in this report can be downloaded from the TCGA Data Coordination Center.