Correlation between copy number variation genes (focal events) and selected clinical features
Sarcoma (Primary solid tumor)
23 September 2013 | analyses__2013_09_23
Maintainer Information
Citation Information
doi:10.7908/C1JD4V4T
Maintained by TCGA GDAC Team (Broad Institute/MD Anderson Cancer Center/Harvard Medical School)
Cite as Broad Institute TCGA Genome Data Analysis Center (2013): Correlation between copy number variation genes (focal events) and selected clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1JD4V4T
Overview
Introduction

This pipeline computes the correlation between significant copy number variation (cnv focal) genes and selected clinical features.

Summary

Testing the association between copy number variation 48 focal events and 3 clinical features across 57 patients, 2 significant findings detected with Q value < 0.25.

- AMP PEAK 4(6P21.1) MUTATION ANALYSIS cnv correlated to 'AGE'.

- AMP PEAK 8(12P12.1) MUTATION ANALYSIS cnv correlated to 'AGE'.

Results
Overview of the results

Table 1. Get Full Table Overview of the association between significant copy number variation of 48 focal events and 3 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 2 significant findings detected.

|  | Clinical Features | Time to Death | AGE | GENDER
| nCNV (%) | nWild-Type | logrank test | t-test | Fisher's exact test
AMP PEAK 4(6P21 1) MUTATION ANALYSIS | 14 (25%) | 43 | 0.192 (1.00) | 0.000262 (0.0378) | 0.55 (1.00)
AMP PEAK 8(12P12 1) MUTATION ANALYSIS | 14 (25%) | 43 | 0.121 (1.00) | 0.00108 (0.155) | 1 (1.00)
AMP PEAK 1(1P32 1) MUTATION ANALYSIS | 17 (30%) | 40 | 0.0546 (1.00) | 0.459 (1.00) | 1 (1.00)
AMP PEAK 2(1Q24 3) MUTATION ANALYSIS | 21 (37%) | 36 | 0.379 (1.00) | 0.641 (1.00) | 0.787 (1.00)
AMP PEAK 3(5P15 33) MUTATION ANALYSIS | 24 (42%) | 33 | 0.0756 (1.00) | 0.0214 (1.00) | 1 (1.00)
AMP PEAK 5(6Q24 3) MUTATION ANALYSIS | 22 (39%) | 35 | 0.713 (1.00) | 0.176 (1.00) | 0.417 (1.00)
AMP PEAK 6(7P21 3) MUTATION ANALYSIS | 20 (35%) | 37 | 0.755 (1.00) | 0.103 (1.00) | 0.585 (1.00)
AMP PEAK 7(11Q22 2) MUTATION ANALYSIS | 11 (19%) | 46 | 0.356 (1.00) | 0.639 (1.00) | 1 (1.00)
AMP PEAK 9(12Q15) MUTATION ANALYSIS | 32 (56%) | 25 | 0.948 (1.00) | 0.503 (1.00) | 0.0033 (0.466)
AMP PEAK 10(17P11 2) MUTATION ANALYSIS | 15 (26%) | 42 | 0.0112 (1.00) | 0.042 (1.00) | 0.77 (1.00)
AMP PEAK 11(19P13 2) MUTATION ANALYSIS | 19 (33%) | 38 | 0.932 (1.00) | 0.225 (1.00) | 0.263 (1.00)
AMP PEAK 12(19Q12) MUTATION ANALYSIS | 20 (35%) | 37 | 0.0478 (1.00) | 0.00535 (0.738) | 1 (1.00)
AMP PEAK 13(XQ21 1) MUTATION ANALYSIS | 11 (19%) | 46 | 0.205 (1.00) | 0.147 (1.00) | 1 (1.00)
DEL PEAK 1(1P36 32) MUTATION ANALYSIS | 18 (32%) | 39 | 0.0226 (1.00) | 0.0613 (1.00) | 0.0239 (1.00)
DEL PEAK 2(1P32 3) MUTATION ANALYSIS | 12 (21%) | 45 | 0.053 (1.00) | 0.828 (1.00) | 0.0563 (1.00)
DEL PEAK 3(1Q44) MUTATION ANALYSIS | 19 (33%) | 38 | 0.76 (1.00) | 0.164 (1.00) | 0.576 (1.00)
DEL PEAK 4(2P25 3) MUTATION ANALYSIS | 15 (26%) | 42 | 0.988 (1.00) | 0.0303 (1.00) | 0.141 (1.00)
DEL PEAK 5(2Q37 3) MUTATION ANALYSIS | 22 (39%) | 35 | 0.859 (1.00) | 0.478 (1.00) | 0.592 (1.00)
DEL PEAK 6(3P21 31) MUTATION ANALYSIS | 16 (28%) | 41 | 0.178 (1.00) | 0.00213 (0.303) | 0.248 (1.00)
DEL PEAK 7(3Q25 2) MUTATION ANALYSIS | 17 (30%) | 40 | 0.851 (1.00) | 0.0862 (1.00) | 0.777 (1.00)
DEL PEAK 8(4Q34 3) MUTATION ANALYSIS | 26 (46%) | 31 | 0.558 (1.00) | 0.314 (1.00) | 0.0343 (1.00)
DEL PEAK 9(6P24 3) MUTATION ANALYSIS | 17 (30%) | 40 | 0.57 (1.00) | 0.383 (1.00) | 0.395 (1.00)
DEL PEAK 10(6Q15) MUTATION ANALYSIS | 9 (16%) | 48 | 0.785 (1.00) | 0.0244 (1.00) | 1 (1.00)
DEL PEAK 11(7Q36 3) MUTATION ANALYSIS | 13 (23%) | 44 | 0.595 (1.00) | 0.0779 (1.00) | 1 (1.00)
DEL PEAK 12(8P23 3) MUTATION ANALYSIS | 17 (30%) | 40 | 0.716 (1.00) | 0.531 (1.00) | 0.565 (1.00)
DEL PEAK 13(9P24 3) MUTATION ANALYSIS | 24 (42%) | 33 | 0.479 (1.00) | 0.00351 (0.488) | 1 (1.00)
DEL PEAK 14(9P21 3) MUTATION ANALYSIS | 29 (51%) | 28 | 0.675 (1.00) | 0.0781 (1.00) | 0.793 (1.00)
DEL PEAK 15(9Q34 3) MUTATION ANALYSIS | 14 (25%) | 43 | 0.156 (1.00) | 0.0277 (1.00) | 0.07 (1.00)
DEL PEAK 16(10P15 3) MUTATION ANALYSIS | 26 (46%) | 31 | 0.559 (1.00) | 0.0293 (1.00) | 0.113 (1.00)
DEL PEAK 17(10Q23 31) MUTATION ANALYSIS | 26 (46%) | 31 | 0.288 (1.00) | 0.161 (1.00) | 0.00791 (1.00)
DEL PEAK 18(11P15 5) MUTATION ANALYSIS | 26 (46%) | 31 | 0.247 (1.00) | 0.00349 (0.488) | 0.792 (1.00)
DEL PEAK 19(11Q22 3) MUTATION ANALYSIS | 22 (39%) | 35 | 0.178 (1.00) | 0.0159 (1.00) | 0.592 (1.00)
DEL PEAK 20(11Q24 3) MUTATION ANALYSIS | 26 (46%) | 31 | 0.0966 (1.00) | 0.0114 (1.00) | 1 (1.00)
DEL PEAK 21(12P13 1) MUTATION ANALYSIS | 16 (28%) | 41 | 0.98 (1.00) | 0.439 (1.00) | 0.141 (1.00)
DEL PEAK 22(13Q14 2) MUTATION ANALYSIS | 38 (67%) | 19 | 0.334 (1.00) | 0.0595 (1.00) | 0.092 (1.00)
DEL PEAK 23(14Q24 1) MUTATION ANALYSIS | 27 (47%) | 30 | 0.158 (1.00) | 0.246 (1.00) | 0.189 (1.00)
DEL PEAK 24(16Q12 1) MUTATION ANALYSIS | 31 (54%) | 26 | 0.184 (1.00) | 0.159 (1.00) | 0.186 (1.00)
DEL PEAK 25(17P13 1) MUTATION ANALYSIS | 15 (26%) | 42 | 0.438 (1.00) | 0.948 (1.00) | 0.0379 (1.00)
DEL PEAK 26(17Q25 3) MUTATION ANALYSIS | 16 (28%) | 41 | 0.524 (1.00) | 0.4 (1.00) | 1 (1.00)
DEL PEAK 27(18P11 32) MUTATION ANALYSIS | 19 (33%) | 38 | 0.948 (1.00) | 0.747 (1.00) | 0.167 (1.00)
DEL PEAK 28(18Q23) MUTATION ANALYSIS | 21 (37%) | 36 | 0.922 (1.00) | 0.0214 (1.00) | 0.787 (1.00)
DEL PEAK 29(19P13 3) MUTATION ANALYSIS | 15 (26%) | 42 | 0.837 (1.00) | 0.873 (1.00) | 0.00705 (0.966)
DEL PEAK 30(19Q13 33) MUTATION ANALYSIS | 17 (30%) | 40 | 0.344 (1.00) | 0.976 (1.00) | 0.777 (1.00)
DEL PEAK 31(21Q22 3) MUTATION ANALYSIS | 21 (37%) | 36 | 0.63 (1.00) | 0.0152 (1.00) | 0.787 (1.00)
DEL PEAK 32(22Q13 32) MUTATION ANALYSIS | 26 (46%) | 31 | 0.407 (1.00) | 0.515 (1.00) | 0.0343 (1.00)
DEL PEAK 33(XP21 1) MUTATION ANALYSIS | 12 (21%) | 45 | 0.435 (1.00) | 0.74 (1.00) | 0.53 (1.00)
DEL PEAK 34(XQ21 1) MUTATION ANALYSIS | 23 (40%) | 34 | 0.109 (1.00) | 0.757 (1.00) | 0.182 (1.00)
DEL PEAK 35(XQ27 1) MUTATION ANALYSIS | 25 (44%) | 32 | 0.872 (1.00) | 0.986 (1.00) | 0.186 (1.00)

'AMP PEAK 4(6P21.1) MUTATION STATUS' versus 'AGE'

P value = 0.000262 (t-test), Q value = 0.038

Table S1. Gene #4: 'AMP PEAK 4(6P21.1) MUTATION STATUS' versus Clinical Feature #2: 'AGE'

| nPatients | Mean (Std.Dev)
--- | --- | ---
ALL | 57 | 63.4 (11.5)
AMP PEAK 4(6P21.1) MUTATED | 14 | 71.5 (7.5)
AMP PEAK 4(6P21.1) WILD-TYPE | 43 | 60.7 (11.4)

Figure S1. Get High-res Image Gene #4: 'AMP PEAK 4(6P21.1) MUTATION STATUS' versus Clinical Feature #2: 'AGE'

'AMP PEAK 8(12P12.1) MUTATION STATUS' versus 'AGE'

P value = 0.00108 (t-test), Q value = 0.15

Table S2. Gene #8: 'AMP PEAK 8(12P12.1) MUTATION STATUS' versus Clinical Feature #2: 'AGE'

| nPatients | Mean (Std.Dev)
--- | --- | ---
ALL | 57 | 63.4 (11.5)
AMP PEAK 8(12P12.1) MUTATED | 14 | 71.2 (8.6)
AMP PEAK 8(12P12.1) WILD-TYPE | 43 | 60.8 (11.3)

Figure S2. Get High-res Image Gene #8: 'AMP PEAK 8(12P12.1) MUTATION STATUS' versus Clinical Feature #2: 'AGE'

Methods & Data
Input

- Copy number data file = transformed.cor.cli.txt

- Clinical data file = SARC-TP.clin.merged.picked.txt

- Number of patients = 57

- Number of significantly focal cnvs = 48

- Number of selected clinical features = 3

- Exclude genes that fewer than K tumors have mutations, K = 3

Survival analysis

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

Student's t-test analysis

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

Fisher's exact test

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

Q value calculation

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.

Download Results

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.

- Analysis Results (MD5 checksum)

- Auxiliary Data (MD5 checksum)

- MAGE-TAB File (MD5 checksum)

References
[1] Bland and Altman, Statistics notes: The logrank test, BMJ 328(7447):1073 (2004)
[2] Lehmann and Romano, Testing Statistical Hypotheses (3E ed.), New York: Springer. ISBN 0387988645 (2005)
[3] Fisher, R.A., On the interpretation of chi-square from contingency tables, and the calculation of P, Journal of the Royal Statistical Society 85(1):87-94 (1922)
[4] Benjamini and Hochberg, Controlling the false discovery rate: a practical and powerful approach to multiple testing, Journal of the Royal Statistical Society Series B 59:289-300 (1995)
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