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

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.

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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