Correlation between copy number variations of arm-level result and selected clinical features
Lymphoid Neoplasm Diffuse Large B-cell Lymphoma (Primary solid tumor)
21 August 2015  |  analyses__2015_08_21
Maintainer Information
Citation Information
doi:10.7908/C1CZ36B7
Maintained by TCGA GDAC Team (Broad Institute/MD Anderson Cancer Center/Harvard Medical School)
Cite as Broad Institute TCGA Genome Data Analysis Center (2015): Correlation between copy number variations of arm-level result and selected clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1CZ36B7
Overview
Introduction

This pipeline computes the correlation between significant arm-level copy number variations (cnvs) and selected clinical features.

Summary

Testing the association between copy number variation 52 arm-level events and 7 clinical features across 47 patients, one significant finding detected with Q value < 0.25.

  • 9p gain cnv correlated to 'HISTOLOGICAL_TYPE'.

Results
Overview of the results

Table 1.  Get Full Table Overview of the association between significant copy number variation of 52 arm-level events 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 		YEARS
TO
BIRTH 		GENDER RADIATION
THERAPY 		HISTOLOGICAL
TYPE 		RACE ETHNICITY
nCNV (%) nWild-Type logrank test Wilcoxon-test Fisher's exact test Fisher's exact test Fisher's exact test Fisher's exact test Fisher's exact test
9p gain 7 (15%) 40 0.945
(1.00) 		0.16
(0.776) 		0.684
(1.00) 		0.0601
(0.561) 		0.00056
(0.204) 		0.496
(1.00) 		0.35
(0.917)
1q gain 5 (11%) 42 0.286
(0.867) 		0.277
(0.867) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		0.232
(0.867) 		1
(1.00)
2p gain 6 (13%) 41 0.986
(1.00) 		0.1
(0.668) 		1
(1.00) 		0.221
(0.867) 		0.112
(0.668) 		0.71
(1.00) 		0.164
(0.776)
2q gain 6 (13%) 41 0.986
(1.00) 		0.1
(0.668) 		1
(1.00) 		0.221
(0.867) 		0.111
(0.668) 		0.71
(1.00) 		0.164
(0.776)
3p gain 10 (21%) 37 0.098
(0.668) 		0.979
(1.00) 		1
(1.00) 		0.636
(1.00) 		0.789
(1.00) 		0.59
(1.00) 		0.251
(0.867)
3q gain 13 (28%) 34 0.0508
(0.561) 		0.568
(1.00) 		0.746
(1.00) 		0.385
(0.971) 		1
(1.00) 		0.812
(1.00) 		0.269
(0.867)
5p gain 7 (15%) 40 0.607
(1.00) 		0.317
(0.915) 		1
(1.00) 		0.0601
(0.561) 		0.0134
(0.486) 		0.735
(1.00) 		0.0595
(0.561)
5q gain 6 (13%) 41 0.981
(1.00) 		0.156
(0.776) 		0.678
(1.00) 		0.037
(0.561) 		0.00732
(0.365) 		1
(1.00) 		0.0301
(0.561)
6p gain 6 (13%) 41 0.275
(0.867) 		0.823
(1.00) 		0.204
(0.867) 		1
(1.00) 		0.642
(1.00) 		0.707
(1.00) 		0.637
(1.00)
6q gain 4 (9%) 43 0.423
(0.993) 		0.954
(1.00) 		0.117
(0.668) 		1
(1.00) 		1
(1.00) 		0.343
(0.917) 		1
(1.00)
7p gain 15 (32%) 32 0.11
(0.668) 		0.723
(1.00) 		0.758
(1.00) 		1
(1.00) 		0.219
(0.867) 		1
(1.00) 		0.481
(1.00)
7q gain 13 (28%) 34 0.231
(0.867) 		0.695
(1.00) 		0.746
(1.00) 		1
(1.00) 		0.315
(0.915) 		0.81
(1.00) 		0.713
(1.00)
8p gain 7 (15%) 40 0.774
(1.00) 		0.0391
(0.561) 		0.436
(0.993) 		0.286
(0.867) 		0.153
(0.776) 		0.337
(0.917) 		0.00802
(0.365)
8q gain 8 (17%) 39 0.672
(1.00) 		0.0282
(0.561) 		0.715
(1.00) 		0.089
(0.668) 		0.0213
(0.516) 		0.272
(0.867) 		0.00184
(0.291)
9q gain 7 (15%) 40 0.898
(1.00) 		0.139
(0.776) 		0.217
(0.867) 		0.0601
(0.561) 		0.0122
(0.486) 		0.496
(1.00) 		0.35
(0.917)
10p gain 4 (9%) 43 0.402
(0.971) 		0.954
(1.00) 		0.117
(0.668) 		1
(1.00) 		1
(1.00) 		0.669
(1.00) 		1
(1.00)
10q gain 4 (9%) 43 0.423
(0.993) 		0.457
(1.00) 		0.617
(1.00) 		0.496
(1.00) 		1
(1.00) 		0.669
(1.00) 		0.266
(0.867)
11p gain 9 (19%) 38 0.747
(1.00) 		0.695
(1.00) 		0.0305
(0.561) 		1
(1.00) 		0.0652
(0.593) 		0.553
(1.00) 		0.0352
(0.561)
11q gain 13 (28%) 34 0.819
(1.00) 		0.475
(1.00) 		0.102
(0.668) 		0.654
(1.00) 		0.234
(0.867) 		0.653
(1.00) 		0.269
(0.867)
12p gain 7 (15%) 40 0.216
(0.867) 		0.354
(0.92) 		1
(1.00) 		0.286
(0.867) 		0.0565
(0.561) 		1
(1.00) 		0.35
(0.917)
12q gain 9 (19%) 38 0.0546
(0.561) 		0.57
(1.00) 		0.486
(1.00) 		0.609
(1.00) 		0.0207
(0.516) 		0.777
(1.00) 		0.205
(0.867)
13q gain 5 (11%) 42 0.647
(1.00) 		0.342
(0.917) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		0.431
(0.993) 		0.59
(1.00)
16p gain 7 (15%) 40 0.281
(0.867) 		0.754
(1.00) 		1
(1.00) 		1
(1.00) 		0.274
(0.867) 		1
(1.00) 		1
(1.00)
16q gain 7 (15%) 40 0.0742
(0.659) 		0.964
(1.00) 		0.684
(1.00) 		1
(1.00) 		0.276
(0.867) 		1
(1.00) 		1
(1.00)
17q gain 3 (6%) 44 0.196
(0.867) 		0.24
(0.867) 		0.242
(0.867) 		1
(1.00) 		0.39
(0.971) 		0.114
(0.668) 		0.56
(1.00)
18p gain 13 (28%) 34 0.0492
(0.561) 		0.295
(0.88) 		0.746
(1.00) 		0.385
(0.971) 		0.806
(1.00) 		0.114
(0.668) 		0.713
(1.00)
18q gain 14 (30%) 33 0.19
(0.867) 		0.522
(1.00) 		1
(1.00) 		0.658
(1.00) 		0.803
(1.00) 		0.0593
(0.561) 		0.731
(1.00)
19p gain 3 (6%) 44 0.445
(0.993) 		0.0895
(0.668) 		1
(1.00) 		0.398
(0.971) 		1
(1.00) 		1
(1.00) 		0.156
(0.776)
19q gain 3 (6%) 44 0.445
(0.993) 		0.0895
(0.668) 		1
(1.00) 		0.398
(0.971) 		1
(1.00) 		1
(1.00) 		0.156
(0.776)
20p gain 5 (11%) 42 0.745
(1.00) 		0.641
(1.00) 		0.0561
(0.561) 		1
(1.00) 		0.57
(1.00) 		0.434
(0.993) 		0.59
(1.00)
20q gain 4 (9%) 43 0.56
(1.00) 		0.26
(0.867) 		0.117
(0.668) 		1
(1.00) 		0.488
(1.00) 		0.67
(1.00) 		0.266
(0.867)
21q gain 10 (21%) 37 0.977
(1.00) 		0.317
(0.915) 		0.475
(1.00) 		0.636
(1.00) 		0.288
(0.867) 		0.777
(1.00) 		0.7
(1.00)
xp gain 6 (13%) 41 0.926
(1.00) 		0.655
(1.00) 		1
(1.00) 		1
(1.00) 		0.0179
(0.516) 		1
(1.00) 		0.0301
(0.561)
xq gain 6 (13%) 41 0.87
(1.00) 		0.632
(1.00) 		1
(1.00) 		0.57
(1.00) 		0.0187
(0.516) 		0.706
(1.00) 		0.164
(0.776)
1p loss 3 (6%) 44 0.445
(0.993) 		0.384
(0.971) 		0.579
(1.00) 		1
(1.00) 		0.199
(0.867) 		1
(1.00) 		1
(1.00)
3p loss 5 (11%) 42 0.402
(0.971) 		0.262
(0.867) 		1
(1.00) 		1
(1.00) 		0.153
(0.776) 		0.23
(0.867) 		0.0971
(0.668)
3q loss 4 (9%) 43 0.445
(0.993) 		0.35
(0.917) 		1
(1.00) 		0.496
(1.00) 		0.0994
(0.668) 		0.219
(0.867) 		0.0459
(0.561)
4p loss 3 (6%) 44 0.502
(1.00) 		0.349
(0.917) 		0.242
(0.867) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00)
4q loss 4 (9%) 43 0.49
(1.00) 		0.469
(1.00) 		0.117
(0.668) 		1
(1.00) 		1
(1.00) 		0.667
(1.00) 		1
(1.00)
6q loss 7 (15%) 40 0.851
(1.00) 		0.811
(1.00) 		1
(1.00) 		0.573
(1.00) 		0.0873
(0.668) 		0.338
(0.917) 		0.0595
(0.561)
8p loss 8 (17%) 39 0.929
(1.00) 		0.799
(1.00) 		0.269
(0.867) 		1
(1.00) 		0.34
(0.917) 		0.744
(1.00) 		0.403
(0.971)
8q loss 4 (9%) 43 0.402
(0.971) 		0.153
(0.776) 		0.617
(1.00) 		1
(1.00) 		0.266
(0.867) 		1
(1.00) 		0.266
(0.867)
13q loss 3 (6%) 44 0.527
(1.00) 		0.879
(1.00) 		1
(1.00) 		0.398
(0.971) 		0.0536
(0.561) 		0.316
(0.915) 		0.156
(0.776)
15q loss 7 (15%) 40 0.22
(0.867) 		0.765
(1.00) 		0.112
(0.668) 		0.573
(1.00) 		1
(1.00) 		1
(1.00) 		0.659
(1.00)
16q loss 4 (9%) 43 0.435
(0.993) 		0.909
(1.00) 		0.117
(0.668) 		1
(1.00) 		1
(1.00) 		0.343
(0.917) 		0.56
(1.00)
17p loss 9 (19%) 38 0.186
(0.867) 		0.871
(1.00) 		0.16
(0.776) 		0.609
(1.00) 		0.0211
(0.516) 		0.552
(1.00) 		0.0048
(0.291)
17q loss 4 (9%) 43 0.47
(1.00) 		0.504
(1.00) 		1
(1.00) 		0.496
(1.00) 		0.00412
(0.291) 		0.217
(0.867) 		0.00278
(0.291)
18p loss 5 (11%) 42 0.602
(1.00) 		0.863
(1.00) 		0.644
(1.00) 		1
(1.00) 		0.332
(0.917) 		1
(1.00) 		0.59
(1.00)
18q loss 4 (9%) 43 0.418
(0.993) 		0.0327
(0.561) 		0.617
(1.00) 		1
(1.00) 		0.264
(0.867) 		0.215
(0.867) 		0.0459
(0.561)
22q loss 3 (6%) 44 0.502
(1.00) 		0.794
(1.00) 		0.242
(0.867) 		1
(1.00) 		1
(1.00) 		0.113
(0.668) 		0.56
(1.00)
xp loss 5 (11%) 42 0.0498
(0.561) 		0.468
(1.00) 		0.0561
(0.561) 		1
(1.00) 		1
(1.00) 		0.434
(0.993) 		1
(1.00)
xq loss 4 (9%) 43 0.0045
(0.291) 		1
(1.00) 		0.117
(0.668) 		1
(1.00) 		1
(1.00) 		0.347
(0.917) 		0.56
(1.00)
'9p gain' versus 'HISTOLOGICAL_TYPE'

P value = 0.00056 (Fisher's exact test), Q value = 0.2

Table S1.  Gene #14: '9p gain' versus Clinical Feature #5: 'HISTOLOGICAL_TYPE'

nPatients DIFFUSE LARGE B-CELL LYMPHOMA (DLBCL) NOS (ANY ANATOMIC SITE NODAL OR EXTRANODAL) PRIMARY DLBCL OF THE CNS PRIMARY MEDIASTINAL (THYMIC) DLBCL
ALL 40 3 4
9P GAIN MUTATED 3 0 4
9P GAIN WILD-TYPE 37 3 0

Figure S1.  Get High-res Image Gene #14: '9p gain' versus Clinical Feature #5: 'HISTOLOGICAL_TYPE'

Methods & Data
Input

  • Copy number data file = broad_values_by_arm.txt from GISTIC pipeline

  • Processed Copy number data file = /xchip/cga/gdac-prod/tcga-gdac/jobResults/GDAC_Correlate_Genomic_Events_Preprocess/DLBC-TP/19780780/transformed.cor.cli.txt

  • Clinical data file = /xchip/cga/gdac-prod/tcga-gdac/jobResults/Append_Data/DLBC-TP/19775131/DLBC-TP.merged_data.txt

  • Number of patients = 47

  • Number of significantly arm-level cnvs = 52

  • Number of selected clinical features = 7

  • Exclude regions 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

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] 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)
[3] 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)
Copyright © 2015 Broad Institute TCGA GDAC as part of the TCGA Research Network. All rights reserved.
Made with Nozzle