Correlation between copy number variations of arm-level result and selected clinical features
Lymphoid Neoplasm Diffuse Large B-cell Lymphoma (Primary solid tumor)
28 January 2016  |  analyses__2016_01_28
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 (2016): Correlation between copy number variations of arm-level result and selected clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C10001GR
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 8 clinical features across 48 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 8 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
TUMOR
TISSUE
SITE
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 Fisher's exact test
9p gain 7 (15%) 41 0.945
(1.00)
0.156
(0.834)
0.413
(1.00)
0.687
(1.00)
0.0566
(0.589)
0.00041
(0.171)
0.492
(1.00)
0.345
(1.00)
1q gain 6 (12%) 42 0.286
(0.995)
0.374
(1.00)
0.245
(0.989)
1
(1.00)
0.571
(1.00)
1
(1.00)
0.14
(0.834)
1
(1.00)
2p gain 6 (12%) 42 0.986
(1.00)
0.0952
(0.732)
1
(1.00)
0.214
(0.989)
0.108
(0.732)
0.701
(1.00)
0.156
(0.834)
2q gain 6 (12%) 42 0.986
(1.00)
0.0952
(0.732)
1
(1.00)
0.214
(0.989)
0.108
(0.732)
0.705
(1.00)
0.156
(0.834)
3p gain 10 (21%) 38 0.098
(0.732)
1
(1.00)
0.562
(1.00)
0.735
(1.00)
0.63
(1.00)
0.786
(1.00)
0.585
(1.00)
0.241
(0.989)
3q gain 13 (27%) 35 0.0508
(0.589)
0.585
(1.00)
0.565
(1.00)
0.746
(1.00)
0.377
(1.00)
1
(1.00)
0.651
(1.00)
0.263
(0.989)
5p gain 7 (15%) 41 0.607
(1.00)
0.32
(1.00)
1
(1.00)
0.0566
(0.589)
0.0124
(0.481)
0.736
(1.00)
0.0552
(0.589)
5q gain 6 (12%) 42 0.981
(1.00)
0.156
(0.834)
0.674
(1.00)
0.0348
(0.589)
0.0071
(0.376)
1
(1.00)
0.0278
(0.589)
6p gain 6 (12%) 42 0.275
(0.989)
0.852
(1.00)
0.199
(0.988)
1
(1.00)
0.635
(1.00)
0.703
(1.00)
0.631
(1.00)
6q gain 4 (8%) 44 0.423
(1.00)
0.926
(1.00)
0.114
(0.732)
1
(1.00)
1
(1.00)
0.223
(0.989)
1
(1.00)
7p gain 14 (29%) 34 0.145
(0.834)
0.901
(1.00)
0.562
(1.00)
1
(1.00)
1
(1.00)
0.253
(0.989)
0.822
(1.00)
0.726
(1.00)
7q gain 12 (25%) 36 0.292
(0.995)
0.347
(1.00)
0.561
(1.00)
1
(1.00)
1
(1.00)
0.493
(1.00)
0.617
(1.00)
1
(1.00)
8p gain 7 (15%) 41 0.774
(1.00)
0.0393
(0.589)
0.429
(1.00)
0.276
(0.989)
0.146
(0.834)
0.343
(1.00)
0.00724
(0.376)
8q gain 8 (17%) 40 0.672
(1.00)
0.0278
(0.589)
0.71
(1.00)
0.0841
(0.732)
0.0199
(0.562)
0.273
(0.989)
0.00162
(0.312)
9q gain 7 (15%) 41 0.898
(1.00)
0.136
(0.834)
0.412
(1.00)
0.223
(0.989)
0.0566
(0.589)
0.0117
(0.481)
0.49
(1.00)
0.345
(1.00)
10p gain 4 (8%) 44 0.402
(1.00)
0.926
(1.00)
0.114
(0.732)
1
(1.00)
1
(1.00)
0.664
(1.00)
1
(1.00)
10q gain 4 (8%) 44 0.423
(1.00)
0.444
(1.00)
0.614
(1.00)
0.488
(1.00)
1
(1.00)
0.663
(1.00)
0.257
(0.989)
11p gain 9 (19%) 39 0.747
(1.00)
0.711
(1.00)
0.793
(1.00)
0.0276
(0.589)
1
(1.00)
0.0633
(0.642)
0.554
(1.00)
0.0321
(0.589)
11q gain 13 (27%) 35 0.819
(1.00)
0.493
(1.00)
0.783
(1.00)
0.101
(0.732)
0.655
(1.00)
0.221
(0.989)
0.81
(1.00)
0.263
(0.989)
12p gain 7 (15%) 41 0.216
(0.989)
0.357
(1.00)
0.972
(1.00)
1
(1.00)
0.276
(0.989)
0.0532
(0.589)
1
(1.00)
0.345
(1.00)
12q gain 9 (19%) 39 0.0546
(0.589)
0.588
(1.00)
0.253
(0.989)
0.713
(1.00)
0.605
(1.00)
0.0203
(0.562)
0.769
(1.00)
0.199
(0.988)
13q gain 5 (10%) 43 0.647
(1.00)
0.344
(1.00)
1
(1.00)
1
(1.00)
1
(1.00)
0.422
(1.00)
0.587
(1.00)
16p gain 7 (15%) 41 0.281
(0.989)
0.77
(1.00)
0.928
(1.00)
1
(1.00)
1
(1.00)
0.265
(0.989)
1
(1.00)
1
(1.00)
16q gain 7 (15%) 41 0.0742
(0.732)
0.953
(1.00)
0.616
(1.00)
0.687
(1.00)
1
(1.00)
0.266
(0.989)
1
(1.00)
1
(1.00)
17q gain 3 (6%) 45 0.196
(0.988)
0.241
(0.989)
0.239
(0.989)
1
(1.00)
0.383
(1.00)
0.11
(0.732)
0.563
(1.00)
18p gain 13 (27%) 35 0.0492
(0.589)
0.291
(0.995)
0.648
(1.00)
0.746
(1.00)
0.377
(1.00)
0.803
(1.00)
0.0851
(0.732)
0.71
(1.00)
18q gain 13 (27%) 35 0.0492
(0.589)
0.291
(0.995)
0.644
(1.00)
0.746
(1.00)
0.377
(1.00)
0.804
(1.00)
0.0836
(0.732)
0.71
(1.00)
19p gain 3 (6%) 45 0.445
(1.00)
0.0844
(0.732)
1
(1.00)
0.391
(1.00)
1
(1.00)
1
(1.00)
0.15
(0.834)
19q gain 3 (6%) 45 0.445
(1.00)
0.0844
(0.732)
1
(1.00)
0.391
(1.00)
1
(1.00)
1
(1.00)
0.15
(0.834)
20p gain 5 (10%) 43 0.745
(1.00)
0.636
(1.00)
0.0538
(0.589)
1
(1.00)
0.563
(1.00)
0.425
(1.00)
0.587
(1.00)
20q gain 4 (8%) 44 0.56
(1.00)
0.255
(0.989)
0.114
(0.732)
1
(1.00)
0.478
(1.00)
0.66
(1.00)
0.257
(0.989)
21q gain 10 (21%) 38 0.977
(1.00)
0.328
(1.00)
0.48
(1.00)
0.307
(1.00)
0.63
(1.00)
0.279
(0.989)
0.779
(1.00)
0.695
(1.00)
xp gain 6 (12%) 42 0.926
(1.00)
0.64
(1.00)
0.305
(1.00)
1
(1.00)
1
(1.00)
0.0172
(0.562)
1
(1.00)
0.0278
(0.589)
xq gain 7 (15%) 41 0.935
(1.00)
0.248
(0.989)
0.305
(1.00)
1
(1.00)
0.573
(1.00)
0.0285
(0.589)
1
(1.00)
0.0552
(0.589)
1p loss 3 (6%) 45 0.445
(1.00)
0.36
(1.00)
0.587
(1.00)
1
(1.00)
0.193
(0.988)
1
(1.00)
1
(1.00)
3p loss 4 (8%) 44 0.502
(1.00)
0.455
(1.00)
0.614
(1.00)
0.488
(1.00)
0.0949
(0.732)
0.342
(1.00)
0.0432
(0.589)
3q loss 3 (6%) 45 0.561
(1.00)
0.624
(1.00)
1
(1.00)
0.391
(1.00)
0.0521
(0.589)
0.319
(1.00)
0.0127
(0.481)
4p loss 3 (6%) 45 0.502
(1.00)
0.327
(1.00)
0.239
(0.989)
1
(1.00)
1
(1.00)
1
(1.00)
1
(1.00)
4q loss 4 (8%) 44 0.49
(1.00)
0.455
(1.00)
0.114
(0.732)
1
(1.00)
1
(1.00)
0.662
(1.00)
1
(1.00)
6q loss 7 (15%) 41 0.851
(1.00)
0.826
(1.00)
0.56
(1.00)
1
(1.00)
0.573
(1.00)
0.0839
(0.732)
0.337
(1.00)
0.0552
(0.589)
8p loss 8 (17%) 40 0.929
(1.00)
0.782
(1.00)
0.26
(0.989)
1
(1.00)
0.333
(1.00)
0.741
(1.00)
0.394
(1.00)
8q loss 4 (8%) 44 0.402
(1.00)
0.14
(0.834)
0.614
(1.00)
1
(1.00)
0.259
(0.989)
1
(1.00)
0.257
(0.989)
13q loss 3 (6%) 45 0.527
(1.00)
0.898
(1.00)
1
(1.00)
0.391
(1.00)
0.0519
(0.589)
0.32
(1.00)
0.15
(0.834)
15q loss 7 (15%) 41 0.22
(0.989)
0.737
(1.00)
0.106
(0.732)
0.573
(1.00)
1
(1.00)
1
(1.00)
0.662
(1.00)
16q loss 4 (8%) 44 0.435
(1.00)
0.94
(1.00)
0.114
(0.732)
1
(1.00)
1
(1.00)
0.223
(0.989)
0.56
(1.00)
17p loss 9 (19%) 39 0.186
(0.97)
0.843
(1.00)
0.891
(1.00)
0.151
(0.834)
0.605
(1.00)
0.0197
(0.562)
0.552
(1.00)
0.00424
(0.312)
17q loss 4 (8%) 44 0.47
(1.00)
0.49
(1.00)
1
(1.00)
0.488
(1.00)
0.00402
(0.312)
0.346
(1.00)
0.00254
(0.312)
18p loss 5 (10%) 43 0.602
(1.00)
0.853
(1.00)
0.88
(1.00)
0.649
(1.00)
1
(1.00)
0.326
(1.00)
1
(1.00)
0.587
(1.00)
18q loss 5 (10%) 43 0.768
(1.00)
0.166
(0.875)
1
(1.00)
1
(1.00)
0.328
(1.00)
0.675
(1.00)
0.0918
(0.732)
22q loss 3 (6%) 45 0.502
(1.00)
0.782
(1.00)
0.239
(0.989)
1
(1.00)
1
(1.00)
0.11
(0.732)
0.563
(1.00)
xp loss 5 (10%) 43 0.0498
(0.589)
0.447
(1.00)
0.0538
(0.589)
1
(1.00)
1
(1.00)
0.424
(1.00)
1
(1.00)
xq loss 4 (8%) 44 0.0045
(0.312)
1
(1.00)
0.114
(0.732)
1
(1.00)
1
(1.00)
0.22
(0.989)
0.56
(1.00)
'9p gain' versus 'HISTOLOGICAL_TYPE'

P value = 0.00041 (Fisher's exact test), Q value = 0.17

Table S1.  Gene #14: '9p gain' versus Clinical Feature #6: '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 41 3 4
9P GAIN MUTATED 3 0 4
9P GAIN WILD-TYPE 38 3 0

Figure S1.  Get High-res Image Gene #14: '9p gain' versus Clinical Feature #6: '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/22516374/transformed.cor.cli.txt

  • Clinical data file = /xchip/cga/gdac-prod/tcga-gdac/jobResults/Append_Data/DLBC-TP/22506396/DLBC-TP.merged_data.txt

  • Number of patients = 48

  • Number of significantly arm-level cnvs = 52

  • Number of selected clinical features = 8

  • 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)