Correlation between copy number variations of arm-level result and selected clinical features
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 65 arm-level events and 7 clinical features across 22 patients, 3 significant findings detected with Q value < 0.25.

  • 19p gain cnv correlated to 'AGE'.

  • 16p loss cnv correlated to 'AGE'.

  • 16q loss cnv correlated to 'AGE'.

Results
Overview of the results

Table 1.  Get Full Table Overview of the association between significant copy number variation of 65 arm-level events and 7 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 3 significant findings detected.

Clinical
Features 		Time
to
Death 		AGE NEOPLASM
DISEASESTAGE 		PATHOLOGY
T
STAGE 		PATHOLOGY
N
STAGE 		GENDER NUMBERPACKYEARSSMOKED
nCNV (%) nWild-Type logrank test t-test Chi-square test Fisher's exact test Fisher's exact test Fisher's exact test t-test
19p gain 4 (18%) 18 0.218
(1.00) 		0.000351
(0.153) 		0.186
(1.00) 		1
(1.00) 		0.27
(1.00) 		1
(1.00) 		0.501
(1.00)
16p loss 3 (14%) 19 0.575
(1.00) 		3.15e-06
(0.00138) 		0.568
(1.00) 		0.75
(1.00) 		0.766
(1.00) 		0.371
(1.00)
16q loss 3 (14%) 19 0.575
(1.00) 		3.15e-06
(0.00138) 		0.568
(1.00) 		0.75
(1.00) 		0.766
(1.00) 		0.371
(1.00)
1p gain 4 (18%) 18 0.961
(1.00) 		0.0876
(1.00) 		0.31
(1.00) 		0.032
(1.00) 		0.478
(1.00) 		0.47
(1.00) 		0.475
(1.00)
1q gain 10 (45%) 12 0.623
(1.00) 		0.0582
(1.00) 		0.467
(1.00) 		0.453
(1.00) 		0.733
(1.00) 		1
(1.00) 		0.467
(1.00)
2p gain 8 (36%) 14 0.753
(1.00) 		0.301
(1.00) 		0.0687
(1.00) 		0.0127
(1.00) 		1
(1.00) 		0.527
(1.00) 		0.128
(1.00)
2q gain 4 (18%) 18 0.979
(1.00) 		0.47
(1.00) 		0.244
(1.00) 		1
(1.00) 		1
(1.00) 		0.47
(1.00)
3p gain 3 (14%) 19 0.5
(1.00) 		0.691
(1.00) 		0.0225
(1.00) 		0.0526
(1.00) 		0.558
(1.00) 		0.371
(1.00)
3q gain 11 (50%) 11 0.447
(1.00) 		0.0987
(1.00) 		0.543
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		0.186
(1.00)
5p gain 7 (32%) 15 0.474
(1.00) 		0.805
(1.00) 		0.194
(1.00) 		0.702
(1.00) 		0.296
(1.00) 		0.227
(1.00) 		0.263
(1.00)
6p gain 3 (14%) 19 0.187
(1.00) 		0.646
(1.00) 		0.568
(1.00) 		0.75
(1.00) 		0.766
(1.00) 		0.0377
(1.00)
7p gain 14 (64%) 8 0.356
(1.00) 		0.434
(1.00) 		0.52
(1.00) 		0.725
(1.00) 		0.0496
(1.00) 		1
(1.00) 		0.749
(1.00)
7q gain 8 (36%) 14 0.666
(1.00) 		0.884
(1.00) 		0.183
(1.00) 		0.312
(1.00) 		0.853
(1.00) 		1
(1.00) 		0.35
(1.00)
8p gain 8 (36%) 14 0.321
(1.00) 		0.156
(1.00) 		0.22
(1.00) 		0.097
(1.00) 		1
(1.00) 		0.527
(1.00) 		0.805
(1.00)
8q gain 12 (55%) 10 0.444
(1.00) 		0.215
(1.00) 		0.561
(1.00) 		0.743
(1.00) 		0.733
(1.00) 		1
(1.00) 		0.133
(1.00)
9q gain 6 (27%) 16 0.187
(1.00) 		0.76
(1.00) 		0.0236
(1.00) 		0.231
(1.00) 		0.247
(1.00) 		0.532
(1.00) 		0.0933
(1.00)
11p gain 5 (23%) 17 0.355
(1.00) 		0.334
(1.00) 		0.908
(1.00) 		0.518
(1.00) 		1
(1.00) 		1
(1.00) 		0.551
(1.00)
11q gain 5 (23%) 17 0.482
(1.00) 		0.117
(1.00) 		0.944
(1.00) 		1
(1.00) 		0.809
(1.00) 		1
(1.00) 		0.752
(1.00)
12p gain 6 (27%) 16 0.286
(1.00) 		0.473
(1.00) 		0.452
(1.00) 		0.814
(1.00) 		0.325
(1.00) 		1
(1.00) 		0.309
(1.00)
12q gain 6 (27%) 16 0.286
(1.00) 		0.702
(1.00) 		0.349
(1.00) 		0.814
(1.00) 		0.685
(1.00) 		1
(1.00) 		0.309
(1.00)
13q gain 3 (14%) 19 0.00305
(1.00) 		0.785
(1.00) 		0.243
(1.00) 		0.55
(1.00) 		1
(1.00) 		0.371
(1.00) 		0.215
(1.00)
14q gain 6 (27%) 16 0.261
(1.00) 		0.416
(1.00) 		0.826
(1.00) 		0.69
(1.00) 		0.202
(1.00) 		0.532
(1.00) 		0.805
(1.00)
15q gain 3 (14%) 19 0.108
(1.00) 		0.969
(1.00) 		0.719
(1.00) 		0.75
(1.00) 		1
(1.00) 		0.371
(1.00)
16p gain 6 (27%) 16 0.688
(1.00) 		0.357
(1.00) 		0.05
(1.00) 		0.231
(1.00) 		0.16
(1.00) 		0.532
(1.00) 		0.753
(1.00)
16q gain 5 (23%) 17 0.688
(1.00) 		0.154
(1.00) 		0.0338
(1.00) 		0.518
(1.00) 		0.0341
(1.00) 		1
(1.00) 		0.751
(1.00)
17p gain 5 (23%) 17 0.43
(1.00) 		0.583
(1.00) 		0.779
(1.00) 		1
(1.00) 		0.145
(1.00) 		1
(1.00) 		0.378
(1.00)
17q gain 8 (36%) 14 0.843
(1.00) 		0.798
(1.00) 		0.559
(1.00) 		0.725
(1.00) 		0.131
(1.00) 		0.273
(1.00) 		0.144
(1.00)
18p gain 7 (32%) 15 0.137
(1.00) 		0.652
(1.00) 		0.339
(1.00) 		0.152
(1.00) 		0.842
(1.00) 		0.227
(1.00) 		0.797
(1.00)
18q gain 3 (14%) 19 0.108
(1.00) 		0.968
(1.00) 		0.568
(1.00) 		0.75
(1.00) 		0.766
(1.00) 		0.371
(1.00)
19q gain 6 (27%) 16 0.394
(1.00) 		0.00924
(1.00) 		0.256
(1.00) 		0.587
(1.00) 		0.0955
(1.00) 		0.532
(1.00) 		0.501
(1.00)
20p gain 15 (68%) 7 0.168
(1.00) 		0.764
(1.00) 		0.385
(1.00) 		0.58
(1.00) 		0.586
(1.00) 		0.523
(1.00) 		0.931
(1.00)
20q gain 16 (73%) 6 0.25
(1.00) 		0.208
(1.00) 		0.328
(1.00) 		0.587
(1.00) 		0.247
(1.00) 		0.532
(1.00) 		0.846
(1.00)
22q gain 5 (23%) 17 0.583
(1.00) 		0.0585
(1.00) 		0.202
(1.00) 		1
(1.00) 		0.00281
(1.00) 		1
(1.00) 		0.523
(1.00)
xq gain 5 (23%) 17 0.0384
(1.00) 		0.74
(1.00) 		0.846
(1.00) 		0.649
(1.00) 		0.809
(1.00) 		1
(1.00)
1p loss 3 (14%) 19 0.187
(1.00) 		0.717
(1.00) 		0.757
(1.00) 		1
(1.00) 		0.766
(1.00) 		1
(1.00) 		0.601
(1.00)
2q loss 4 (18%) 18 0.881
(1.00) 		0.919
(1.00) 		0.319
(1.00) 		0.789
(1.00) 		0.478
(1.00) 		0.47
(1.00)
3p loss 11 (50%) 11 0.16
(1.00) 		0.284
(1.00) 		0.358
(1.00) 		0.0373
(1.00) 		1
(1.00) 		1
(1.00) 		0.301
(1.00)
3q loss 3 (14%) 19 0.473
(1.00) 		0.605
(1.00) 		1
(1.00) 		0.558
(1.00) 		1
(1.00) 		0.396
(1.00)
4p loss 13 (59%) 9 0.0804
(1.00) 		0.641
(1.00) 		0.529
(1.00) 		0.0944
(1.00) 		0.146
(1.00) 		0.544
(1.00) 		0.322
(1.00)
4q loss 11 (50%) 11 0.0804
(1.00) 		0.567
(1.00) 		0.148
(1.00) 		0.183
(1.00) 		0.0898
(1.00) 		1
(1.00) 		0.186
(1.00)
5p loss 7 (32%) 15 0.0943
(1.00) 		0.149
(1.00) 		0.291
(1.00) 		1
(1.00) 		0.0213
(1.00) 		1
(1.00) 		0.418
(1.00)
5q loss 12 (55%) 10 0.434
(1.00) 		0.969
(1.00) 		0.561
(1.00) 		0.743
(1.00) 		0.624
(1.00) 		0.221
(1.00) 		0.452
(1.00)
6p loss 3 (14%) 19 0.146
(1.00) 		1
(1.00) 		0.506
(1.00) 		0.4
(1.00) 		0.558
(1.00) 		1
(1.00)
7p loss 3 (14%) 19 0.71
(1.00) 		0.506
(1.00) 		0.4
(1.00) 		0.0701
(1.00) 		0.371
(1.00) 		0.293
(1.00)
7q loss 3 (14%) 19 0.0408
(1.00) 		0.145
(1.00) 		0.257
(1.00) 		0.0701
(1.00) 		1
(1.00) 		0.198
(1.00)
8p loss 9 (41%) 13 0.906
(1.00) 		0.505
(1.00) 		0.24
(1.00) 		0.00438
(1.00) 		0.44
(1.00) 		0.24
(1.00) 		0.446
(1.00)
9p loss 13 (59%) 9 0.843
(1.00) 		0.109
(1.00) 		0.434
(1.00) 		0.861
(1.00) 		0.626
(1.00) 		0.24
(1.00) 		0.735
(1.00)
9q loss 9 (41%) 13 0.889
(1.00) 		0.48
(1.00) 		0.529
(1.00) 		1
(1.00) 		0.858
(1.00) 		0.0545
(1.00) 		0.0536
(1.00)
10p loss 7 (32%) 15 0.315
(1.00) 		0.668
(1.00) 		0.383
(1.00) 		0.288
(1.00) 		0.586
(1.00) 		1
(1.00) 		0.43
(1.00)
10q loss 8 (36%) 14 0.979
(1.00) 		0.678
(1.00) 		0.29
(1.00) 		0.156
(1.00) 		0.853
(1.00) 		1
(1.00) 		0.665
(1.00)
11p loss 5 (23%) 17 0.5
(1.00) 		0.42
(1.00) 		0.202
(1.00) 		0.158
(1.00) 		0.44
(1.00) 		1
(1.00)
11q loss 6 (27%) 16 0.818
(1.00) 		0.802
(1.00) 		0.113
(1.00) 		0.587
(1.00) 		0.16
(1.00) 		1
(1.00) 		0.614
(1.00)
12p loss 5 (23%) 17 0.275
(1.00) 		0.2
(1.00) 		0.48
(1.00) 		0.342
(1.00) 		0.809
(1.00) 		0.117
(1.00) 		0.215
(1.00)
12q loss 4 (18%) 18 0.719
(1.00) 		0.386
(1.00) 		0.244
(1.00) 		0.789
(1.00) 		1
(1.00) 		0.0727
(1.00)
13q loss 11 (50%) 11 0.313
(1.00) 		0.704
(1.00) 		0.406
(1.00) 		0.0831
(1.00) 		0.18
(1.00) 		1
(1.00) 		0.322
(1.00)
14q loss 4 (18%) 18 0.979
(1.00) 		0.85
(1.00) 		0.244
(1.00) 		1
(1.00) 		0.139
(1.00) 		0.47
(1.00)
15q loss 5 (23%) 17 0.137
(1.00) 		0.865
(1.00) 		0.351
(1.00) 		1
(1.00) 		0.272
(1.00) 		1
(1.00) 		0.904
(1.00)
17p loss 8 (36%) 14 0.409
(1.00) 		0.937
(1.00) 		0.0687
(1.00) 		1
(1.00) 		0.131
(1.00) 		1
(1.00) 		0.834
(1.00)
18p loss 6 (27%) 16 0.515
(1.00) 		0.517
(1.00) 		0.495
(1.00) 		0.814
(1.00) 		1
(1.00) 		0.532
(1.00) 		0.119
(1.00)
18q loss 10 (45%) 12 0.569
(1.00) 		0.172
(1.00) 		0.421
(1.00) 		0.0487
(1.00) 		0.624
(1.00) 		0.221
(1.00) 		0.45
(1.00)
19p loss 9 (41%) 13 0.262
(1.00) 		0.397
(1.00) 		0.884
(1.00) 		1
(1.00) 		0.332
(1.00) 		0.544
(1.00) 		0.921
(1.00)
19q loss 6 (27%) 16 0.356
(1.00) 		0.425
(1.00) 		0.826
(1.00) 		1
(1.00) 		0.403
(1.00) 		0.169
(1.00) 		0.921
(1.00)
21q loss 13 (59%) 9 0.843
(1.00) 		0.461
(1.00) 		0.619
(1.00) 		1
(1.00) 		0.525
(1.00) 		0.24
(1.00) 		0.0403
(1.00)
22q loss 9 (41%) 13 0.428
(1.00) 		0.47
(1.00) 		0.619
(1.00) 		0.232
(1.00) 		0.525
(1.00) 		0.544
(1.00) 		0.278
(1.00)
xq loss 6 (27%) 16 0.915
(1.00) 		0.845
(1.00) 		0.0897
(1.00) 		0.0798
(1.00) 		0.247
(1.00) 		1
(1.00) 		0.422
(1.00)
'19p gain' versus 'AGE'

P value = 0.000351 (t-test), Q value = 0.15

Table S1.  Gene #27: '19p gain' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 22 66.0 (10.8)
19P GAIN MUTATED 4 78.5 (4.1)
19P GAIN WILD-TYPE 18 63.2 (9.8)

Figure S1.  Get High-res Image Gene #27: '19p gain' versus Clinical Feature #2: 'AGE'

'16p loss' versus 'AGE'

P value = 3.15e-06 (t-test), Q value = 0.0014

Table S2.  Gene #56: '16p loss' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 22 66.0 (10.8)
16P LOSS MUTATED 3 83.3 (2.5)
16P LOSS WILD-TYPE 19 63.3 (8.8)

Figure S2.  Get High-res Image Gene #56: '16p loss' versus Clinical Feature #2: 'AGE'

'16q loss' versus 'AGE'

P value = 3.15e-06 (t-test), Q value = 0.0014

Table S3.  Gene #57: '16q loss' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 22 66.0 (10.8)
16Q LOSS MUTATED 3 83.3 (2.5)
16Q LOSS WILD-TYPE 19 63.3 (8.8)

Figure S3.  Get High-res Image Gene #57: '16q loss' versus Clinical Feature #2: 'AGE'

Methods & Data
Input

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

  • Clinical data file = ESCA-TP.merged_data.txt

  • Number of patients = 22

  • Number of significantly arm-level cnvs = 65

  • 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

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

Chi-square test

For multi-class clinical features (nominal or ordinal), Chi-square tests (Greenwood and Nikulin 1996) were used to estimate the P values using the 'chisq.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.

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] Greenwood and Nikulin, A guide to chi-squared testing, Wiley, New York. ISBN 047155779X (1996)
[4] 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)
[5] 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)
Made with Nozzle