Correlation between copy number variations of arm-level result and selected clinical features
Glioblastoma Multiforme (Primary solid tumor)
15 January 2014  |  analyses__2014_01_15
Maintainer Information
Citation Information
doi:10.7908/C11834WK
Maintained by TCGA GDAC Team (Broad Institute/MD Anderson Cancer Center/Harvard Medical School)
Cite as Broad Institute TCGA Genome Data Analysis Center (2014): Correlation between copy number variations of arm-level result and selected clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C11834WK
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 80 arm-level events and 6 clinical features across 553 patients, 11 significant findings detected with Q value < 0.25.

  • 7p gain cnv correlated to 'Time to Death' and 'AGE'.

  • 7q gain cnv correlated to 'Time to Death' and 'AGE'.

  • 10p gain cnv correlated to 'KARNOFSKY.PERFORMANCE.SCORE'.

  • 20p gain cnv correlated to 'AGE'.

  • 20q gain cnv correlated to 'AGE'.

  • 10p loss cnv correlated to 'Time to Death' and 'AGE'.

  • 10q loss cnv correlated to 'Time to Death' and 'AGE'.

Results
Overview of the results

Table 1.  Get Full Table Overview of the association between significant copy number variation of 80 arm-level events and 6 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 11 significant findings detected.

Clinical
Features 		Time
to
Death 		AGE GENDER KARNOFSKY
PERFORMANCE
SCORE 		HISTOLOGICAL
TYPE 		RADIATIONS
RADIATION
REGIMENINDICATION
nCNV (%) nWild-Type logrank test t-test Fisher's exact test t-test Fisher's exact test Fisher's exact test
7p gain 449 (81%) 104 9.02e-05
(0.0426) 		1.45e-06
(0.000691) 		1
(1.00) 		0.574
(1.00) 		0.0104
(1.00) 		0.159
(1.00)
7q gain 453 (82%) 100 0.000226
(0.106) 		7.13e-06
(0.00339) 		0.43
(1.00) 		0.766
(1.00) 		0.00729
(1.00) 		0.188
(1.00)
10p loss 461 (83%) 92 2.48e-05
(0.0118) 		1.41e-07
(6.76e-05) 		0.199
(1.00) 		0.175
(1.00) 		0.00117
(0.547) 		0.805
(1.00)
10q loss 472 (85%) 81 6.88e-05
(0.0326) 		1.16e-06
(0.000553) 		0.462
(1.00) 		0.0059
(1.00) 		0.0202
(1.00) 		0.796
(1.00)
10p gain 12 (2%) 541 0.00435
(1.00) 		0.0026
(1.00) 		0.0712
(1.00) 		0.00032
(0.15) 		0.467
(1.00) 		1
(1.00)
20p gain 214 (39%) 339 0.679
(1.00) 		3.69e-05
(0.0175) 		0.327
(1.00) 		0.403
(1.00) 		0.549
(1.00) 		0.572
(1.00)
20q gain 212 (38%) 341 0.965
(1.00) 		0.000177
(0.0833) 		0.283
(1.00) 		0.527
(1.00) 		0.522
(1.00) 		0.51
(1.00)
1p gain 81 (15%) 472 0.167
(1.00) 		0.564
(1.00) 		0.624
(1.00) 		0.347
(1.00) 		0.372
(1.00) 		0.515
(1.00)
1q gain 87 (16%) 466 0.452
(1.00) 		0.838
(1.00) 		0.404
(1.00) 		0.374
(1.00) 		0.444
(1.00) 		0.528
(1.00)
2p gain 36 (7%) 517 0.618
(1.00) 		0.906
(1.00) 		0.112
(1.00) 		0.6
(1.00) 		0.664
(1.00) 		0.714
(1.00)
2q gain 35 (6%) 518 0.504
(1.00) 		0.637
(1.00) 		0.285
(1.00) 		0.45
(1.00) 		0.651
(1.00) 		1
(1.00)
3p gain 56 (10%) 497 0.927
(1.00) 		0.0177
(1.00) 		0.471
(1.00) 		0.644
(1.00) 		0.771
(1.00) 		0.879
(1.00)
3q gain 62 (11%) 491 0.826
(1.00) 		0.092
(1.00) 		0.493
(1.00) 		0.549
(1.00) 		0.696
(1.00) 		0.773
(1.00)
4p gain 35 (6%) 518 0.959
(1.00) 		0.236
(1.00) 		0.722
(1.00) 		0.0834
(1.00) 		1
(1.00) 		0.574
(1.00)
4q gain 33 (6%) 520 0.688
(1.00) 		0.51
(1.00) 		0.277
(1.00) 		0.146
(1.00) 		1
(1.00) 		0.248
(1.00)
5p gain 47 (8%) 506 0.855
(1.00) 		0.572
(1.00) 		0.118
(1.00) 		0.199
(1.00) 		0.0816
(1.00) 		0.87
(1.00)
5q gain 39 (7%) 514 0.709
(1.00) 		0.5
(1.00) 		0.0625
(1.00) 		0.704
(1.00) 		0.168
(1.00) 		0.722
(1.00)
6p gain 23 (4%) 530 0.48
(1.00) 		0.571
(1.00) 		0.514
(1.00) 		0.543
(1.00) 		1
(1.00) 		0.174
(1.00)
6q gain 22 (4%) 531 0.417
(1.00) 		0.3
(1.00) 		0.827
(1.00) 		0.489
(1.00) 		1
(1.00) 		0.486
(1.00)
8p gain 51 (9%) 502 0.708
(1.00) 		0.464
(1.00) 		0.652
(1.00) 		0.798
(1.00) 		0.645
(1.00) 		0.751
(1.00)
8q gain 58 (10%) 495 0.56
(1.00) 		0.136
(1.00) 		0.396
(1.00) 		0.918
(1.00) 		0.679
(1.00) 		1
(1.00)
9p gain 47 (8%) 506 0.554
(1.00) 		0.848
(1.00) 		0.165
(1.00) 		0.881
(1.00) 		0.514
(1.00) 		0.624
(1.00)
9q gain 71 (13%) 482 0.636
(1.00) 		0.945
(1.00) 		0.121
(1.00) 		0.69
(1.00) 		0.656
(1.00) 		0.891
(1.00)
10q gain 3 (1%) 550 0.454
(1.00) 		0.907
(1.00) 		0.565
(1.00) 		1
(1.00) 		0.227
(1.00)
11p gain 18 (3%) 535 0.467
(1.00) 		0.524
(1.00) 		0.635
(1.00) 		0.316
(1.00) 		1
(1.00) 		0.605
(1.00)
11q gain 15 (3%) 538 0.161
(1.00) 		0.074
(1.00) 		0.179
(1.00) 		0.0605
(1.00) 		0.546
(1.00) 		0.165
(1.00)
12p gain 57 (10%) 496 0.746
(1.00) 		0.181
(1.00) 		0.477
(1.00) 		0.417
(1.00) 		1
(1.00) 		0.762
(1.00)
12q gain 47 (8%) 506 0.973
(1.00) 		0.578
(1.00) 		0.28
(1.00) 		0.657
(1.00) 		0.436
(1.00) 		0.742
(1.00)
13q gain 9 (2%) 544 0.702
(1.00) 		0.0191
(1.00) 		0.165
(1.00) 		0.0966
(1.00) 		1
(1.00) 		0.143
(1.00)
14q gain 22 (4%) 531 0.229
(1.00) 		0.141
(1.00) 		0.512
(1.00) 		0.41
(1.00) 		0.0163
(1.00) 		0.639
(1.00)
15q gain 24 (4%) 529 0.46
(1.00) 		0.969
(1.00) 		0.528
(1.00) 		0.131
(1.00) 		0.346
(1.00) 		0.117
(1.00)
16p gain 37 (7%) 516 0.027
(1.00) 		0.584
(1.00) 		0.296
(1.00) 		0.699
(1.00) 		1
(1.00) 		0.0446
(1.00)
16q gain 36 (7%) 517 0.105
(1.00) 		0.528
(1.00) 		0.597
(1.00) 		0.984
(1.00) 		1
(1.00) 		0.0624
(1.00)
17p gain 45 (8%) 508 0.403
(1.00) 		0.153
(1.00) 		0.153
(1.00) 		0.7
(1.00) 		0.853
(1.00) 		0.503
(1.00)
17q gain 56 (10%) 497 0.0742
(1.00) 		0.0573
(1.00) 		0.392
(1.00) 		0.763
(1.00) 		0.884
(1.00) 		0.446
(1.00)
18p gain 57 (10%) 496 0.674
(1.00) 		0.778
(1.00) 		0.67
(1.00) 		0.282
(1.00) 		0.278
(1.00) 		1
(1.00)
18q gain 56 (10%) 497 0.535
(1.00) 		0.573
(1.00) 		0.313
(1.00) 		0.253
(1.00) 		0.272
(1.00) 		0.762
(1.00)
19p gain 216 (39%) 337 0.36
(1.00) 		0.663
(1.00) 		0.789
(1.00) 		0.81
(1.00) 		0.351
(1.00) 		0.778
(1.00)
19q gain 190 (34%) 363 0.454
(1.00) 		0.213
(1.00) 		0.583
(1.00) 		0.901
(1.00) 		0.811
(1.00) 		0.561
(1.00)
21q gain 60 (11%) 493 0.491
(1.00) 		0.0397
(1.00) 		1
(1.00) 		0.167
(1.00) 		0.115
(1.00) 		1
(1.00)
22q gain 34 (6%) 519 0.374
(1.00) 		0.687
(1.00) 		1
(1.00) 		0.446
(1.00) 		0.799
(1.00) 		0.85
(1.00)
xq gain 16 (3%) 537 0.976
(1.00) 		0.32
(1.00) 		1
(1.00) 		0.371
(1.00) 		0.192
(1.00) 		0.104
(1.00)
1p loss 15 (3%) 538 0.299
(1.00) 		0.0288
(1.00) 		0.424
(1.00) 		0.887
(1.00) 		0.546
(1.00) 		0.413
(1.00)
1q loss 14 (3%) 539 0.476
(1.00) 		0.00333
(1.00) 		1
(1.00) 		0.204
(1.00) 		1
(1.00) 		0.381
(1.00)
2p loss 30 (5%) 523 0.908
(1.00) 		0.359
(1.00) 		0.0551
(1.00) 		0.902
(1.00) 		1
(1.00) 		0.155
(1.00)
2q loss 30 (5%) 523 0.742
(1.00) 		0.607
(1.00) 		0.125
(1.00) 		0.819
(1.00) 		0.579
(1.00) 		0.0672
(1.00)
3p loss 38 (7%) 515 0.26
(1.00) 		0.0373
(1.00) 		0.734
(1.00) 		0.767
(1.00) 		0.552
(1.00) 		0.0442
(1.00)
3q loss 32 (6%) 521 0.704
(1.00) 		0.42
(1.00) 		0.456
(1.00) 		0.908
(1.00) 		1
(1.00) 		0.326
(1.00)
4p loss 52 (9%) 501 0.614
(1.00) 		0.475
(1.00) 		0.233
(1.00) 		0.449
(1.00) 		0.302
(1.00) 		0.637
(1.00)
4q loss 53 (10%) 500 0.229
(1.00) 		0.187
(1.00) 		0.883
(1.00) 		0.188
(1.00) 		0.766
(1.00) 		0.756
(1.00)
5p loss 42 (8%) 511 0.0463
(1.00) 		0.342
(1.00) 		1
(1.00) 		0.811
(1.00) 		1
(1.00) 		0.0379
(1.00)
5q loss 43 (8%) 510 0.0912
(1.00) 		0.312
(1.00) 		1
(1.00) 		0.972
(1.00) 		0.592
(1.00) 		0.17
(1.00)
6p loss 83 (15%) 470 0.0119
(1.00) 		0.451
(1.00) 		0.626
(1.00) 		0.529
(1.00) 		0.347
(1.00) 		0.797
(1.00)
6q loss 119 (22%) 434 0.387
(1.00) 		0.72
(1.00) 		0.291
(1.00) 		0.392
(1.00) 		0.206
(1.00) 		0.738
(1.00)
7p loss 8 (1%) 545 0.372
(1.00) 		0.153
(1.00) 		1
(1.00) 		0.628
(1.00) 		1
(1.00) 		0.445
(1.00)
7q loss 6 (1%) 547 0.544
(1.00) 		0.0995
(1.00) 		1
(1.00) 		0.22
(1.00) 		1
(1.00) 		0.672
(1.00)
8p loss 58 (10%) 495 0.628
(1.00) 		0.189
(1.00) 		0.157
(1.00) 		0.789
(1.00) 		0.886
(1.00) 		0.653
(1.00)
8q loss 42 (8%) 511 0.23
(1.00) 		0.0748
(1.00) 		0.418
(1.00) 		0.508
(1.00) 		0.839
(1.00) 		1
(1.00)
9p loss 190 (34%) 363 0.32
(1.00) 		0.568
(1.00) 		0.583
(1.00) 		0.975
(1.00) 		0.856
(1.00) 		0.498
(1.00)
9q loss 85 (15%) 468 0.388
(1.00) 		0.558
(1.00) 		0.28
(1.00) 		0.517
(1.00) 		0.914
(1.00) 		0.611
(1.00)
11p loss 95 (17%) 458 0.159
(1.00) 		0.889
(1.00) 		0.0508
(1.00) 		0.59
(1.00) 		0.404
(1.00) 		0.543
(1.00)
11q loss 89 (16%) 464 0.865
(1.00) 		0.158
(1.00) 		0.407
(1.00) 		0.981
(1.00) 		1
(1.00) 		0.263
(1.00)
12p loss 59 (11%) 494 0.976
(1.00) 		0.632
(1.00) 		0.4
(1.00) 		0.655
(1.00) 		0.886
(1.00) 		0.554
(1.00)
12q loss 57 (10%) 496 0.866
(1.00) 		0.639
(1.00) 		0.567
(1.00) 		0.498
(1.00) 		0.886
(1.00) 		0.881
(1.00)
13q loss 180 (33%) 373 0.965
(1.00) 		0.772
(1.00) 		0.853
(1.00) 		0.655
(1.00) 		0.687
(1.00) 		0.556
(1.00)
14q loss 140 (25%) 413 0.759
(1.00) 		0.965
(1.00) 		0.484
(1.00) 		0.494
(1.00) 		0.11
(1.00) 		0.673
(1.00)
15q loss 99 (18%) 454 0.729
(1.00) 		0.167
(1.00) 		0.498
(1.00) 		0.425
(1.00) 		0.286
(1.00) 		0.0925
(1.00)
16p loss 62 (11%) 491 0.0888
(1.00) 		0.491
(1.00) 		0.783
(1.00) 		0.994
(1.00) 		0.235
(1.00) 		0.0574
(1.00)
16q loss 80 (14%) 473 0.0407
(1.00) 		0.756
(1.00) 		1
(1.00) 		0.744
(1.00) 		0.368
(1.00) 		0.0363
(1.00)
17p loss 61 (11%) 492 0.873
(1.00) 		0.474
(1.00) 		0.271
(1.00) 		0.88
(1.00) 		0.887
(1.00) 		0.143
(1.00)
17q loss 40 (7%) 513 0.903
(1.00) 		0.448
(1.00) 		0.503
(1.00) 		0.552
(1.00) 		0.829
(1.00) 		0.0216
(1.00)
18p loss 67 (12%) 486 0.179
(1.00) 		0.822
(1.00) 		0.594
(1.00) 		0.475
(1.00) 		0.798
(1.00) 		0.889
(1.00)
18q loss 60 (11%) 493 0.237
(1.00) 		0.972
(1.00) 		0.89
(1.00) 		0.191
(1.00) 		0.886
(1.00) 		0.304
(1.00)
19p loss 26 (5%) 527 0.628
(1.00) 		0.54
(1.00) 		0.838
(1.00) 		0.795
(1.00) 		0.515
(1.00) 		0.668
(1.00)
19q loss 34 (6%) 519 0.628
(1.00) 		0.552
(1.00) 		1
(1.00) 		0.79
(1.00) 		0.277
(1.00) 		0.85
(1.00)
20p loss 18 (3%) 535 0.901
(1.00) 		0.273
(1.00) 		0.219
(1.00) 		0.714
(1.00) 		1
(1.00) 		0.8
(1.00)
20q loss 16 (3%) 537 0.807
(1.00) 		0.656
(1.00) 		0.197
(1.00) 		0.846
(1.00) 		1
(1.00) 		0.588
(1.00)
21q loss 40 (7%) 513 0.919
(1.00) 		0.639
(1.00) 		0.503
(1.00) 		0.175
(1.00) 		1
(1.00) 		0.376
(1.00)
22q loss 172 (31%) 381 0.46
(1.00) 		0.153
(1.00) 		1
(1.00) 		0.495
(1.00) 		0.85
(1.00) 		1
(1.00)
xq loss 102 (18%) 451 0.114
(1.00) 		0.373
(1.00) 		0.575
(1.00) 		0.35
(1.00) 		0.297
(1.00) 		0.477
(1.00)
'7p gain' versus 'Time to Death'

P value = 9.02e-05 (logrank test), Q value = 0.043

Table S1.  Gene #13: '7p gain' versus Clinical Feature #1: 'Time to Death'

nPatients nDeath Duration Range (Median), Month
ALL 553 445 0.1 - 127.6 (9.9)
7P GAIN MUTATED 449 368 0.1 - 127.6 (9.6)
7P GAIN WILD-TYPE 104 77 0.2 - 108.8 (13.0)

Figure S1.  Get High-res Image Gene #13: '7p gain' versus Clinical Feature #1: 'Time to Death'

'7p gain' versus 'AGE'

P value = 1.45e-06 (t-test), Q value = 0.00069

Table S2.  Gene #13: '7p gain' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 553 57.8 (14.4)
7P GAIN MUTATED 449 59.7 (12.4)
7P GAIN WILD-TYPE 104 49.7 (19.2)

Figure S2.  Get High-res Image Gene #13: '7p gain' versus Clinical Feature #2: 'AGE'

'7q gain' versus 'Time to Death'

P value = 0.000226 (logrank test), Q value = 0.11

Table S3.  Gene #14: '7q gain' versus Clinical Feature #1: 'Time to Death'

nPatients nDeath Duration Range (Median), Month
ALL 553 445 0.1 - 127.6 (9.9)
7Q GAIN MUTATED 453 369 0.1 - 127.6 (9.6)
7Q GAIN WILD-TYPE 100 76 0.2 - 108.8 (13.8)

Figure S3.  Get High-res Image Gene #14: '7q gain' versus Clinical Feature #1: 'Time to Death'

'7q gain' versus 'AGE'

P value = 7.13e-06 (t-test), Q value = 0.0034

Table S4.  Gene #14: '7q gain' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 553 57.8 (14.4)
7Q GAIN MUTATED 453 59.6 (12.2)
7Q GAIN WILD-TYPE 100 49.8 (20.1)

Figure S4.  Get High-res Image Gene #14: '7q gain' versus Clinical Feature #2: 'AGE'

'10p gain' versus 'KARNOFSKY.PERFORMANCE.SCORE'

P value = 0.00032 (t-test), Q value = 0.15

Table S5.  Gene #19: '10p gain' versus Clinical Feature #4: 'KARNOFSKY.PERFORMANCE.SCORE'

nPatients Mean (Std.Dev)
ALL 408 77.4 (14.7)
10P GAIN MUTATED 11 80.0 (0.0)
10P GAIN WILD-TYPE 397 77.3 (14.9)

Figure S5.  Get High-res Image Gene #19: '10p gain' versus Clinical Feature #4: 'KARNOFSKY.PERFORMANCE.SCORE'

'20p gain' versus 'AGE'

P value = 3.69e-05 (t-test), Q value = 0.017

Table S6.  Gene #36: '20p gain' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 553 57.8 (14.4)
20P GAIN MUTATED 214 60.9 (13.0)
20P GAIN WILD-TYPE 339 55.9 (15.0)

Figure S6.  Get High-res Image Gene #36: '20p gain' versus Clinical Feature #2: 'AGE'

'20q gain' versus 'AGE'

P value = 0.000177 (t-test), Q value = 0.083

Table S7.  Gene #37: '20q gain' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 553 57.8 (14.4)
20Q GAIN MUTATED 212 60.7 (13.3)
20Q GAIN WILD-TYPE 341 56.1 (14.9)

Figure S7.  Get High-res Image Gene #37: '20q gain' versus Clinical Feature #2: 'AGE'

'10p loss' versus 'Time to Death'

P value = 2.48e-05 (logrank test), Q value = 0.012

Table S8.  Gene #59: '10p loss' versus Clinical Feature #1: 'Time to Death'

nPatients nDeath Duration Range (Median), Month
ALL 553 445 0.1 - 127.6 (9.9)
10P LOSS MUTATED 461 376 0.1 - 127.6 (9.8)
10P LOSS WILD-TYPE 92 69 0.2 - 108.8 (12.5)

Figure S8.  Get High-res Image Gene #59: '10p loss' versus Clinical Feature #1: 'Time to Death'

'10p loss' versus 'AGE'

P value = 1.41e-07 (t-test), Q value = 6.8e-05

Table S9.  Gene #59: '10p loss' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 553 57.8 (14.4)
10P LOSS MUTATED 461 59.7 (12.5)
10P LOSS WILD-TYPE 92 48.2 (18.9)

Figure S9.  Get High-res Image Gene #59: '10p loss' versus Clinical Feature #2: 'AGE'

'10q loss' versus 'Time to Death'

P value = 6.88e-05 (logrank test), Q value = 0.033

Table S10.  Gene #60: '10q loss' versus Clinical Feature #1: 'Time to Death'

nPatients nDeath Duration Range (Median), Month
ALL 553 445 0.1 - 127.6 (9.9)
10Q LOSS MUTATED 472 385 0.1 - 127.6 (9.8)
10Q LOSS WILD-TYPE 81 60 0.2 - 108.8 (12.0)

Figure S10.  Get High-res Image Gene #60: '10q loss' versus Clinical Feature #1: 'Time to Death'

'10q loss' versus 'AGE'

P value = 1.16e-06 (t-test), Q value = 0.00055

Table S11.  Gene #60: '10q loss' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 553 57.8 (14.4)
10Q LOSS MUTATED 472 59.5 (12.9)
10Q LOSS WILD-TYPE 81 48.3 (18.6)

Figure S11.  Get High-res Image Gene #60: '10q loss' versus Clinical Feature #2: 'AGE'

Methods & Data
Input

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

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

  • Number of patients = 553

  • Number of significantly arm-level cnvs = 80

  • Number of selected clinical features = 6

  • 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

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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