Correlation between copy number variations of arm-level result and selected clinical features
Breast Invasive Carcinoma (Primary solid tumor)
23 September 2013  |  analyses__2013_09_23
Maintainer Information
Citation Information
doi:10.7908/C1FT8JBH
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 variations of arm-level result and selected clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1FT8JBH
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 10 clinical features across 949 patients, 24 significant findings detected with Q value < 0.25.

  • 2P GAIN MUTATION ANALYSIS cnv correlated to 'HISTOLOGICAL.TYPE'.

  • 3Q GAIN MUTATION ANALYSIS cnv correlated to 'HISTOLOGICAL.TYPE'.

  • 6P GAIN MUTATION ANALYSIS cnv correlated to 'HISTOLOGICAL.TYPE'.

  • 6Q GAIN MUTATION ANALYSIS cnv correlated to 'HISTOLOGICAL.TYPE'.

  • 8Q GAIN MUTATION ANALYSIS cnv correlated to 'HISTOLOGICAL.TYPE'.

  • 10P GAIN MUTATION ANALYSIS cnv correlated to 'HISTOLOGICAL.TYPE'.

  • 20P GAIN MUTATION ANALYSIS cnv correlated to 'HISTOLOGICAL.TYPE'.

  • 20Q GAIN MUTATION ANALYSIS cnv correlated to 'HISTOLOGICAL.TYPE'.

  • XQ GAIN MUTATION ANALYSIS cnv correlated to 'HISTOLOGICAL.TYPE'.

  • 4P LOSS MUTATION ANALYSIS cnv correlated to 'HISTOLOGICAL.TYPE'.

  • 4Q LOSS MUTATION ANALYSIS cnv correlated to 'HISTOLOGICAL.TYPE'.

  • 5P LOSS MUTATION ANALYSIS cnv correlated to 'HISTOLOGICAL.TYPE'.

  • 5Q LOSS MUTATION ANALYSIS cnv correlated to 'HISTOLOGICAL.TYPE'.

  • 6Q LOSS MUTATION ANALYSIS cnv correlated to 'AGE'.

  • 8P LOSS MUTATION ANALYSIS cnv correlated to 'HISTOLOGICAL.TYPE'.

  • 9P LOSS MUTATION ANALYSIS cnv correlated to 'PATHOLOGY.T.STAGE' and 'HISTOLOGICAL.TYPE'.

  • 13Q LOSS MUTATION ANALYSIS cnv correlated to 'HISTOLOGICAL.TYPE'.

  • 14Q LOSS MUTATION ANALYSIS cnv correlated to 'HISTOLOGICAL.TYPE'.

  • 16Q LOSS MUTATION ANALYSIS cnv correlated to 'HISTOLOGICAL.TYPE'.

  • 17Q LOSS MUTATION ANALYSIS cnv correlated to 'HISTOLOGICAL.TYPE'.

  • 18P LOSS MUTATION ANALYSIS cnv correlated to 'Time to Death'.

  • 19P LOSS MUTATION ANALYSIS cnv correlated to 'HISTOLOGICAL.TYPE'.

  • 19Q LOSS MUTATION ANALYSIS 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 80 arm-level events and 10 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 24 significant findings detected.

Clinical
Features 		Time
to
Death 		AGE NEOPLASM
DISEASESTAGE 		PATHOLOGY
T
STAGE 		PATHOLOGY
N
STAGE 		PATHOLOGY
M
STAGE 		GENDER HISTOLOGICAL
TYPE 		RADIATIONS
RADIATION
REGIMENINDICATION 		NUMBER
OF
LYMPH
NODES
nCNV (%) nWild-Type logrank test t-test Chi-square test Fisher's exact test Fisher's exact test Fisher's exact test Fisher's exact test Chi-square test Fisher's exact test t-test
9P LOSS MUTATION ANALYSIS 279 (29%) 670 0.0342
(1.00) 		0.479
(1.00) 		0.00203
(1.00) 		0.000149
(0.116) 		0.0305
(1.00) 		0.0448
(1.00) 		0.169
(1.00) 		1.37e-05
(0.0108) 		1
(1.00) 		0.839
(1.00)
2P GAIN MUTATION ANALYSIS 102 (11%) 847 0.469
(1.00) 		0.817
(1.00) 		0.762
(1.00) 		0.727
(1.00) 		0.863
(1.00) 		0.714
(1.00) 		0.612
(1.00) 		4.42e-05
(0.0349) 		0.143
(1.00) 		0.118
(1.00)
3Q GAIN MUTATION ANALYSIS 179 (19%) 770 0.471
(1.00) 		0.357
(1.00) 		0.743
(1.00) 		0.112
(1.00) 		0.782
(1.00) 		0.152
(1.00) 		0.698
(1.00) 		4.36e-05
(0.0345) 		0.211
(1.00) 		0.258
(1.00)
6P GAIN MUTATION ANALYSIS 180 (19%) 769 0.179
(1.00) 		0.792
(1.00) 		0.787
(1.00) 		0.188
(1.00) 		0.446
(1.00) 		0.747
(1.00) 		0.697
(1.00) 		0.000101
(0.0789) 		0.177
(1.00) 		0.786
(1.00)
6Q GAIN MUTATION ANALYSIS 127 (13%) 822 0.118
(1.00) 		0.91
(1.00) 		0.871
(1.00) 		0.134
(1.00) 		0.113
(1.00) 		0.877
(1.00) 		1
(1.00) 		8.11e-05
(0.0639) 		1
(1.00) 		0.799
(1.00)
8Q GAIN MUTATION ANALYSIS 472 (50%) 477 0.589
(1.00) 		0.804
(1.00) 		0.338
(1.00) 		0.775
(1.00) 		0.467
(1.00) 		0.0848
(1.00) 		0.545
(1.00) 		9.55e-06
(0.00759) 		0.0965
(1.00) 		0.886
(1.00)
10P GAIN MUTATION ANALYSIS 186 (20%) 763 0.981
(1.00) 		0.653
(1.00) 		0.121
(1.00) 		0.294
(1.00) 		0.27
(1.00) 		0.4
(1.00) 		0.697
(1.00) 		0.000292
(0.227) 		0.216
(1.00) 		0.567
(1.00)
20P GAIN MUTATION ANALYSIS 350 (37%) 599 0.416
(1.00) 		0.519
(1.00) 		0.534
(1.00) 		0.283
(1.00) 		0.0825
(1.00) 		0.00226
(1.00) 		0.044
(1.00) 		5.1e-07
(0.000407) 		0.0714
(1.00) 		0.658
(1.00)
20Q GAIN MUTATION ANALYSIS 383 (40%) 566 0.423
(1.00) 		0.754
(1.00) 		0.534
(1.00) 		0.0692
(1.00) 		0.102
(1.00) 		0.00557
(1.00) 		0.536
(1.00) 		7.06e-08
(5.63e-05) 		0.19
(1.00) 		0.568
(1.00)
XQ GAIN MUTATION ANALYSIS 138 (15%) 811 0.375
(1.00) 		0.234
(1.00) 		0.449
(1.00) 		0.498
(1.00) 		0.803
(1.00) 		0.0969
(1.00) 		1
(1.00) 		0.000129
(0.101) 		0.0315
(1.00) 		0.761
(1.00)
4P LOSS MUTATION ANALYSIS 299 (32%) 650 0.425
(1.00) 		0.456
(1.00) 		0.478
(1.00) 		0.06
(1.00) 		0.548
(1.00) 		0.65
(1.00) 		1
(1.00) 		6.01e-06
(0.00478) 		0.684
(1.00) 		0.896
(1.00)
4Q LOSS MUTATION ANALYSIS 263 (28%) 686 0.992
(1.00) 		0.973
(1.00) 		0.718
(1.00) 		0.135
(1.00) 		0.6
(1.00) 		0.588
(1.00) 		0.3
(1.00) 		0.000113
(0.0887) 		0.736
(1.00) 		0.701
(1.00)
5P LOSS MUTATION ANALYSIS 125 (13%) 824 0.103
(1.00) 		0.0404
(1.00) 		0.259
(1.00) 		0.0594
(1.00) 		0.917
(1.00) 		0.648
(1.00) 		1
(1.00) 		1.13e-05
(0.00893) 		0.434
(1.00) 		0.308
(1.00)
5Q LOSS MUTATION ANALYSIS 198 (21%) 751 0.23
(1.00) 		0.00325
(1.00) 		0.183
(1.00) 		0.0123
(1.00) 		0.375
(1.00) 		0.534
(1.00) 		0.133
(1.00) 		1.06e-09
(8.48e-07) 		1
(1.00) 		0.0944
(1.00)
6Q LOSS MUTATION ANALYSIS 237 (25%) 712 0.516
(1.00) 		0.000225
(0.175) 		0.953
(1.00) 		0.634
(1.00) 		0.669
(1.00) 		0.0995
(1.00) 		0.466
(1.00) 		0.571
(1.00) 		0.116
(1.00) 		0.48
(1.00)
8P LOSS MUTATION ANALYSIS 358 (38%) 591 0.0989
(1.00) 		0.376
(1.00) 		0.937
(1.00) 		0.292
(1.00) 		0.563
(1.00) 		0.569
(1.00) 		0.751
(1.00) 		9.05e-05
(0.0712) 		0.938
(1.00) 		0.612
(1.00)
13Q LOSS MUTATION ANALYSIS 377 (40%) 572 0.0387
(1.00) 		0.4
(1.00) 		0.696
(1.00) 		0.19
(1.00) 		0.642
(1.00) 		0.91
(1.00) 		0.53
(1.00) 		0.000152
(0.119) 		0.699
(1.00) 		0.087
(1.00)
14Q LOSS MUTATION ANALYSIS 223 (23%) 726 0.0497
(1.00) 		0.524
(1.00) 		0.722
(1.00) 		0.0236
(1.00) 		0.0594
(1.00) 		0.868
(1.00) 		0.467
(1.00) 		6.82e-05
(0.0538) 		0.533
(1.00) 		0.141
(1.00)
16Q LOSS MUTATION ANALYSIS 514 (54%) 435 0.0366
(1.00) 		0.000948
(0.734) 		0.51
(1.00) 		0.77
(1.00) 		0.404
(1.00) 		0.176
(1.00) 		0.2
(1.00) 		1.26e-11
(1.01e-08) 		0.449
(1.00) 		0.236
(1.00)
17Q LOSS MUTATION ANALYSIS 248 (26%) 701 0.992
(1.00) 		0.113
(1.00) 		0.804
(1.00) 		0.622
(1.00) 		0.222
(1.00) 		0.327
(1.00) 		0.0714
(1.00) 		0.000305
(0.237) 		0.264
(1.00) 		0.685
(1.00)
18P LOSS MUTATION ANALYSIS 277 (29%) 672 7.49e-05
(0.059) 		0.0206
(1.00) 		0.122
(1.00) 		0.04
(1.00) 		0.556
(1.00) 		0.892
(1.00) 		0.732
(1.00) 		0.0694
(1.00) 		0.618
(1.00) 		0.254
(1.00)
19P LOSS MUTATION ANALYSIS 163 (17%) 786 0.192
(1.00) 		0.0267
(1.00) 		0.901
(1.00) 		0.699
(1.00) 		0.424
(1.00) 		0.324
(1.00) 		1
(1.00) 		4.04e-05
(0.032) 		0.688
(1.00) 		0.439
(1.00)
19Q LOSS MUTATION ANALYSIS 146 (15%) 803 0.294
(1.00) 		0.411
(1.00) 		0.573
(1.00) 		0.531
(1.00) 		0.211
(1.00) 		0.372
(1.00) 		1
(1.00) 		0.000106
(0.0828) 		0.142
(1.00) 		0.395
(1.00)
1P GAIN MUTATION ANALYSIS 170 (18%) 779 0.379
(1.00) 		0.184
(1.00) 		0.703
(1.00) 		0.094
(1.00) 		0.427
(1.00) 		0.946
(1.00) 		0.697
(1.00) 		0.0692
(1.00) 		0.0101
(1.00) 		0.536
(1.00)
1Q GAIN MUTATION ANALYSIS 604 (64%) 345 0.272
(1.00) 		0.31
(1.00) 		0.114
(1.00) 		0.00166
(1.00) 		0.837
(1.00) 		0.924
(1.00) 		1
(1.00) 		0.0301
(1.00) 		0.307
(1.00) 		0.888
(1.00)
2Q GAIN MUTATION ANALYSIS 58 (6%) 891 0.9
(1.00) 		0.999
(1.00) 		0.82
(1.00) 		0.52
(1.00) 		0.943
(1.00) 		1
(1.00) 		1
(1.00) 		0.0439
(1.00) 		0.154
(1.00) 		0.164
(1.00)
3P GAIN MUTATION ANALYSIS 125 (13%) 824 0.495
(1.00) 		0.0747
(1.00) 		0.0725
(1.00) 		0.00877
(1.00) 		0.278
(1.00) 		0.0392
(1.00) 		1
(1.00) 		0.00986
(1.00) 		0.577
(1.00) 		0.608
(1.00)
4P GAIN MUTATION ANALYSIS 66 (7%) 883 0.0407
(1.00) 		0.475
(1.00) 		0.0106
(1.00) 		0.0133
(1.00) 		0.931
(1.00) 		0.298
(1.00) 		0.515
(1.00) 		0.0506
(1.00) 		0.457
(1.00) 		0.969
(1.00)
4Q GAIN MUTATION ANALYSIS 62 (7%) 887 0.0174
(1.00) 		0.74
(1.00) 		0.00671
(1.00) 		0.0317
(1.00) 		0.722
(1.00) 		0.3
(1.00) 		0.493
(1.00) 		0.00466
(1.00) 		0.444
(1.00) 		0.995
(1.00)
5P GAIN MUTATION ANALYSIS 265 (28%) 684 0.0554
(1.00) 		0.177
(1.00) 		0.631
(1.00) 		0.458
(1.00) 		0.00482
(1.00) 		0.054
(1.00) 		0.478
(1.00) 		0.431
(1.00) 		0.207
(1.00) 		0.79
(1.00)
5Q GAIN MUTATION ANALYSIS 173 (18%) 776 0.496
(1.00) 		0.0164
(1.00) 		0.544
(1.00) 		0.178
(1.00) 		0.305
(1.00) 		0.244
(1.00) 		1
(1.00) 		0.907
(1.00) 		0.435
(1.00) 		0.613
(1.00)
7P GAIN MUTATION ANALYSIS 269 (28%) 680 0.424
(1.00) 		0.418
(1.00) 		0.86
(1.00) 		0.563
(1.00) 		0.807
(1.00) 		0.809
(1.00) 		0.0355
(1.00) 		0.133
(1.00) 		0.0438
(1.00) 		0.28
(1.00)
7Q GAIN MUTATION ANALYSIS 222 (23%) 727 0.541
(1.00) 		0.743
(1.00) 		0.632
(1.00) 		0.535
(1.00) 		0.603
(1.00) 		0.609
(1.00) 		0.0598
(1.00) 		0.273
(1.00) 		0.154
(1.00) 		0.452
(1.00)
8P GAIN MUTATION ANALYSIS 248 (26%) 701 0.763
(1.00) 		0.391
(1.00) 		0.898
(1.00) 		0.773
(1.00) 		0.653
(1.00) 		0.58
(1.00) 		0.727
(1.00) 		0.623
(1.00) 		0.796
(1.00) 		0.822
(1.00)
9P GAIN MUTATION ANALYSIS 117 (12%) 832 0.909
(1.00) 		0.729
(1.00) 		0.458
(1.00) 		0.681
(1.00) 		0.253
(1.00) 		0.676
(1.00) 		0.621
(1.00) 		0.713
(1.00) 		0.909
(1.00) 		0.36
(1.00)
9Q GAIN MUTATION ANALYSIS 105 (11%) 844 0.245
(1.00) 		0.434
(1.00) 		0.846
(1.00) 		0.411
(1.00) 		0.478
(1.00) 		0.821
(1.00) 		0.613
(1.00) 		0.346
(1.00) 		0.548
(1.00) 		0.505
(1.00)
10Q GAIN MUTATION ANALYSIS 105 (11%) 844 0.94
(1.00) 		0.584
(1.00) 		0.418
(1.00) 		0.314
(1.00) 		0.872
(1.00) 		0.848
(1.00) 		0.613
(1.00) 		0.0993
(1.00) 		0.548
(1.00) 		0.831
(1.00)
11P GAIN MUTATION ANALYSIS 116 (12%) 833 0.617
(1.00) 		0.838
(1.00) 		0.902
(1.00) 		0.65
(1.00) 		0.322
(1.00) 		0.891
(1.00) 		0.351
(1.00) 		0.0269
(1.00) 		0.419
(1.00) 		0.106
(1.00)
11Q GAIN MUTATION ANALYSIS 86 (9%) 863 0.345
(1.00) 		0.922
(1.00) 		0.314
(1.00) 		0.707
(1.00) 		0.446
(1.00) 		0.476
(1.00) 		1
(1.00) 		0.0119
(1.00) 		0.599
(1.00) 		0.476
(1.00)
12P GAIN MUTATION ANALYSIS 192 (20%) 757 0.297
(1.00) 		0.419
(1.00) 		0.523
(1.00) 		0.159
(1.00) 		0.19
(1.00) 		0.444
(1.00) 		0.0336
(1.00) 		0.0493
(1.00) 		0.259
(1.00) 		0.205
(1.00)
12Q GAIN MUTATION ANALYSIS 162 (17%) 787 0.153
(1.00) 		0.338
(1.00) 		0.0727
(1.00) 		0.0355
(1.00) 		0.0059
(1.00) 		0.27
(1.00) 		0.0166
(1.00) 		0.196
(1.00) 		0.366
(1.00) 		0.0895
(1.00)
13Q GAIN MUTATION ANALYSIS 79 (8%) 870 0.443
(1.00) 		0.493
(1.00) 		0.833
(1.00) 		0.212
(1.00) 		0.841
(1.00) 		0.249
(1.00) 		1
(1.00) 		0.0215
(1.00) 		0.681
(1.00) 		0.97
(1.00)
14Q GAIN MUTATION ANALYSIS 127 (13%) 822 0.583
(1.00) 		0.0434
(1.00) 		0.0854
(1.00) 		0.11
(1.00) 		0.0382
(1.00) 		0.753
(1.00) 		0.375
(1.00) 		0.343
(1.00) 		1
(1.00) 		0.0922
(1.00)
15Q GAIN MUTATION ANALYSIS 81 (9%) 868 0.417
(1.00) 		0.961
(1.00) 		0.569
(1.00) 		0.936
(1.00) 		0.831
(1.00) 		0.554
(1.00) 		0.592
(1.00) 		0.0383
(1.00) 		1
(1.00) 		0.419
(1.00)
16P GAIN MUTATION ANALYSIS 416 (44%) 533 0.959
(1.00) 		0.0171
(1.00) 		0.791
(1.00) 		0.938
(1.00) 		0.344
(1.00) 		0.854
(1.00) 		0.755
(1.00) 		0.0748
(1.00) 		0.761
(1.00) 		0.701
(1.00)
16Q GAIN MUTATION ANALYSIS 119 (13%) 830 0.171
(1.00) 		0.692
(1.00) 		0.159
(1.00) 		0.325
(1.00) 		0.357
(1.00) 		0.259
(1.00) 		0.119
(1.00) 		0.0824
(1.00) 		0.909
(1.00) 		0.675
(1.00)
17P GAIN MUTATION ANALYSIS 90 (9%) 859 0.415
(1.00) 		0.877
(1.00) 		0.124
(1.00) 		0.0388
(1.00) 		0.174
(1.00) 		0.593
(1.00) 		0.0102
(1.00) 		0.242
(1.00) 		0.197
(1.00) 		0.395
(1.00)
17Q GAIN MUTATION ANALYSIS 187 (20%) 762 0.115
(1.00) 		0.936
(1.00) 		0.914
(1.00) 		0.145
(1.00) 		0.662
(1.00) 		0.457
(1.00) 		0.000731
(0.566) 		0.292
(1.00) 		0.776
(1.00) 		0.956
(1.00)
18P GAIN MUTATION ANALYSIS 151 (16%) 798 0.757
(1.00) 		0.219
(1.00) 		0.138
(1.00) 		0.644
(1.00) 		0.0931
(1.00) 		0.163
(1.00) 		0.665
(1.00) 		0.0052
(1.00) 		0.0386
(1.00) 		0.854
(1.00)
18Q GAIN MUTATION ANALYSIS 129 (14%) 820 0.757
(1.00) 		0.755
(1.00) 		0.178
(1.00) 		0.455
(1.00) 		0.262
(1.00) 		0.0381
(1.00) 		0.634
(1.00) 		0.0543
(1.00) 		0.0984
(1.00) 		0.838
(1.00)
19P GAIN MUTATION ANALYSIS 155 (16%) 794 0.5
(1.00) 		0.881
(1.00) 		0.316
(1.00) 		0.199
(1.00) 		0.527
(1.00) 		0.152
(1.00) 		0.0644
(1.00) 		0.0296
(1.00) 		0.219
(1.00) 		0.319
(1.00)
19Q GAIN MUTATION ANALYSIS 185 (19%) 764 0.215
(1.00) 		0.118
(1.00) 		0.481
(1.00) 		0.734
(1.00) 		0.423
(1.00) 		0.0401
(1.00) 		0.111
(1.00) 		0.143
(1.00) 		0.446
(1.00) 		0.546
(1.00)
21Q GAIN MUTATION ANALYSIS 176 (19%) 773 0.00543
(1.00) 		0.0836
(1.00) 		0.511
(1.00) 		0.645
(1.00) 		0.397
(1.00) 		0.241
(1.00) 		1
(1.00) 		0.00138
(1.00) 		0.00839
(1.00) 		0.169
(1.00)
22Q GAIN MUTATION ANALYSIS 86 (9%) 863 0.364
(1.00) 		0.818
(1.00) 		0.229
(1.00) 		0.427
(1.00) 		0.408
(1.00) 		0.476
(1.00) 		0.612
(1.00) 		0.0149
(1.00) 		0.357
(1.00) 		0.411
(1.00)
1P LOSS MUTATION ANALYSIS 210 (22%) 739 0.0466
(1.00) 		0.0205
(1.00) 		0.00142
(1.00) 		0.000581
(0.451) 		0.00792
(1.00) 		0.277
(1.00) 		1
(1.00) 		0.208
(1.00) 		0.364
(1.00) 		0.0336
(1.00)
1Q LOSS MUTATION ANALYSIS 50 (5%) 899 0.389
(1.00) 		0.441
(1.00) 		0.916
(1.00) 		0.385
(1.00) 		0.053
(1.00) 		0.629
(1.00) 		1
(1.00) 		0.263
(1.00) 		0.315
(1.00) 		0.86
(1.00)
2P LOSS MUTATION ANALYSIS 150 (16%) 799 0.929
(1.00) 		0.389
(1.00) 		0.666
(1.00) 		0.569
(1.00) 		0.295
(1.00) 		0.0941
(1.00) 		1
(1.00) 		0.551
(1.00) 		0.121
(1.00) 		0.83
(1.00)
2Q LOSS MUTATION ANALYSIS 174 (18%) 775 0.501
(1.00) 		0.337
(1.00) 		0.326
(1.00) 		0.66
(1.00) 		0.2
(1.00) 		0.0949
(1.00) 		0.699
(1.00) 		0.425
(1.00) 		0.204
(1.00) 		0.789
(1.00)
3P LOSS MUTATION ANALYSIS 154 (16%) 795 0.317
(1.00) 		0.055
(1.00) 		0.946
(1.00) 		0.021
(1.00) 		0.827
(1.00) 		0.565
(1.00) 		0.38
(1.00) 		0.0339
(1.00) 		0.0822
(1.00) 		0.773
(1.00)
3Q LOSS MUTATION ANALYSIS 83 (9%) 866 0.0899
(1.00) 		0.202
(1.00) 		0.617
(1.00) 		0.00383
(1.00) 		0.581
(1.00) 		0.561
(1.00) 		1
(1.00) 		0.076
(1.00) 		0.0227
(1.00) 		0.0875
(1.00)
6P LOSS MUTATION ANALYSIS 162 (17%) 787 0.905
(1.00) 		0.026
(1.00) 		0.992
(1.00) 		0.679
(1.00) 		0.894
(1.00) 		0.0196
(1.00) 		1
(1.00) 		0.682
(1.00) 		0.482
(1.00) 		0.0689
(1.00)
7P LOSS MUTATION ANALYSIS 95 (10%) 854 0.852
(1.00) 		0.889
(1.00) 		0.19
(1.00) 		0.438
(1.00) 		0.0565
(1.00) 		0.358
(1.00) 		0.611
(1.00) 		0.0302
(1.00) 		0.452
(1.00) 		0.0146
(1.00)
7Q LOSS MUTATION ANALYSIS 107 (11%) 842 0.113
(1.00) 		0.169
(1.00) 		0.435
(1.00) 		0.731
(1.00) 		0.201
(1.00) 		0.115
(1.00) 		0.614
(1.00) 		0.197
(1.00) 		0.812
(1.00) 		0.0238
(1.00)
8Q LOSS MUTATION ANALYSIS 79 (8%) 870 0.0253
(1.00) 		0.168
(1.00) 		0.667
(1.00) 		0.788
(1.00) 		0.112
(1.00) 		0.735
(1.00) 		1
(1.00) 		0.229
(1.00) 		0.414
(1.00) 		0.986
(1.00)
9Q LOSS MUTATION ANALYSIS 247 (26%) 702 0.208
(1.00) 		0.547
(1.00) 		0.291
(1.00) 		0.00711
(1.00) 		0.132
(1.00) 		0.552
(1.00) 		0.138
(1.00) 		0.00105
(0.81) 		0.667
(1.00) 		0.807
(1.00)
10P LOSS MUTATION ANALYSIS 146 (15%) 803 0.0595
(1.00) 		0.931
(1.00) 		0.169
(1.00) 		0.0804
(1.00) 		0.473
(1.00) 		0.00977
(1.00) 		0.376
(1.00) 		0.0816
(1.00) 		0.834
(1.00) 		0.927
(1.00)
10Q LOSS MUTATION ANALYSIS 188 (20%) 761 0.0423
(1.00) 		0.935
(1.00) 		0.472
(1.00) 		0.0521
(1.00) 		0.575
(1.00) 		0.0357
(1.00) 		0.696
(1.00) 		0.0561
(1.00) 		0.925
(1.00) 		0.938
(1.00)
11P LOSS MUTATION ANALYSIS 236 (25%) 713 0.0323
(1.00) 		0.59
(1.00) 		0.0275
(1.00) 		0.0621
(1.00) 		0.095
(1.00) 		0.858
(1.00) 		0.466
(1.00) 		0.0924
(1.00) 		0.541
(1.00) 		0.257
(1.00)
11Q LOSS MUTATION ANALYSIS 317 (33%) 632 0.346
(1.00) 		0.912
(1.00) 		0.373
(1.00) 		0.304
(1.00) 		0.103
(1.00) 		0.512
(1.00) 		0.315
(1.00) 		0.486
(1.00) 		0.749
(1.00) 		0.749
(1.00)
12P LOSS MUTATION ANALYSIS 131 (14%) 818 0.26
(1.00) 		0.422
(1.00) 		0.212
(1.00) 		0.071
(1.00) 		0.564
(1.00) 		0.0947
(1.00) 		1
(1.00) 		0.00524
(1.00) 		0.511
(1.00) 		0.392
(1.00)
12Q LOSS MUTATION ANALYSIS 107 (11%) 842 0.426
(1.00) 		0.0778
(1.00) 		0.155
(1.00) 		0.0637
(1.00) 		0.541
(1.00) 		0.487
(1.00) 		0.614
(1.00) 		0.0114
(1.00) 		0.0721
(1.00) 		0.578
(1.00)
15Q LOSS MUTATION ANALYSIS 271 (29%) 678 0.0706
(1.00) 		0.649
(1.00) 		0.585
(1.00) 		0.0497
(1.00) 		0.174
(1.00) 		0.484
(1.00) 		1
(1.00) 		0.00765
(1.00) 		0.0539
(1.00) 		0.98
(1.00)
16P LOSS MUTATION ANALYSIS 139 (15%) 810 0.376
(1.00) 		0.57
(1.00) 		0.171
(1.00) 		0.733
(1.00) 		0.076
(1.00) 		0.603
(1.00) 		1
(1.00) 		0.381
(1.00) 		0.749
(1.00) 		0.53
(1.00)
17P LOSS MUTATION ANALYSIS 513 (54%) 436 0.279
(1.00) 		0.0232
(1.00) 		0.236
(1.00) 		0.0069
(1.00) 		0.486
(1.00) 		0.938
(1.00) 		1
(1.00) 		0.026
(1.00) 		0.595
(1.00) 		0.888
(1.00)
18Q LOSS MUTATION ANALYSIS 276 (29%) 673 0.00594
(1.00) 		0.0229
(1.00) 		0.0749
(1.00) 		0.0697
(1.00) 		0.151
(1.00) 		0.662
(1.00) 		0.732
(1.00) 		0.044
(1.00) 		0.868
(1.00) 		0.47
(1.00)
20P LOSS MUTATION ANALYSIS 85 (9%) 864 0.0885
(1.00) 		0.661
(1.00) 		0.403
(1.00) 		0.294
(1.00) 		0.567
(1.00) 		0.783
(1.00) 		0.611
(1.00) 		0.0577
(1.00) 		0.693
(1.00) 		0.745
(1.00)
20Q LOSS MUTATION ANALYSIS 45 (5%) 904 0.214
(1.00) 		0.418
(1.00) 		0.275
(1.00) 		0.0776
(1.00) 		0.988
(1.00) 		0.77
(1.00) 		1
(1.00) 		0.0183
(1.00) 		0.723
(1.00) 		0.646
(1.00)
21Q LOSS MUTATION ANALYSIS 152 (16%) 797 0.381
(1.00) 		0.445
(1.00) 		0.035
(1.00) 		0.556
(1.00) 		0.00622
(1.00) 		0.559
(1.00) 		0.379
(1.00) 		0.0826
(1.00) 		0.606
(1.00) 		0.616
(1.00)
22Q LOSS MUTATION ANALYSIS 415 (44%) 534 0.147
(1.00) 		0.505
(1.00) 		0.943
(1.00) 		0.605
(1.00) 		0.483
(1.00) 		0.686
(1.00) 		0.347
(1.00) 		0.00859
(1.00) 		0.0394
(1.00) 		0.284
(1.00)
XQ LOSS MUTATION ANALYSIS 178 (19%) 771 0.556
(1.00) 		0.239
(1.00) 		0.36
(1.00) 		0.0246
(1.00) 		0.487
(1.00) 		0.646
(1.00) 		0.408
(1.00) 		0.0717
(1.00) 		0.439
(1.00) 		0.0471
(1.00)
'2P GAIN MUTATION STATUS' versus 'HISTOLOGICAL.TYPE'

P value = 4.42e-05 (Chi-square test), Q value = 0.035

Table S1.  Gene #3: '2P GAIN MUTATION STATUS' versus Clinical Feature #8: 'HISTOLOGICAL.TYPE'

nPatients INFILTRATING CARCINOMA NOS INFILTRATING DUCTAL CARCINOMA INFILTRATING LOBULAR CARCINOMA MEDULLARY CARCINOMA MIXED HISTOLOGY (PLEASE SPECIFY) MUCINOUS CARCINOMA OTHER SPECIFY
ALL 1 706 151 5 28 14 43
2P GAIN MUTATED 1 92 3 1 0 0 5
2P GAIN WILD-TYPE 0 614 148 4 28 14 38

Figure S1.  Get High-res Image Gene #3: '2P GAIN MUTATION STATUS' versus Clinical Feature #8: 'HISTOLOGICAL.TYPE'

'3Q GAIN MUTATION STATUS' versus 'HISTOLOGICAL.TYPE'

P value = 4.36e-05 (Chi-square test), Q value = 0.034

Table S2.  Gene #6: '3Q GAIN MUTATION STATUS' versus Clinical Feature #8: 'HISTOLOGICAL.TYPE'

nPatients INFILTRATING CARCINOMA NOS INFILTRATING DUCTAL CARCINOMA INFILTRATING LOBULAR CARCINOMA MEDULLARY CARCINOMA MIXED HISTOLOGY (PLEASE SPECIFY) MUCINOUS CARCINOMA OTHER SPECIFY
ALL 1 706 151 5 28 14 43
3Q GAIN MUTATED 0 155 8 3 5 1 7
3Q GAIN WILD-TYPE 1 551 143 2 23 13 36

Figure S2.  Get High-res Image Gene #6: '3Q GAIN MUTATION STATUS' versus Clinical Feature #8: 'HISTOLOGICAL.TYPE'

'6P GAIN MUTATION STATUS' versus 'HISTOLOGICAL.TYPE'

P value = 0.000101 (Chi-square test), Q value = 0.079

Table S3.  Gene #11: '6P GAIN MUTATION STATUS' versus Clinical Feature #8: 'HISTOLOGICAL.TYPE'

nPatients INFILTRATING CARCINOMA NOS INFILTRATING DUCTAL CARCINOMA INFILTRATING LOBULAR CARCINOMA MEDULLARY CARCINOMA MIXED HISTOLOGY (PLEASE SPECIFY) MUCINOUS CARCINOMA OTHER SPECIFY
ALL 1 706 151 5 28 14 43
6P GAIN MUTATED 0 148 14 4 2 1 10
6P GAIN WILD-TYPE 1 558 137 1 26 13 33

Figure S3.  Get High-res Image Gene #11: '6P GAIN MUTATION STATUS' versus Clinical Feature #8: 'HISTOLOGICAL.TYPE'

'6Q GAIN MUTATION STATUS' versus 'HISTOLOGICAL.TYPE'

P value = 8.11e-05 (Chi-square test), Q value = 0.064

Table S4.  Gene #12: '6Q GAIN MUTATION STATUS' versus Clinical Feature #8: 'HISTOLOGICAL.TYPE'

nPatients INFILTRATING CARCINOMA NOS INFILTRATING DUCTAL CARCINOMA INFILTRATING LOBULAR CARCINOMA MEDULLARY CARCINOMA MIXED HISTOLOGY (PLEASE SPECIFY) MUCINOUS CARCINOMA OTHER SPECIFY
ALL 1 706 151 5 28 14 43
6Q GAIN MUTATED 0 102 10 4 2 1 8
6Q GAIN WILD-TYPE 1 604 141 1 26 13 35

Figure S4.  Get High-res Image Gene #12: '6Q GAIN MUTATION STATUS' versus Clinical Feature #8: 'HISTOLOGICAL.TYPE'

'8Q GAIN MUTATION STATUS' versus 'HISTOLOGICAL.TYPE'

P value = 9.55e-06 (Chi-square test), Q value = 0.0076

Table S5.  Gene #16: '8Q GAIN MUTATION STATUS' versus Clinical Feature #8: 'HISTOLOGICAL.TYPE'

nPatients INFILTRATING CARCINOMA NOS INFILTRATING DUCTAL CARCINOMA INFILTRATING LOBULAR CARCINOMA MEDULLARY CARCINOMA MIXED HISTOLOGY (PLEASE SPECIFY) MUCINOUS CARCINOMA OTHER SPECIFY
ALL 1 706 151 5 28 14 43
8Q GAIN MUTATED 1 378 46 4 13 4 25
8Q GAIN WILD-TYPE 0 328 105 1 15 10 18

Figure S5.  Get High-res Image Gene #16: '8Q GAIN MUTATION STATUS' versus Clinical Feature #8: 'HISTOLOGICAL.TYPE'

'10P GAIN MUTATION STATUS' versus 'HISTOLOGICAL.TYPE'

P value = 0.000292 (Chi-square test), Q value = 0.23

Table S6.  Gene #19: '10P GAIN MUTATION STATUS' versus Clinical Feature #8: 'HISTOLOGICAL.TYPE'

nPatients INFILTRATING CARCINOMA NOS INFILTRATING DUCTAL CARCINOMA INFILTRATING LOBULAR CARCINOMA MEDULLARY CARCINOMA MIXED HISTOLOGY (PLEASE SPECIFY) MUCINOUS CARCINOMA OTHER SPECIFY
ALL 1 706 151 5 28 14 43
10P GAIN MUTATED 0 160 15 3 4 0 4
10P GAIN WILD-TYPE 1 546 136 2 24 14 39

Figure S6.  Get High-res Image Gene #19: '10P GAIN MUTATION STATUS' versus Clinical Feature #8: 'HISTOLOGICAL.TYPE'

'20P GAIN MUTATION STATUS' versus 'HISTOLOGICAL.TYPE'

P value = 5.1e-07 (Chi-square test), Q value = 0.00041

Table S7.  Gene #36: '20P GAIN MUTATION STATUS' versus Clinical Feature #8: 'HISTOLOGICAL.TYPE'

nPatients INFILTRATING CARCINOMA NOS INFILTRATING DUCTAL CARCINOMA INFILTRATING LOBULAR CARCINOMA MEDULLARY CARCINOMA MIXED HISTOLOGY (PLEASE SPECIFY) MUCINOUS CARCINOMA OTHER SPECIFY
ALL 1 706 151 5 28 14 43
20P GAIN MUTATED 0 299 28 1 8 1 12
20P GAIN WILD-TYPE 1 407 123 4 20 13 31

Figure S7.  Get High-res Image Gene #36: '20P GAIN MUTATION STATUS' versus Clinical Feature #8: 'HISTOLOGICAL.TYPE'

'20Q GAIN MUTATION STATUS' versus 'HISTOLOGICAL.TYPE'

P value = 7.06e-08 (Chi-square test), Q value = 5.6e-05

Table S8.  Gene #37: '20Q GAIN MUTATION STATUS' versus Clinical Feature #8: 'HISTOLOGICAL.TYPE'

nPatients INFILTRATING CARCINOMA NOS INFILTRATING DUCTAL CARCINOMA INFILTRATING LOBULAR CARCINOMA MEDULLARY CARCINOMA MIXED HISTOLOGY (PLEASE SPECIFY) MUCINOUS CARCINOMA OTHER SPECIFY
ALL 1 706 151 5 28 14 43
20Q GAIN MUTATED 0 327 32 1 8 1 14
20Q GAIN WILD-TYPE 1 379 119 4 20 13 29

Figure S8.  Get High-res Image Gene #37: '20Q GAIN MUTATION STATUS' versus Clinical Feature #8: 'HISTOLOGICAL.TYPE'

'XQ GAIN MUTATION STATUS' versus 'HISTOLOGICAL.TYPE'

P value = 0.000129 (Chi-square test), Q value = 0.1

Table S9.  Gene #40: 'XQ GAIN MUTATION STATUS' versus Clinical Feature #8: 'HISTOLOGICAL.TYPE'

nPatients INFILTRATING CARCINOMA NOS INFILTRATING DUCTAL CARCINOMA INFILTRATING LOBULAR CARCINOMA MEDULLARY CARCINOMA MIXED HISTOLOGY (PLEASE SPECIFY) MUCINOUS CARCINOMA OTHER SPECIFY
ALL 1 706 151 5 28 14 43
XQ GAIN MUTATED 1 119 8 2 1 3 3
XQ GAIN WILD-TYPE 0 587 143 3 27 11 40

Figure S9.  Get High-res Image Gene #40: 'XQ GAIN MUTATION STATUS' versus Clinical Feature #8: 'HISTOLOGICAL.TYPE'

'4P LOSS MUTATION STATUS' versus 'HISTOLOGICAL.TYPE'

P value = 6.01e-06 (Chi-square test), Q value = 0.0048

Table S10.  Gene #47: '4P LOSS MUTATION STATUS' versus Clinical Feature #8: 'HISTOLOGICAL.TYPE'

nPatients INFILTRATING CARCINOMA NOS INFILTRATING DUCTAL CARCINOMA INFILTRATING LOBULAR CARCINOMA MEDULLARY CARCINOMA MIXED HISTOLOGY (PLEASE SPECIFY) MUCINOUS CARCINOMA OTHER SPECIFY
ALL 1 706 151 5 28 14 43
4P LOSS MUTATED 1 251 23 2 6 0 15
4P LOSS WILD-TYPE 0 455 128 3 22 14 28

Figure S10.  Get High-res Image Gene #47: '4P LOSS MUTATION STATUS' versus Clinical Feature #8: 'HISTOLOGICAL.TYPE'

'4Q LOSS MUTATION STATUS' versus 'HISTOLOGICAL.TYPE'

P value = 0.000113 (Chi-square test), Q value = 0.089

Table S11.  Gene #48: '4Q LOSS MUTATION STATUS' versus Clinical Feature #8: 'HISTOLOGICAL.TYPE'

nPatients INFILTRATING CARCINOMA NOS INFILTRATING DUCTAL CARCINOMA INFILTRATING LOBULAR CARCINOMA MEDULLARY CARCINOMA MIXED HISTOLOGY (PLEASE SPECIFY) MUCINOUS CARCINOMA OTHER SPECIFY
ALL 1 706 151 5 28 14 43
4Q LOSS MUTATED 0 220 20 1 6 0 15
4Q LOSS WILD-TYPE 1 486 131 4 22 14 28

Figure S11.  Get High-res Image Gene #48: '4Q LOSS MUTATION STATUS' versus Clinical Feature #8: 'HISTOLOGICAL.TYPE'

'5P LOSS MUTATION STATUS' versus 'HISTOLOGICAL.TYPE'

P value = 1.13e-05 (Chi-square test), Q value = 0.0089

Table S12.  Gene #49: '5P LOSS MUTATION STATUS' versus Clinical Feature #8: 'HISTOLOGICAL.TYPE'

nPatients INFILTRATING CARCINOMA NOS INFILTRATING DUCTAL CARCINOMA INFILTRATING LOBULAR CARCINOMA MEDULLARY CARCINOMA MIXED HISTOLOGY (PLEASE SPECIFY) MUCINOUS CARCINOMA OTHER SPECIFY
ALL 1 706 151 5 28 14 43
5P LOSS MUTATED 0 109 3 3 5 0 4
5P LOSS WILD-TYPE 1 597 148 2 23 14 39

Figure S12.  Get High-res Image Gene #49: '5P LOSS MUTATION STATUS' versus Clinical Feature #8: 'HISTOLOGICAL.TYPE'

'5Q LOSS MUTATION STATUS' versus 'HISTOLOGICAL.TYPE'

P value = 1.06e-09 (Chi-square test), Q value = 8.5e-07

Table S13.  Gene #50: '5Q LOSS MUTATION STATUS' versus Clinical Feature #8: 'HISTOLOGICAL.TYPE'

nPatients INFILTRATING CARCINOMA NOS INFILTRATING DUCTAL CARCINOMA INFILTRATING LOBULAR CARCINOMA MEDULLARY CARCINOMA MIXED HISTOLOGY (PLEASE SPECIFY) MUCINOUS CARCINOMA OTHER SPECIFY
ALL 1 706 151 5 28 14 43
5Q LOSS MUTATED 1 179 4 3 4 0 6
5Q LOSS WILD-TYPE 0 527 147 2 24 14 37

Figure S13.  Get High-res Image Gene #50: '5Q LOSS MUTATION STATUS' versus Clinical Feature #8: 'HISTOLOGICAL.TYPE'

'6Q LOSS MUTATION STATUS' versus 'AGE'

P value = 0.000225 (t-test), Q value = 0.17

Table S14.  Gene #52: '6Q LOSS MUTATION STATUS' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 946 58.5 (13.2)
6Q LOSS MUTATED 237 55.8 (13.1)
6Q LOSS WILD-TYPE 709 59.5 (13.1)

Figure S14.  Get High-res Image Gene #52: '6Q LOSS MUTATION STATUS' versus Clinical Feature #2: 'AGE'

'8P LOSS MUTATION STATUS' versus 'HISTOLOGICAL.TYPE'

P value = 9.05e-05 (Chi-square test), Q value = 0.071

Table S15.  Gene #55: '8P LOSS MUTATION STATUS' versus Clinical Feature #8: 'HISTOLOGICAL.TYPE'

nPatients INFILTRATING CARCINOMA NOS INFILTRATING DUCTAL CARCINOMA INFILTRATING LOBULAR CARCINOMA MEDULLARY CARCINOMA MIXED HISTOLOGY (PLEASE SPECIFY) MUCINOUS CARCINOMA OTHER SPECIFY
ALL 1 706 151 5 28 14 43
8P LOSS MUTATED 1 295 33 2 7 2 17
8P LOSS WILD-TYPE 0 411 118 3 21 12 26

Figure S15.  Get High-res Image Gene #55: '8P LOSS MUTATION STATUS' versus Clinical Feature #8: 'HISTOLOGICAL.TYPE'

'9P LOSS MUTATION STATUS' versus 'PATHOLOGY.T.STAGE'

P value = 0.000149 (Fisher's exact test), Q value = 0.12

Table S16.  Gene #57: '9P LOSS MUTATION STATUS' versus Clinical Feature #4: 'PATHOLOGY.T.STAGE'

nPatients T1 T2 T3 T4
ALL 247 551 113 35
9P LOSS MUTATED 53 181 27 18
9P LOSS WILD-TYPE 194 370 86 17

Figure S16.  Get High-res Image Gene #57: '9P LOSS MUTATION STATUS' versus Clinical Feature #4: 'PATHOLOGY.T.STAGE'

'9P LOSS MUTATION STATUS' versus 'HISTOLOGICAL.TYPE'

P value = 1.37e-05 (Chi-square test), Q value = 0.011

Table S17.  Gene #57: '9P LOSS MUTATION STATUS' versus Clinical Feature #8: 'HISTOLOGICAL.TYPE'

nPatients INFILTRATING CARCINOMA NOS INFILTRATING DUCTAL CARCINOMA INFILTRATING LOBULAR CARCINOMA MEDULLARY CARCINOMA MIXED HISTOLOGY (PLEASE SPECIFY) MUCINOUS CARCINOMA OTHER SPECIFY
ALL 1 706 151 5 28 14 43
9P LOSS MUTATED 0 238 19 3 8 3 8
9P LOSS WILD-TYPE 1 468 132 2 20 11 35

Figure S17.  Get High-res Image Gene #57: '9P LOSS MUTATION STATUS' versus Clinical Feature #8: 'HISTOLOGICAL.TYPE'

'13Q LOSS MUTATION STATUS' versus 'HISTOLOGICAL.TYPE'

P value = 0.000152 (Chi-square test), Q value = 0.12

Table S18.  Gene #65: '13Q LOSS MUTATION STATUS' versus Clinical Feature #8: 'HISTOLOGICAL.TYPE'

nPatients INFILTRATING CARCINOMA NOS INFILTRATING DUCTAL CARCINOMA INFILTRATING LOBULAR CARCINOMA MEDULLARY CARCINOMA MIXED HISTOLOGY (PLEASE SPECIFY) MUCINOUS CARCINOMA OTHER SPECIFY
ALL 1 706 151 5 28 14 43
13Q LOSS MUTATED 0 309 40 4 9 2 12
13Q LOSS WILD-TYPE 1 397 111 1 19 12 31

Figure S18.  Get High-res Image Gene #65: '13Q LOSS MUTATION STATUS' versus Clinical Feature #8: 'HISTOLOGICAL.TYPE'

'14Q LOSS MUTATION STATUS' versus 'HISTOLOGICAL.TYPE'

P value = 6.82e-05 (Chi-square test), Q value = 0.054

Table S19.  Gene #66: '14Q LOSS MUTATION STATUS' versus Clinical Feature #8: 'HISTOLOGICAL.TYPE'

nPatients INFILTRATING CARCINOMA NOS INFILTRATING DUCTAL CARCINOMA INFILTRATING LOBULAR CARCINOMA MEDULLARY CARCINOMA MIXED HISTOLOGY (PLEASE SPECIFY) MUCINOUS CARCINOMA OTHER SPECIFY
ALL 1 706 151 5 28 14 43
14Q LOSS MUTATED 0 188 20 4 3 1 6
14Q LOSS WILD-TYPE 1 518 131 1 25 13 37

Figure S19.  Get High-res Image Gene #66: '14Q LOSS MUTATION STATUS' versus Clinical Feature #8: 'HISTOLOGICAL.TYPE'

'16Q LOSS MUTATION STATUS' versus 'HISTOLOGICAL.TYPE'

P value = 1.26e-11 (Chi-square test), Q value = 1e-08

Table S20.  Gene #69: '16Q LOSS MUTATION STATUS' versus Clinical Feature #8: 'HISTOLOGICAL.TYPE'

nPatients INFILTRATING CARCINOMA NOS INFILTRATING DUCTAL CARCINOMA INFILTRATING LOBULAR CARCINOMA MEDULLARY CARCINOMA MIXED HISTOLOGY (PLEASE SPECIFY) MUCINOUS CARCINOMA OTHER SPECIFY
ALL 1 706 151 5 28 14 43
16Q LOSS MUTATED 0 361 118 2 18 1 13
16Q LOSS WILD-TYPE 1 345 33 3 10 13 30

Figure S20.  Get High-res Image Gene #69: '16Q LOSS MUTATION STATUS' versus Clinical Feature #8: 'HISTOLOGICAL.TYPE'

'17Q LOSS MUTATION STATUS' versus 'HISTOLOGICAL.TYPE'

P value = 0.000305 (Chi-square test), Q value = 0.24

Table S21.  Gene #71: '17Q LOSS MUTATION STATUS' versus Clinical Feature #8: 'HISTOLOGICAL.TYPE'

nPatients INFILTRATING CARCINOMA NOS INFILTRATING DUCTAL CARCINOMA INFILTRATING LOBULAR CARCINOMA MEDULLARY CARCINOMA MIXED HISTOLOGY (PLEASE SPECIFY) MUCINOUS CARCINOMA OTHER SPECIFY
ALL 1 706 151 5 28 14 43
17Q LOSS MUTATED 0 204 26 4 3 0 11
17Q LOSS WILD-TYPE 1 502 125 1 25 14 32

Figure S21.  Get High-res Image Gene #71: '17Q LOSS MUTATION STATUS' versus Clinical Feature #8: 'HISTOLOGICAL.TYPE'

'18P LOSS MUTATION STATUS' versus 'Time to Death'

P value = 7.49e-05 (logrank test), Q value = 0.059

Table S22.  Gene #72: '18P LOSS MUTATION STATUS' versus Clinical Feature #1: 'Time to Death'

nPatients nDeath Duration Range (Median), Month
ALL 895 109 0.0 - 234.2 (21.4)
18P LOSS MUTATED 256 45 0.0 - 189.0 (20.8)
18P LOSS WILD-TYPE 639 64 0.0 - 234.2 (21.7)

Figure S22.  Get High-res Image Gene #72: '18P LOSS MUTATION STATUS' versus Clinical Feature #1: 'Time to Death'

'19P LOSS MUTATION STATUS' versus 'HISTOLOGICAL.TYPE'

P value = 4.04e-05 (Chi-square test), Q value = 0.032

Table S23.  Gene #74: '19P LOSS MUTATION STATUS' versus Clinical Feature #8: 'HISTOLOGICAL.TYPE'

nPatients INFILTRATING CARCINOMA NOS INFILTRATING DUCTAL CARCINOMA INFILTRATING LOBULAR CARCINOMA MEDULLARY CARCINOMA MIXED HISTOLOGY (PLEASE SPECIFY) MUCINOUS CARCINOMA OTHER SPECIFY
ALL 1 706 151 5 28 14 43
19P LOSS MUTATED 0 146 5 1 2 3 5
19P LOSS WILD-TYPE 1 560 146 4 26 11 38

Figure S23.  Get High-res Image Gene #74: '19P LOSS MUTATION STATUS' versus Clinical Feature #8: 'HISTOLOGICAL.TYPE'

'19Q LOSS MUTATION STATUS' versus 'HISTOLOGICAL.TYPE'

P value = 0.000106 (Chi-square test), Q value = 0.083

Table S24.  Gene #75: '19Q LOSS MUTATION STATUS' versus Clinical Feature #8: 'HISTOLOGICAL.TYPE'

nPatients INFILTRATING CARCINOMA NOS INFILTRATING DUCTAL CARCINOMA INFILTRATING LOBULAR CARCINOMA MEDULLARY CARCINOMA MIXED HISTOLOGY (PLEASE SPECIFY) MUCINOUS CARCINOMA OTHER SPECIFY
ALL 1 706 151 5 28 14 43
19Q LOSS MUTATED 0 131 4 1 2 3 4
19Q LOSS WILD-TYPE 1 575 147 4 26 11 39

Figure S24.  Get High-res Image Gene #75: '19Q LOSS MUTATION STATUS' versus Clinical Feature #8: 'HISTOLOGICAL.TYPE'

Methods & Data
Input

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

  • Clinical data file = BRCA-TP.clin.merged.picked.txt

  • Number of patients = 949

  • Number of significantly arm-level cnvs = 80

  • Number of selected clinical features = 10

  • 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.

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] 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)
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