Correlation between copy number variations of arm-level result and selected clinical features

Bladder Urothelial Carcinoma (Primary solid tumor)

21 April 2013 | analyses__2013_04_21

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 (2013): Bladder Urothelial Carcinoma (Primary solid tumor cohort) - 21 April 2013: Correlation between copy number variations of arm-level result and selected clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1H41PB7

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 74 arm-level results and 11 clinical features across 131 patients, 9 significant findings detected with Q value < 0.25.

2p gain cnv correlated to 'GENDER'.
4p gain cnv correlated to 'NUMBER.OF.LYMPH.NODES'.
5q gain cnv correlated to 'NUMBER.OF.LYMPH.NODES'.
9q gain cnv correlated to 'NUMBER.OF.LYMPH.NODES'.
14q gain cnv correlated to 'NUMBER.OF.LYMPH.NODES'.
16p gain cnv correlated to 'Time to Death'.
17p gain cnv correlated to 'NUMBER.OF.LYMPH.NODES'.
6p loss cnv correlated to 'KARNOFSKY.PERFORMANCE.SCORE'.
16q loss cnv correlated to 'TOBACCOSMOKINGHISTORYINDICATOR'.

Results

Overview of the results

Table 1. Get Full Table Overview of the association between significant copy number variation of 74 arm-level results and 11 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 9 significant findings detected.


		Clinical Features	Time to Death	AGE	GENDER	KARNOFSKY PERFORMANCE SCORE	NUMBERPACKYEARSSMOKED	TOBACCOSMOKINGHISTORYINDICATOR	DISTANT METASTASIS	LYMPH NODE METASTASIS	NUMBER OF LYMPH NODES	TUMOR STAGECODE	NEOPLASM DISEASESTAGE
	nCNV (%)	nWild-Type	logrank test	t-test	Fisher's exact test	t-test	t-test	t-test	Fisher's exact test	Chi-square test	t-test	t-test	Fisher's exact test
2p gain	0 (0%)	106	0.584 (1.00)	0.595 (1.00)	0.000227 (0.156)	0.934 (1.00)	0.741 (1.00)	0.356 (1.00)	1 (1.00)	0.437 (1.00)	0.492 (1.00)		0.684 (1.00)
4p gain	0 (0%)	123	0.0892 (1.00)	0.819 (1.00)	0.679 (1.00)		0.394 (1.00)				0.000201 (0.138)
5q gain	0 (0%)	114	0.16 (1.00)	0.55 (1.00)	0.237 (1.00)	0.252 (1.00)	0.914 (1.00)	0.913 (1.00)	0.823 (1.00)	0.377 (1.00)	0.000102 (0.0701)		0.367 (1.00)
9q gain	0 (0%)	119	0.0825 (1.00)	0.186 (1.00)	0.496 (1.00)	0.786 (1.00)	0.167 (1.00)	0.975 (1.00)	0.691 (1.00)	0.402 (1.00)	2.87e-06 (0.00199)		0.00942 (1.00)
14q gain	0 (0%)	120	0.955 (1.00)	0.633 (1.00)	0.467 (1.00)	0.471 (1.00)	0.341 (1.00)	0.728 (1.00)	0.736 (1.00)	0.747 (1.00)	7.1e-05 (0.0489)		0.689 (1.00)
16p gain	0 (0%)	122	4.1e-05 (0.0284)	0.484 (1.00)	0.228 (1.00)	0.45 (1.00)	0.212 (1.00)	0.721 (1.00)	0.263 (1.00)	0.853 (1.00)	0.068 (1.00)		0.61 (1.00)
17p gain	0 (0%)	124	0.305 (1.00)	0.972 (1.00)	0.367 (1.00)		0.974 (1.00)	0.535 (1.00)	0.691 (1.00)	0.402 (1.00)	3.04e-06 (0.00211)		0.12 (1.00)
6p loss	0 (0%)	113	0.994 (1.00)	0.348 (1.00)	0.775 (1.00)	6.63e-05 (0.0457)	0.655 (1.00)	0.341 (1.00)	0.345 (1.00)	0.264 (1.00)	0.282 (1.00)		0.0307 (1.00)
16q loss	0 (0%)	116	0.718 (1.00)	0.31 (1.00)	0.354 (1.00)	0.191 (1.00)	0.946 (1.00)	4.43e-05 (0.0306)	0.813 (1.00)	0.0107 (1.00)	0.344 (1.00)		0.215 (1.00)
1p gain	0 (0%)	116	0.083 (1.00)	0.501 (1.00)	0.528 (1.00)	0.494 (1.00)	0.429 (1.00)	0.976 (1.00)	0.783 (1.00)	0.463 (1.00)	0.558 (1.00)		0.226 (1.00)
1q gain	0 (0%)	102	0.029 (1.00)	0.0223 (1.00)	0.809 (1.00)	0.257 (1.00)	0.675 (1.00)	0.845 (1.00)	0.572 (1.00)	0.911 (1.00)	0.849 (1.00)		0.699 (1.00)
2q gain	0 (0%)	121	0.62 (1.00)	0.632 (1.00)	0.712 (1.00)	0.257 (1.00)	0.443 (1.00)	0.716 (1.00)	0.551 (1.00)	0.434 (1.00)	0.316 (1.00)		0.0363 (1.00)
3p gain	0 (0%)	105	0.485 (1.00)	0.507 (1.00)	0.459 (1.00)	0.422 (1.00)	0.87 (1.00)	0.938 (1.00)	0.742 (1.00)	0.374 (1.00)	0.262 (1.00)		0.265 (1.00)
3q gain	0 (0%)	94	0.207 (1.00)	0.25 (1.00)	0.119 (1.00)	0.846 (1.00)	0.872 (1.00)	0.707 (1.00)	0.643 (1.00)	0.503 (1.00)	0.27 (1.00)		0.61 (1.00)
4q gain	0 (0%)	128	0.303 (1.00)	0.515 (1.00)	1 (1.00)		0.284 (1.00)
5p gain	0 (0%)	92	0.797 (1.00)	0.488 (1.00)	0.512 (1.00)	0.135 (1.00)	0.581 (1.00)	0.567 (1.00)	0.602 (1.00)	0.0104 (1.00)	0.31 (1.00)		0.507 (1.00)
6p gain	0 (0%)	121	0.205 (1.00)	0.643 (1.00)	1 (1.00)	0.616 (1.00)	0.669 (1.00)	0.886 (1.00)	1 (1.00)	0.447 (1.00)	0.122 (1.00)		0.893 (1.00)
6q gain	0 (0%)	126	0.105 (1.00)	0.895 (1.00)	0.33 (1.00)		0.779 (1.00)				0.00639 (1.00)
7p gain	0 (0%)	93	0.497 (1.00)	0.344 (1.00)	0.516 (1.00)	0.141 (1.00)	0.413 (1.00)	0.0177 (1.00)	0.361 (1.00)	0.954 (1.00)	0.788 (1.00)		1 (1.00)
7q gain	0 (0%)	96	0.583 (1.00)	0.631 (1.00)	0.0238 (1.00)	0.141 (1.00)	0.256 (1.00)	0.127 (1.00)	0.88 (1.00)	0.879 (1.00)	0.535 (1.00)		0.508 (1.00)
8p gain	0 (0%)	117	0.902 (1.00)	0.185 (1.00)	1 (1.00)	0.821 (1.00)	0.214 (1.00)	0.304 (1.00)	1 (1.00)	0.834 (1.00)	0.0016 (1.00)		0.867 (1.00)
8q gain	0 (0%)	92	0.558 (1.00)	0.573 (1.00)	0.827 (1.00)	0.896 (1.00)	0.322 (1.00)	0.715 (1.00)	0.635 (1.00)	0.993 (1.00)	0.165 (1.00)		0.74 (1.00)
9p gain	0 (0%)	118	0.037 (1.00)	0.0242 (1.00)	0.183 (1.00)	0.842 (1.00)	0.0265 (1.00)	0.119 (1.00)	0.744 (1.00)	0.319 (1.00)	0.00161 (1.00)		0.489 (1.00)
10p gain	0 (0%)	106	0.87 (1.00)	0.993 (1.00)	0.614 (1.00)	0.73 (1.00)	0.56 (1.00)	0.372 (1.00)	1 (1.00)	0.607 (1.00)	0.666 (1.00)		0.801 (1.00)
10q gain	0 (0%)	124	0.402 (1.00)	0.113 (1.00)	1 (1.00)		0.689 (1.00)	0.648 (1.00)	0.609 (1.00)	0.866 (1.00)	0.535 (1.00)
11p gain	0 (0%)	125	0.0551 (1.00)	0.109 (1.00)	0.336 (1.00)	0.0875 (1.00)	0.618 (1.00)	0.183 (1.00)	1 (1.00)	0.217 (1.00)	0.1 (1.00)		0.523 (1.00)
11q gain	0 (0%)	124	0.297 (1.00)	0.301 (1.00)	0.191 (1.00)	0.792 (1.00)	0.997 (1.00)	0.649 (1.00)	1 (1.00)	0.302 (1.00)	0.321 (1.00)		0.737 (1.00)
12p gain	0 (0%)	107	0.847 (1.00)	0.723 (1.00)	1 (1.00)	0.245 (1.00)	0.978 (1.00)	0.699 (1.00)	0.713 (1.00)	0.446 (1.00)	0.0101 (1.00)		0.374 (1.00)
12q gain	0 (0%)	114	0.36 (1.00)	0.464 (1.00)	0.237 (1.00)	0.347 (1.00)	0.532 (1.00)	0.561 (1.00)	0.422 (1.00)	0.553 (1.00)	0.0816 (1.00)		0.427 (1.00)
13q gain	0 (0%)	110	0.383 (1.00)	0.597 (1.00)	1 (1.00)	0.64 (1.00)	0.145 (1.00)	0.672 (1.00)	0.165 (1.00)	0.174 (1.00)	0.871 (1.00)		0.481 (1.00)
15q gain	0 (0%)	127	0.0836 (1.00)	0.828 (1.00)	1 (1.00)						0.922 (1.00)
16q gain	0 (0%)	119	0.00157 (1.00)	0.319 (1.00)	0.0733 (1.00)	0.468 (1.00)	0.439 (1.00)	0.0896 (1.00)	0.483 (1.00)	0.849 (1.00)	0.0525 (1.00)		0.489 (1.00)
17q gain	0 (0%)	109	0.691 (1.00)	0.923 (1.00)	0.792 (1.00)	0.0945 (1.00)	0.438 (1.00)	0.0874 (1.00)	1 (1.00)	0.882 (1.00)	0.936 (1.00)		1 (1.00)
18p gain	0 (0%)	110	0.885 (1.00)	0.99 (1.00)	0.785 (1.00)	0.469 (1.00)	0.375 (1.00)	0.0858 (1.00)	0.705 (1.00)	0.623 (1.00)	0.679 (1.00)		1 (1.00)
18q gain	0 (0%)	124	0.026 (1.00)	0.788 (1.00)	1 (1.00)		0.848 (1.00)	0.232 (1.00)	0.664 (1.00)	0.838 (1.00)	0.269 (1.00)		1 (1.00)
19p gain	0 (0%)	120	0.631 (1.00)	0.892 (1.00)	0.729 (1.00)	0.257 (1.00)	0.377 (1.00)	0.834 (1.00)	0.776 (1.00)	0.648 (1.00)	0.0478 (1.00)		0.279 (1.00)
19q gain	0 (0%)	107	0.327 (1.00)	0.962 (1.00)	0.309 (1.00)	0.345 (1.00)	0.4 (1.00)	0.83 (1.00)	1 (1.00)	0.919 (1.00)	0.731 (1.00)		0.431 (1.00)
20p gain	0 (0%)	83	0.324 (1.00)	0.844 (1.00)	0.143 (1.00)	0.753 (1.00)	0.435 (1.00)	0.992 (1.00)	0.609 (1.00)	0.367 (1.00)	0.419 (1.00)		0.876 (1.00)
20q gain	0 (0%)	78	0.734 (1.00)	0.387 (1.00)	1 (1.00)	0.48 (1.00)	0.279 (1.00)	0.558 (1.00)	0.559 (1.00)	0.503 (1.00)	0.402 (1.00)		0.508 (1.00)
21q gain	0 (0%)	107	0.437 (1.00)	0.216 (1.00)	1 (1.00)	0.907 (1.00)	0.639 (1.00)	0.492 (1.00)	0.813 (1.00)	0.677 (1.00)	0.929 (1.00)		0.259 (1.00)
22q gain	0 (0%)	120	0.0761 (1.00)	0.544 (1.00)	0.729 (1.00)	0.606 (1.00)	0.487 (1.00)	0.0612 (1.00)	0.551 (1.00)	0.405 (1.00)	0.54 (1.00)		0.689 (1.00)
Xq gain	0 (0%)	125	0.43 (1.00)	0.7 (1.00)	0.641 (1.00)		0.473 (1.00)	0.472 (1.00)	0.455 (1.00)	0.167 (1.00)	0.0933 (1.00)		0.523 (1.00)
2p loss	0 (0%)	124	0.588 (1.00)	0.654 (1.00)	0.679 (1.00)	0.904 (1.00)	0.238 (1.00)	0.983 (1.00)	0.691 (1.00)	0.167 (1.00)			0.523 (1.00)
2q loss	0 (0%)	116	0.0327 (1.00)	0.985 (1.00)	0.354 (1.00)	0.904 (1.00)	0.226 (1.00)	0.677 (1.00)	0.813 (1.00)	0.0296 (1.00)	0.13 (1.00)		0.0898 (1.00)
3p loss	0 (0%)	122	0.943 (1.00)	0.645 (1.00)	0.228 (1.00)		0.494 (1.00)	0.957 (1.00)	1 (1.00)	0.597 (1.00)	0.862 (1.00)		0.361 (1.00)
4p loss	0 (0%)	106	0.503 (1.00)	0.922 (1.00)	1 (1.00)	0.0948 (1.00)	0.541 (1.00)	0.434 (1.00)	0.497 (1.00)	0.0965 (1.00)	0.261 (1.00)		0.371 (1.00)
4q loss	0 (0%)	107	0.682 (1.00)	0.738 (1.00)	0.795 (1.00)	0.0948 (1.00)	0.905 (1.00)	0.305 (1.00)	0.462 (1.00)	0.944 (1.00)	0.807 (1.00)		0.941 (1.00)
5p loss	0 (0%)	120	0.225 (1.00)	0.452 (1.00)	0.143 (1.00)	0.0998 (1.00)	0.802 (1.00)	0.41 (1.00)	0.736 (1.00)	0.946 (1.00)	0.973 (1.00)		0.293 (1.00)
5q loss	0 (0%)	101	0.854 (1.00)	0.61 (1.00)	0.632 (1.00)	0.305 (1.00)	0.345 (1.00)	0.391 (1.00)	0.346 (1.00)	0.182 (1.00)	0.291 (1.00)		0.129 (1.00)
6q loss	0 (0%)	104	0.332 (1.00)	0.906 (1.00)	0.62 (1.00)	0.148 (1.00)	0.374 (1.00)	0.377 (1.00)	0.316 (1.00)	0.216 (1.00)	0.286 (1.00)		0.132 (1.00)
8p loss	0 (0%)	85	0.352 (1.00)	0.464 (1.00)	0.301 (1.00)	0.41 (1.00)	0.149 (1.00)	0.835 (1.00)	0.91 (1.00)	0.57 (1.00)	0.863 (1.00)		0.843 (1.00)
8q loss	0 (0%)	125	0.957 (1.00)	0.0819 (1.00)	0.641 (1.00)		0.847 (1.00)	0.98 (1.00)	0.691 (1.00)	0.582 (1.00)	0.894 (1.00)		0.215 (1.00)
9p loss	0 (0%)	93	0.982 (1.00)	0.58 (1.00)	0.278 (1.00)	0.374 (1.00)	0.284 (1.00)	0.526 (1.00)	0.22 (1.00)	0.478 (1.00)	0.892 (1.00)		0.422 (1.00)
9q loss	0 (0%)	95	0.812 (1.00)	0.876 (1.00)	0.185 (1.00)	0.651 (1.00)	0.198 (1.00)	0.886 (1.00)	0.291 (1.00)	0.609 (1.00)	0.0671 (1.00)		0.409 (1.00)
10p loss	0 (0%)	113	0.481 (1.00)	0.896 (1.00)	1 (1.00)	0.0186 (1.00)	0.804 (1.00)	0.224 (1.00)	0.559 (1.00)	0.388 (1.00)	0.0409 (1.00)		0.932 (1.00)
10q loss	0 (0%)	105	0.427 (1.00)	0.0231 (1.00)	0.805 (1.00)	0.134 (1.00)	0.744 (1.00)	0.766 (1.00)	0.778 (1.00)	0.671 (1.00)	0.849 (1.00)		0.772 (1.00)
11p loss	0 (0%)	89	0.617 (1.00)	0.271 (1.00)	0.833 (1.00)	0.135 (1.00)	0.982 (1.00)	0.249 (1.00)	0.243 (1.00)	0.789 (1.00)	0.241 (1.00)		0.336 (1.00)
11q loss	0 (0%)	100	0.882 (1.00)	0.619 (1.00)	0.815 (1.00)	0.708 (1.00)	0.343 (1.00)	0.884 (1.00)	0.536 (1.00)	0.794 (1.00)	0.258 (1.00)		0.724 (1.00)
12p loss	0 (0%)	126	0.937 (1.00)	0.298 (1.00)	0.33 (1.00)		0.678 (1.00)	0.39 (1.00)	1 (1.00)	0.619 (1.00)	0.877 (1.00)		0.387 (1.00)
12q loss	0 (0%)	125	0.125 (1.00)	0.314 (1.00)	0.336 (1.00)		0.857 (1.00)	0.318 (1.00)	1 (1.00)	0.0362 (1.00)	0.462 (1.00)		0.195 (1.00)
13q loss	0 (0%)	113	0.874 (1.00)	0.685 (1.00)	0.24 (1.00)	0.0159 (1.00)	0.723 (1.00)	0.308 (1.00)	1 (1.00)	0.481 (1.00)	0.582 (1.00)		0.387 (1.00)
14q loss	0 (0%)	109	0.21 (1.00)	0.241 (1.00)	0.28 (1.00)	0.772 (1.00)	0.719 (1.00)	0.677 (1.00)	1 (1.00)	0.406 (1.00)	0.676 (1.00)		0.849 (1.00)
15q loss	0 (0%)	116	0.472 (1.00)	0.824 (1.00)	0.528 (1.00)	0.763 (1.00)	0.883 (1.00)	0.00922 (1.00)	1 (1.00)	0.755 (1.00)	0.946 (1.00)		0.518 (1.00)
16p loss	0 (0%)	117	0.459 (1.00)	0.205 (1.00)	0.188 (1.00)	0.0945 (1.00)	0.443 (1.00)	0.00096 (0.655)	1 (1.00)	0.137 (1.00)	0.976 (1.00)		0.649 (1.00)
17p loss	0 (0%)	94	0.392 (1.00)	0.602 (1.00)	0.824 (1.00)	0.856 (1.00)	0.338 (1.00)	0.73 (1.00)	0.716 (1.00)	0.711 (1.00)	0.769 (1.00)		0.777 (1.00)
17q loss	0 (0%)	126	0.887 (1.00)	0.407 (1.00)	1 (1.00)	0.77 (1.00)	0.526 (1.00)	0.29 (1.00)	1 (1.00)	0.0247 (1.00)			0.0658 (1.00)
18p loss	0 (0%)	113	0.329 (1.00)	0.0554 (1.00)	0.392 (1.00)	0.295 (1.00)	0.674 (1.00)	0.892 (1.00)	0.189 (1.00)	0.867 (1.00)	0.847 (1.00)		0.684 (1.00)
18q loss	0 (0%)	97	0.0978 (1.00)	0.0375 (1.00)	0.167 (1.00)	0.57 (1.00)	0.253 (1.00)	0.565 (1.00)	0.635 (1.00)	0.929 (1.00)	0.824 (1.00)		0.777 (1.00)
19p loss	0 (0%)	123	0.341 (1.00)	0.913 (1.00)	1 (1.00)		0.929 (1.00)	0.641 (1.00)	0.0861 (1.00)	0.00234 (1.00)	0.265 (1.00)		0.00166 (1.00)
19q loss	0 (0%)	128	0.000889 (0.608)	0.9 (1.00)	0.572 (1.00)						0.692 (1.00)
20p loss	0 (0%)	126	0.714 (1.00)	0.479 (1.00)	1 (1.00)		0.0292 (1.00)	0.9 (1.00)			0.64 (1.00)		0.538 (1.00)
21q loss	0 (0%)	118	0.996 (1.00)	0.000838 (0.574)	1 (1.00)	0.00136 (0.928)	0.894 (1.00)	0.397 (1.00)	0.295 (1.00)	0.00863 (1.00)	0.616 (1.00)		0.0642 (1.00)
22q loss	0 (0%)	106	0.115 (1.00)	0.518 (1.00)	0.799 (1.00)	0.187 (1.00)	0.808 (1.00)	0.264 (1.00)	0.859 (1.00)	0.711 (1.00)	0.627 (1.00)		0.888 (1.00)
Xq loss	0 (0%)	128	0.31 (1.00)	0.858 (1.00)	1 (1.00)		0.349 (1.00)	0.0942 (1.00)	1 (1.00)				0.0658 (1.00)

'2p gain' versus 'GENDER'

P value = 0.000227 (Fisher's exact test), Q value = 0.16

Table S1. Gene #3: '2p gain' versus Clinical Feature #3: 'GENDER'

nPatients	FEMALE	MALE
ALL	33	98
2P GAIN CNV	14	11
2P GAIN WILD-TYPE	19	87

Figure S1. Get High-res Image Gene #3: '2p gain' versus Clinical Feature #3: 'GENDER'

'4p gain' versus 'NUMBER.OF.LYMPH.NODES'

P value = 0.000201 (t-test), Q value = 0.14

Table S2. Gene #7: '4p gain' versus Clinical Feature #9: 'NUMBER.OF.LYMPH.NODES'

	nPatients	Mean (Std.Dev)
ALL	98	1.9 (3.8)
4P GAIN CNV	5	0.2 (0.4)
4P GAIN WILD-TYPE	93	2.0 (3.8)

Figure S2. Get High-res Image Gene #7: '4p gain' versus Clinical Feature #9: 'NUMBER.OF.LYMPH.NODES'

'5q gain' versus 'NUMBER.OF.LYMPH.NODES'

P value = 0.000102 (t-test), Q value = 0.07

Table S3. Gene #10: '5q gain' versus Clinical Feature #9: 'NUMBER.OF.LYMPH.NODES'

	nPatients	Mean (Std.Dev)
ALL	98	1.9 (3.8)
5Q GAIN CNV	11	0.3 (0.5)
5Q GAIN WILD-TYPE	87	2.1 (3.9)

Figure S3. Get High-res Image Gene #10: '5q gain' versus Clinical Feature #9: 'NUMBER.OF.LYMPH.NODES'

'9q gain' versus 'NUMBER.OF.LYMPH.NODES'

P value = 2.87e-06 (t-test), Q value = 0.002

Table S4. Gene #18: '9q gain' versus Clinical Feature #9: 'NUMBER.OF.LYMPH.NODES'

	nPatients	Mean (Std.Dev)
ALL	98	1.9 (3.8)
9Q GAIN CNV	9	0.0 (0.0)
9Q GAIN WILD-TYPE	89	2.1 (3.9)

Figure S4. Get High-res Image Gene #18: '9q gain' versus Clinical Feature #9: 'NUMBER.OF.LYMPH.NODES'

'14q gain' versus 'NUMBER.OF.LYMPH.NODES'

P value = 7.1e-05 (t-test), Q value = 0.049

Table S5. Gene #26: '14q gain' versus Clinical Feature #9: 'NUMBER.OF.LYMPH.NODES'

	nPatients	Mean (Std.Dev)
ALL	98	1.9 (3.8)
14Q GAIN CNV	6	0.2 (0.4)
14Q GAIN WILD-TYPE	92	2.0 (3.9)

Figure S5. Get High-res Image Gene #26: '14q gain' versus Clinical Feature #9: 'NUMBER.OF.LYMPH.NODES'

'16p gain' versus 'Time to Death'

P value = 4.1e-05 (logrank test), Q value = 0.028

Table S6. Gene #28: '16p gain' versus Clinical Feature #1: 'Time to Death'

	nPatients	nDeath	Duration Range (Median), Month
ALL	124	32	0.1 - 131.2 (7.0)
16P GAIN CNV	9	5	2.2 - 9.7 (5.1)
16P GAIN WILD-TYPE	115	27	0.1 - 131.2 (7.0)

Figure S6. Get High-res Image Gene #28: '16p gain' versus Clinical Feature #1: 'Time to Death'

'17p gain' versus 'NUMBER.OF.LYMPH.NODES'

P value = 3.04e-06 (t-test), Q value = 0.0021

Table S7. Gene #30: '17p gain' versus Clinical Feature #9: 'NUMBER.OF.LYMPH.NODES'

	nPatients	Mean (Std.Dev)
ALL	98	1.9 (3.8)
17P GAIN CNV	5	0.0 (0.0)
17P GAIN WILD-TYPE	93	2.0 (3.8)

Figure S7. Get High-res Image Gene #30: '17p gain' versus Clinical Feature #9: 'NUMBER.OF.LYMPH.NODES'

'6p loss' versus 'KARNOFSKY.PERFORMANCE.SCORE'

P value = 6.63e-05 (t-test), Q value = 0.046

Table S8. Gene #48: '6p loss' versus Clinical Feature #4: 'KARNOFSKY.PERFORMANCE.SCORE'

	nPatients	Mean (Std.Dev)
ALL	37	78.1 (16.3)
6P LOSS CNV	4	90.0 (0.0)
6P LOSS WILD-TYPE	33	76.7 (16.7)

Figure S8. Get High-res Image Gene #48: '6p loss' versus Clinical Feature #4: 'KARNOFSKY.PERFORMANCE.SCORE'

'16q loss' versus 'TOBACCOSMOKINGHISTORYINDICATOR'

P value = 4.43e-05 (t-test), Q value = 0.031

Table S9. Gene #64: '16q loss' versus Clinical Feature #6: 'TOBACCOSMOKINGHISTORYINDICATOR'

	nPatients	Mean (Std.Dev)
ALL	80	2.8 (1.2)
16Q LOSS CNV	11	3.6 (0.5)
16Q LOSS WILD-TYPE	69	2.7 (1.2)

Figure S9. Get High-res Image Gene #64: '16q loss' versus Clinical Feature #6: 'TOBACCOSMOKINGHISTORYINDICATOR'

Methods & Data

Input

Mutation data file = broad_values_by_arm.mutsig.cluster.txt
Clinical data file = BLCA-TP.clin.merged.picked.txt
Number of patients = 131
Number of significantly arm-level cnvs = 74
Number of selected clinical features = 11
Exclude genes 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

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

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

This is an experimental feature. The full results of the analysis summarized in this report can be downloaded from the TCGA Data Coordination Center.

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] Greenwood and Nikulin, A guide to chi-squared testing, Wiley, New York. ISBN 047155779X (1996)

[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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