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

Kidney Renal Papillary Cell Carcinoma (Primary solid tumor)

23 September 2013 | analyses__2013_09_23

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): Correlation between copy number variations of arm-level result and selected clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1DB8042

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 63 arm-level events and 10 clinical features across 129 patients, 11 significant findings detected with Q value < 0.25.

1Q GAIN MUTATION ANALYSIS cnv correlated to 'Time to Death', 'NEOPLASM.DISEASESTAGE', and 'PATHOLOGY.T.STAGE'.
6Q GAIN MUTATION ANALYSIS cnv correlated to 'Time to Death'.
8Q GAIN MUTATION ANALYSIS cnv correlated to 'Time to Death'.
17P GAIN MUTATION ANALYSIS cnv correlated to 'PATHOLOGY.M.STAGE'.
3Q LOSS MUTATION ANALYSIS cnv correlated to 'Time to Death'.
5P LOSS MUTATION ANALYSIS cnv correlated to 'Time to Death'.
16P LOSS MUTATION ANALYSIS cnv correlated to 'Time to Death'.
16Q LOSS MUTATION ANALYSIS cnv correlated to 'Time to Death'.
17P LOSS MUTATION ANALYSIS cnv correlated to 'Time to Death'.

Results

Overview of the results

Table 1. Get Full Table Overview of the association between significant copy number variation of 63 arm-level events and 10 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	NEOPLASM DISEASESTAGE	PATHOLOGY T STAGE	PATHOLOGY N STAGE	PATHOLOGY M STAGE	GENDER	KARNOFSKY PERFORMANCE SCORE	NUMBERPACKYEARSSMOKED	YEAROFTOBACCOSMOKINGONSET
	nCNV (%)	nWild-Type	logrank test	t-test	Fisher's exact test	Fisher's exact test	Fisher's exact test	Fisher's exact test	Fisher's exact test	t-test	t-test	t-test
1Q GAIN MUTATION ANALYSIS	11 (9%)	118	1.28e-05 (0.00586)	0.386 (1.00)	0.000272 (0.123)	9.11e-05 (0.0415)	0.379 (1.00)	0.156 (1.00)	0.0944 (1.00)
6Q GAIN MUTATION ANALYSIS	3 (2%)	126	8.53e-06 (0.00393)	0.257 (1.00)	0.0477 (1.00)	0.513 (1.00)		0.00616 (1.00)	0.552 (1.00)
8Q GAIN MUTATION ANALYSIS	13 (10%)	116	3.61e-05 (0.0166)	0.838 (1.00)	0.0576 (1.00)	0.0442 (1.00)	0.0305 (1.00)	0.381 (1.00)	0.221 (1.00)
17P GAIN MUTATION ANALYSIS	71 (55%)	58	0.114 (1.00)	0.0209 (1.00)	0.00213 (0.946)	0.0051 (1.00)	0.227 (1.00)	0.000167 (0.0757)	0.0235 (1.00)	0.182 (1.00)
3Q LOSS MUTATION ANALYSIS	3 (2%)	126	2.37e-06 (0.00109)	0.323 (1.00)	0.0943 (1.00)	0.0665 (1.00)	0.434 (1.00)	0.144 (1.00)	1 (1.00)
5P LOSS MUTATION ANALYSIS	6 (5%)	123	0.000124 (0.0564)	0.114 (1.00)	0.0558 (1.00)	0.0262 (1.00)	0.0172 (1.00)	0.193 (1.00)	0.0739 (1.00)
16P LOSS MUTATION ANALYSIS	4 (3%)	125	4.28e-05 (0.0195)	0.653 (1.00)	0.255 (1.00)	0.157 (1.00)		1 (1.00)	0.0882 (1.00)
16Q LOSS MUTATION ANALYSIS	4 (3%)	125	4.28e-05 (0.0195)	0.653 (1.00)	0.255 (1.00)	0.157 (1.00)		1 (1.00)	0.0882 (1.00)
17P LOSS MUTATION ANALYSIS	7 (5%)	122	4.06e-09 (1.88e-06)	0.863 (1.00)	0.00668 (1.00)	0.0332 (1.00)	0.108 (1.00)	0.0555 (1.00)	0.202 (1.00)
2P GAIN MUTATION ANALYSIS	21 (16%)	108	0.092 (1.00)	0.22 (1.00)	0.0549 (1.00)	0.586 (1.00)	0.203 (1.00)	0.00141 (0.629)	0.449 (1.00)	0.541 (1.00)
2Q GAIN MUTATION ANALYSIS	23 (18%)	106	0.177 (1.00)	0.62 (1.00)	0.0138 (1.00)	0.571 (1.00)	0.127 (1.00)	0.00263 (1.00)	0.456 (1.00)	0.501 (1.00)
3P GAIN MUTATION ANALYSIS	36 (28%)	93	0.239 (1.00)	0.792 (1.00)	0.0926 (1.00)	0.0322 (1.00)	1 (1.00)	0.254 (1.00)	0.403 (1.00)	0.13 (1.00)
3Q GAIN MUTATION ANALYSIS	41 (32%)	88	0.105 (1.00)	0.675 (1.00)	0.129 (1.00)	0.0804 (1.00)	1 (1.00)	0.143 (1.00)	0.155 (1.00)	0.248 (1.00)
4P GAIN MUTATION ANALYSIS	6 (5%)	123	0.0226 (1.00)	0.00425 (1.00)	0.092 (1.00)	0.85 (1.00)	0.53 (1.00)	0.193 (1.00)	0.665 (1.00)
4Q GAIN MUTATION ANALYSIS	5 (4%)	124	0.36 (1.00)	0.0141 (1.00)	0.387 (1.00)	0.662 (1.00)	0.284 (1.00)	0.69 (1.00)	1 (1.00)
5P GAIN MUTATION ANALYSIS	20 (16%)	109	0.449 (1.00)	0.323 (1.00)	0.233 (1.00)	0.217 (1.00)	0.862 (1.00)	0.291 (1.00)	0.608 (1.00)	0.397 (1.00)
5Q GAIN MUTATION ANALYSIS	19 (15%)	110	0.149 (1.00)	0.631 (1.00)	0.305 (1.00)	0.302 (1.00)	1 (1.00)	0.303 (1.00)	0.79 (1.00)	0.397 (1.00)
6P GAIN MUTATION ANALYSIS	4 (3%)	125	0.0639 (1.00)	0.356 (1.00)	0.0624 (1.00)	0.157 (1.00)	0.434 (1.00)	0.00611 (1.00)	0.31 (1.00)
7P GAIN MUTATION ANALYSIS	71 (55%)	58	0.11 (1.00)	0.809 (1.00)	0.0027 (1.00)	0.0132 (1.00)	0.805 (1.00)	0.16 (1.00)	0.0593 (1.00)	0.184 (1.00)
7Q GAIN MUTATION ANALYSIS	73 (57%)	56	0.0991 (1.00)	0.716 (1.00)	0.00387 (1.00)	0.0186 (1.00)	0.726 (1.00)	0.276 (1.00)	0.0863 (1.00)	0.184 (1.00)
8P GAIN MUTATION ANALYSIS	10 (8%)	119	0.0466 (1.00)	0.894 (1.00)	0.487 (1.00)	0.358 (1.00)	0.441 (1.00)	0.849 (1.00)	0.499 (1.00)
10P GAIN MUTATION ANALYSIS	5 (4%)	124	0.54 (1.00)	0.932 (1.00)	0.255 (1.00)	0.515 (1.00)		0.51 (1.00)	1 (1.00)
10Q GAIN MUTATION ANALYSIS	4 (3%)	125	0.501 (1.00)	0.811 (1.00)	0.271 (1.00)	0.589 (1.00)		0.69 (1.00)	1 (1.00)
11P GAIN MUTATION ANALYSIS	6 (5%)	123	0.0357 (1.00)	0.303 (1.00)	0.0558 (1.00)	0.0508 (1.00)	0.721 (1.00)	0.012 (1.00)	1 (1.00)
11Q GAIN MUTATION ANALYSIS	4 (3%)	125	0.755 (1.00)	0.127 (1.00)	0.271 (1.00)	0.0956 (1.00)	1 (1.00)	0.144 (1.00)	0.587 (1.00)
12P GAIN MUTATION ANALYSIS	49 (38%)	80	0.348 (1.00)	0.776 (1.00)	0.582 (1.00)	0.463 (1.00)	0.493 (1.00)	0.109 (1.00)	0.119 (1.00)	0.248 (1.00)
12Q GAIN MUTATION ANALYSIS	49 (38%)	80	0.348 (1.00)	0.776 (1.00)	0.582 (1.00)	0.463 (1.00)	0.493 (1.00)	0.109 (1.00)	0.119 (1.00)	0.248 (1.00)
13Q GAIN MUTATION ANALYSIS	15 (12%)	114	0.485 (1.00)	0.155 (1.00)	0.481 (1.00)	0.527 (1.00)		1 (1.00)	1 (1.00)	0.197 (1.00)
16P GAIN MUTATION ANALYSIS	66 (51%)	63	0.984 (1.00)	0.45 (1.00)	0.599 (1.00)	0.967 (1.00)	1 (1.00)	0.263 (1.00)	0.00728 (1.00)	0.529 (1.00)
16Q GAIN MUTATION ANALYSIS	64 (50%)	65	0.304 (1.00)	0.663 (1.00)	0.599 (1.00)	0.907 (1.00)	0.804 (1.00)	0.0373 (1.00)	0.0359 (1.00)	0.25 (1.00)
17Q GAIN MUTATION ANALYSIS	84 (65%)	45	0.718 (1.00)	0.0637 (1.00)	0.449 (1.00)	0.377 (1.00)	0.506 (1.00)	0.00265 (1.00)	0.115 (1.00)	0.561 (1.00)
18P GAIN MUTATION ANALYSIS	7 (5%)	122	0.85 (1.00)	0.586 (1.00)	0.485 (1.00)	0.538 (1.00)		0.136 (1.00)	1 (1.00)	0.541 (1.00)
18Q GAIN MUTATION ANALYSIS	5 (4%)	124	0.363 (1.00)	0.954 (1.00)	0.733 (1.00)	0.662 (1.00)		0.69 (1.00)	1 (1.00)
20P GAIN MUTATION ANALYSIS	42 (33%)	87	0.815 (1.00)	0.0189 (1.00)	0.606 (1.00)	0.53 (1.00)	0.876 (1.00)	0.492 (1.00)	0.839 (1.00)	0.636 (1.00)
20Q GAIN MUTATION ANALYSIS	45 (35%)	84	0.483 (1.00)	0.0144 (1.00)	0.398 (1.00)	0.432 (1.00)	0.771 (1.00)	0.898 (1.00)	1 (1.00)	0.636 (1.00)
21Q GAIN MUTATION ANALYSIS	6 (5%)	123	0.755 (1.00)	0.0276 (1.00)	0.561 (1.00)	0.251 (1.00)		0.51 (1.00)	0.665 (1.00)
XQ GAIN MUTATION ANALYSIS	38 (29%)	91	0.673 (1.00)	0.609 (1.00)	0.16 (1.00)	0.146 (1.00)	1 (1.00)	0.569 (1.00)	0.145 (1.00)	0.136 (1.00)
1P LOSS MUTATION ANALYSIS	17 (13%)	112	0.7 (1.00)	0.645 (1.00)	0.446 (1.00)	0.565 (1.00)	0.34 (1.00)	0.912 (1.00)	0.779 (1.00)	0.342 (1.00)
1Q LOSS MUTATION ANALYSIS	10 (8%)	119	0.563 (1.00)	0.398 (1.00)	0.255 (1.00)	0.645 (1.00)		0.481 (1.00)	1 (1.00)	0.342 (1.00)
3P LOSS MUTATION ANALYSIS	9 (7%)	120	0.178 (1.00)	0.111 (1.00)	0.00718 (1.00)	0.00599 (1.00)	0.724 (1.00)	0.0885 (1.00)	0.72 (1.00)
4P LOSS MUTATION ANALYSIS	11 (9%)	118	0.193 (1.00)	0.0531 (1.00)	0.00996 (1.00)	0.00414 (1.00)	0.0279 (1.00)	0.468 (1.00)	0.00371 (1.00)
4Q LOSS MUTATION ANALYSIS	12 (9%)	117	0.817 (1.00)	0.237 (1.00)	0.0387 (1.00)	0.0377 (1.00)	0.267 (1.00)	0.12 (1.00)	0.0472 (1.00)
5Q LOSS MUTATION ANALYSIS	5 (4%)	124	0.0201 (1.00)	0.114 (1.00)	0.255 (1.00)	0.0466 (1.00)	0.0394 (1.00)	0.284 (1.00)	0.173 (1.00)
6P LOSS MUTATION ANALYSIS	10 (8%)	119	0.0941 (1.00)	0.501 (1.00)	0.147 (1.00)	0.101 (1.00)	0.53 (1.00)	1 (1.00)	0.283 (1.00)	0.248 (1.00)
6Q LOSS MUTATION ANALYSIS	12 (9%)	117	0.341 (1.00)	0.82 (1.00)	0.119 (1.00)	0.0253 (1.00)	0.587 (1.00)	0.431 (1.00)	0.0472 (1.00)	0.383 (1.00)
8P LOSS MUTATION ANALYSIS	5 (4%)	124	0.000834 (0.374)	0.209 (1.00)	0.041 (1.00)	0.515 (1.00)		0.0196 (1.00)	0.173 (1.00)
8Q LOSS MUTATION ANALYSIS	3 (2%)	126	0.0145 (1.00)	0.601 (1.00)	0.119 (1.00)	0.356 (1.00)		0.144 (1.00)	0.227 (1.00)
9P LOSS MUTATION ANALYSIS	17 (13%)	112	0.0721 (1.00)	0.535 (1.00)	0.00317 (1.00)	0.00353 (1.00)	0.374 (1.00)	0.0495 (1.00)	0.0116 (1.00)	0.398 (1.00)
9Q LOSS MUTATION ANALYSIS	18 (14%)	111	0.0954 (1.00)	0.868 (1.00)	0.0249 (1.00)	0.0024 (1.00)	0.203 (1.00)	0.259 (1.00)	0.0963 (1.00)	0.398 (1.00)
10P LOSS MUTATION ANALYSIS	8 (6%)	121	0.878 (1.00)	0.736 (1.00)	0.14 (1.00)	0.0795 (1.00)	0.102 (1.00)	0.136 (1.00)	0.703 (1.00)	0.397 (1.00)
10Q LOSS MUTATION ANALYSIS	8 (6%)	121	0.219 (1.00)	0.473 (1.00)	0.0723 (1.00)	0.0237 (1.00)	0.34 (1.00)	0.3 (1.00)	1 (1.00)	0.397 (1.00)
11P LOSS MUTATION ANALYSIS	9 (7%)	120	0.013 (1.00)	0.0568 (1.00)	0.185 (1.00)	0.231 (1.00)	0.434 (1.00)	0.481 (1.00)	0.458 (1.00)
11Q LOSS MUTATION ANALYSIS	12 (9%)	117	0.00109 (0.488)	0.0288 (1.00)	0.00424 (1.00)	0.00215 (0.953)	0.285 (1.00)	0.156 (1.00)	1 (1.00)
13Q LOSS MUTATION ANALYSIS	11 (9%)	118	0.0237 (1.00)	0.273 (1.00)	0.0719 (1.00)	0.0427 (1.00)	0.0823 (1.00)	0.468 (1.00)	0.00371 (1.00)
14Q LOSS MUTATION ANALYSIS	27 (21%)	102	0.596 (1.00)	0.73 (1.00)	0.0817 (1.00)	0.117 (1.00)	0.274 (1.00)	0.213 (1.00)	0.246 (1.00)	0.377 (1.00)
15Q LOSS MUTATION ANALYSIS	14 (11%)	115	0.00495 (1.00)	0.178 (1.00)	0.298 (1.00)	0.0761 (1.00)	0.267 (1.00)	0.0578 (1.00)	0.762 (1.00)	0.654 (1.00)
18P LOSS MUTATION ANALYSIS	20 (16%)	109	0.0589 (1.00)	0.427 (1.00)	0.0107 (1.00)	0.00267 (1.00)	0.203 (1.00)	0.0575 (1.00)	1 (1.00)	0.342 (1.00)
18Q LOSS MUTATION ANALYSIS	21 (16%)	108	0.0589 (1.00)	0.427 (1.00)	0.00487 (1.00)	0.000971 (0.435)	0.203 (1.00)	0.042 (1.00)	0.801 (1.00)	0.342 (1.00)
19P LOSS MUTATION ANALYSIS	9 (7%)	120	0.647 (1.00)	0.47 (1.00)	0.118 (1.00)	0.0524 (1.00)	1 (1.00)	0.3 (1.00)	1 (1.00)
19Q LOSS MUTATION ANALYSIS	8 (6%)	121	0.741 (1.00)	0.747 (1.00)	0.0474 (1.00)	0.0179 (1.00)	1 (1.00)	0.136 (1.00)	0.703 (1.00)
21Q LOSS MUTATION ANALYSIS	23 (18%)	106	0.425 (1.00)	0.472 (1.00)	0.0112 (1.00)	0.00971 (1.00)	0.33 (1.00)	0.12 (1.00)	0.456 (1.00)
22Q LOSS MUTATION ANALYSIS	31 (24%)	98	0.788 (1.00)	0.602 (1.00)	0.000733 (0.33)	0.000626 (0.282)	0.14 (1.00)	0.118 (1.00)	0.0735 (1.00)	0.445 (1.00)
XQ LOSS MUTATION ANALYSIS	19 (15%)	110	0.00127 (0.564)	0.0873 (1.00)	0.0621 (1.00)	0.016 (1.00)	0.0392 (1.00)	0.317 (1.00)	0.288 (1.00)	0.458 (1.00)

'1Q GAIN MUTATION STATUS' versus 'Time to Death'

P value = 1.28e-05 (logrank test), Q value = 0.0059

Table S1. Gene #1: '1Q GAIN MUTATION STATUS' versus Clinical Feature #1: 'Time to Death'

	nPatients	nDeath	Duration Range (Median), Month
ALL	119	15	0.0 - 194.8 (13.7)
1Q GAIN MUTATED	10	3	0.7 - 30.3 (5.8)
1Q GAIN WILD-TYPE	109	12	0.0 - 194.8 (14.6)

Figure S1. Get High-res Image Gene #1: '1Q GAIN MUTATION STATUS' versus Clinical Feature #1: 'Time to Death'

'1Q GAIN MUTATION STATUS' versus 'NEOPLASM.DISEASESTAGE'

P value = 0.000272 (Fisher's exact test), Q value = 0.12

Table S2. Gene #1: '1Q GAIN MUTATION STATUS' versus Clinical Feature #3: 'NEOPLASM.DISEASESTAGE'

nPatients	STAGE I	STAGE II	STAGE III	STAGE IV
ALL	69	10	30	10
1Q GAIN MUTATED	1	0	7	3
1Q GAIN WILD-TYPE	68	10	23	7

Figure S2. Get High-res Image Gene #1: '1Q GAIN MUTATION STATUS' versus Clinical Feature #3: 'NEOPLASM.DISEASESTAGE'

'1Q GAIN MUTATION STATUS' versus 'PATHOLOGY.T.STAGE'

P value = 9.11e-05 (Fisher's exact test), Q value = 0.041

Table S3. Gene #1: '1Q GAIN MUTATION STATUS' versus Clinical Feature #4: 'PATHOLOGY.T.STAGE'

nPatients	T1	T2	T3+T4
ALL	74	16	39
1Q GAIN MUTATED	1	0	10
1Q GAIN WILD-TYPE	73	16	29

Figure S3. Get High-res Image Gene #1: '1Q GAIN MUTATION STATUS' versus Clinical Feature #4: 'PATHOLOGY.T.STAGE'

'6Q GAIN MUTATION STATUS' versus 'Time to Death'

P value = 8.53e-06 (logrank test), Q value = 0.0039

Table S4. Gene #11: '6Q GAIN MUTATION STATUS' versus Clinical Feature #1: 'Time to Death'

	nPatients	nDeath	Duration Range (Median), Month
ALL	119	15	0.0 - 194.8 (13.7)
6Q GAIN MUTATED	3	2	7.9 - 13.6 (9.6)
6Q GAIN WILD-TYPE	116	13	0.0 - 194.8 (14.1)

Figure S4. Get High-res Image Gene #11: '6Q GAIN MUTATION STATUS' versus Clinical Feature #1: 'Time to Death'

'8Q GAIN MUTATION STATUS' versus 'Time to Death'

P value = 3.61e-05 (logrank test), Q value = 0.017

Table S5. Gene #15: '8Q GAIN MUTATION STATUS' versus Clinical Feature #1: 'Time to Death'

	nPatients	nDeath	Duration Range (Median), Month
ALL	119	15	0.0 - 194.8 (13.7)
8Q GAIN MUTATED	12	4	0.2 - 43.2 (6.8)
8Q GAIN WILD-TYPE	107	11	0.0 - 194.8 (14.6)

Figure S5. Get High-res Image Gene #15: '8Q GAIN MUTATION STATUS' versus Clinical Feature #1: 'Time to Death'

'17P GAIN MUTATION STATUS' versus 'PATHOLOGY.M.STAGE'

P value = 0.000167 (Fisher's exact test), Q value = 0.076

Table S6. Gene #25: '17P GAIN MUTATION STATUS' versus Clinical Feature #6: 'PATHOLOGY.M.STAGE'

nPatients	M0	M1	MX
ALL	57	6	57
17P GAIN MUTATED	22	1	41
17P GAIN WILD-TYPE	35	5	16

Figure S6. Get High-res Image Gene #25: '17P GAIN MUTATION STATUS' versus Clinical Feature #6: 'PATHOLOGY.M.STAGE'

'3Q LOSS MUTATION STATUS' versus 'Time to Death'

P value = 2.37e-06 (logrank test), Q value = 0.0011

Table S7. Gene #36: '3Q LOSS MUTATION STATUS' versus Clinical Feature #1: 'Time to Death'

	nPatients	nDeath	Duration Range (Median), Month
ALL	119	15	0.0 - 194.8 (13.7)
3Q LOSS MUTATED	3	2	3.7 - 21.6 (8.8)
3Q LOSS WILD-TYPE	116	13	0.0 - 194.8 (13.9)

Figure S7. Get High-res Image Gene #36: '3Q LOSS MUTATION STATUS' versus Clinical Feature #1: 'Time to Death'

'5P LOSS MUTATION STATUS' versus 'Time to Death'

P value = 0.000124 (logrank test), Q value = 0.056

Table S8. Gene #39: '5P LOSS MUTATION STATUS' versus Clinical Feature #1: 'Time to Death'

	nPatients	nDeath	Duration Range (Median), Month
ALL	119	15	0.0 - 194.8 (13.7)
5P LOSS MUTATED	6	2	0.0 - 22.9 (3.2)
5P LOSS WILD-TYPE	113	13	0.0 - 194.8 (14.1)

Figure S8. Get High-res Image Gene #39: '5P LOSS MUTATION STATUS' versus Clinical Feature #1: 'Time to Death'

'16P LOSS MUTATION STATUS' versus 'Time to Death'

P value = 4.28e-05 (logrank test), Q value = 0.02

Table S9. Gene #54: '16P LOSS MUTATION STATUS' versus Clinical Feature #1: 'Time to Death'

	nPatients	nDeath	Duration Range (Median), Month
ALL	119	15	0.0 - 194.8 (13.7)
16P LOSS MUTATED	3	2	0.7 - 21.6 (11.1)
16P LOSS WILD-TYPE	116	13	0.0 - 194.8 (13.9)

Figure S9. Get High-res Image Gene #54: '16P LOSS MUTATION STATUS' versus Clinical Feature #1: 'Time to Death'

'16Q LOSS MUTATION STATUS' versus 'Time to Death'

P value = 4.28e-05 (logrank test), Q value = 0.02

Table S10. Gene #55: '16Q LOSS MUTATION STATUS' versus Clinical Feature #1: 'Time to Death'

	nPatients	nDeath	Duration Range (Median), Month
ALL	119	15	0.0 - 194.8 (13.7)
16Q LOSS MUTATED	3	2	0.7 - 21.6 (11.1)
16Q LOSS WILD-TYPE	116	13	0.0 - 194.8 (13.9)

Figure S10. Get High-res Image Gene #55: '16Q LOSS MUTATION STATUS' versus Clinical Feature #1: 'Time to Death'

'17P LOSS MUTATION STATUS' versus 'Time to Death'

P value = 4.06e-09 (logrank test), Q value = 1.9e-06

Table S11. Gene #56: '17P LOSS MUTATION STATUS' versus Clinical Feature #1: 'Time to Death'

	nPatients	nDeath	Duration Range (Median), Month
ALL	119	15	0.0 - 194.8 (13.7)
17P LOSS MUTATED	5	3	0.2 - 11.3 (9.6)
17P LOSS WILD-TYPE	114	12	0.0 - 194.8 (14.4)

Figure S11. Get High-res Image Gene #56: '17P LOSS MUTATION STATUS' versus Clinical Feature #1: 'Time to Death'

Methods & Data

Input

Copy number data file = transformed.cor.cli.txt
Clinical data file = KIRP-TP.clin.merged.picked.txt
Number of patients = 129
Number of significantly arm-level cnvs = 63
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

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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