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

Thymoma (Primary solid tumor)

02 April 2015 | analyses__2015_04_02

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 (2015): Correlation between copy number variations of arm-level result and selected clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1416W5X

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 52 arm-level events and 5 clinical features across 121 patients, 26 significant findings detected with Q value < 0.25.

1q gain cnv correlated to 'Time to Death'.
3q gain cnv correlated to 'Time to Death'.
7p gain cnv correlated to 'Time to Death'.
7q gain cnv correlated to 'Time to Death'.
8p gain cnv correlated to 'Time to Death'.
8q gain cnv correlated to 'Time to Death'.
9p gain cnv correlated to 'YEARS_TO_BIRTH'.
9q gain cnv correlated to 'YEARS_TO_BIRTH'.
14q gain cnv correlated to 'YEARS_TO_BIRTH'.
xq gain cnv correlated to 'Time to Death'.
3p loss cnv correlated to 'ETHNICITY'.
3q loss cnv correlated to 'ETHNICITY'.
6p loss cnv correlated to 'ETHNICITY'.
6q loss cnv correlated to 'ETHNICITY'.
11p loss cnv correlated to 'ETHNICITY'.
11q loss cnv correlated to 'YEARS_TO_BIRTH' and 'ETHNICITY'.
12q loss cnv correlated to 'YEARS_TO_BIRTH'.
16q loss cnv correlated to 'Time to Death'.
17p loss cnv correlated to 'ETHNICITY'.
17q loss cnv correlated to 'ETHNICITY'.
19p loss cnv correlated to 'ETHNICITY'.
19q loss cnv correlated to 'ETHNICITY'.
22q loss cnv correlated to 'ETHNICITY'.
xp loss cnv correlated to 'Time to Death'.
xq loss cnv correlated to 'ETHNICITY'.

Results

Overview of the results

Table 1. Get Full Table Overview of the association between significant copy number variation of 52 arm-level events and 5 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 26 significant findings detected.


		Clinical Features	Time to Death	YEARS TO BIRTH	GENDER	RACE	ETHNICITY
	nCNV (%)	nWild-Type	logrank test	Wilcoxon-test	Fisher's exact test	Fisher's exact test	Fisher's exact test
11q loss	7 (6%)	114	0.506 (1.00)	0.0117 (0.215)	0.44 (1.00)	0.712 (1.00)	0.0124 (0.215)
1q gain	22 (18%)	99	7.34e-06 (0.0011)	0.462 (1.00)	0.348 (0.896)	0.361 (0.896)	0.674 (1.00)
3q gain	5 (4%)	116	8.43e-06 (0.0011)	0.101 (0.523)	0.674 (1.00)	1 (1.00)	1 (1.00)
7p gain	16 (13%)	105	0.0208 (0.219)	0.323 (0.872)	1 (1.00)	1 (1.00)	1 (1.00)
7q gain	16 (13%)	105	0.0208 (0.219)	0.323 (0.872)	1 (1.00)	1 (1.00)	1 (1.00)
8p gain	12 (10%)	109	0.021 (0.219)	0.224 (0.732)	0.364 (0.896)	0.808 (1.00)	1 (1.00)
8q gain	12 (10%)	109	0.021 (0.219)	0.224 (0.732)	0.364 (0.896)	0.806 (1.00)	1 (1.00)
9p gain	11 (9%)	110	0.206 (0.713)	0.00177 (0.115)	1 (1.00)	0.0343 (0.288)	0.597 (1.00)
9q gain	11 (9%)	110	0.206 (0.713)	0.00177 (0.115)	1 (1.00)	0.034 (0.288)	0.597 (1.00)
14q gain	13 (11%)	108	0.2 (0.713)	0.0141 (0.216)	0.774 (1.00)	0.807 (1.00)	0.597 (1.00)
xq gain	5 (4%)	116	0.0244 (0.244)	0.379 (0.92)	0.674 (1.00)	1 (1.00)	1 (1.00)
3p loss	12 (10%)	109	0.468 (1.00)	0.201 (0.713)	0.763 (1.00)	1 (1.00)	0.00607 (0.183)
3q loss	7 (6%)	114	0.515 (1.00)	0.184 (0.713)	0.115 (0.524)	0.713 (1.00)	0.00741 (0.183)
6p loss	20 (17%)	101	0.118 (0.527)	0.0571 (0.403)	0.809 (1.00)	0.871 (1.00)	0.00646 (0.183)
6q loss	19 (16%)	102	0.0957 (0.508)	0.0811 (0.449)	0.805 (1.00)	0.572 (1.00)	0.00484 (0.183)
11p loss	9 (7%)	112	0.496 (1.00)	0.137 (0.576)	1 (1.00)	1 (1.00)	0.00252 (0.131)
12q loss	7 (6%)	114	0.607 (1.00)	0.0142 (0.216)	0.115 (0.524)	0.711 (1.00)	0.106 (0.523)
16q loss	13 (11%)	108	0.00925 (0.2)	0.771 (1.00)	0.774 (1.00)	0.827 (1.00)	0.0771 (0.449)
17p loss	14 (12%)	107	0.517 (1.00)	0.479 (1.00)	0.397 (0.947)	0.844 (1.00)	0.0163 (0.219)
17q loss	6 (5%)	115	0.692 (1.00)	0.191 (0.713)	0.68 (1.00)	0.654 (1.00)	0.00741 (0.183)
19p loss	3 (2%)	118	0.823 (1.00)	0.289 (0.86)	0.613 (1.00)	1 (1.00)	0.0182 (0.219)
19q loss	3 (2%)	118	0.823 (1.00)	0.289 (0.86)	0.613 (1.00)	1 (1.00)	0.0182 (0.219)
22q loss	13 (11%)	108	0.332 (0.882)	0.107 (0.523)	0.774 (1.00)	1 (1.00)	0.0121 (0.215)
xp loss	7 (6%)	114	0.00774 (0.183)	0.0678 (0.43)	1 (1.00)	1 (1.00)	0.0794 (0.449)
xq loss	4 (3%)	117	0.0301 (0.279)	0.219 (0.732)	0.356 (0.896)	1 (1.00)	0.0182 (0.219)
1p gain	8 (7%)	113	0.0434 (0.353)	0.933 (1.00)	0.484 (1.00)	1 (1.00)	0.106 (0.523)
5p gain	11 (9%)	110	0.0611 (0.403)	0.696 (1.00)	0.12 (0.527)	0.766 (1.00)	0.166 (0.654)
5q gain	9 (7%)	112	0.0505 (0.386)	0.601 (1.00)	0.0898 (0.487)	0.734 (1.00)	0.469 (1.00)
12p gain	4 (3%)	117	0.062 (0.403)	0.413 (0.95)	0.619 (1.00)	1 (1.00)	0.3 (0.86)
12q gain	4 (3%)	117	0.062 (0.403)	0.413 (0.95)	0.619 (1.00)	1 (1.00)	0.3 (0.86)
15q gain	12 (10%)	109	0.122 (0.527)	0.817 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)
17q gain	7 (6%)	114	0.529 (1.00)	0.622 (1.00)	1 (1.00)	0.714 (1.00)	1 (1.00)
18p gain	3 (2%)	118	0.841 (1.00)	0.65 (1.00)	1 (1.00)	1 (1.00)	0.234 (0.732)
18q gain	3 (2%)	118	0.841 (1.00)	0.65 (1.00)	1 (1.00)	1 (1.00)	0.234 (0.732)
19p gain	3 (2%)	118	0.704 (1.00)	0.325 (0.872)	0.613 (1.00)	1 (1.00)	1 (1.00)
19q gain	3 (2%)	118	0.704 (1.00)	0.325 (0.872)	0.613 (1.00)	1 (1.00)	1 (1.00)
20p gain	10 (8%)	111	0.41 (0.95)	0.924 (1.00)	1 (1.00)	0.602 (1.00)	0.198 (0.713)
20q gain	10 (8%)	111	0.41 (0.95)	0.924 (1.00)	1 (1.00)	0.608 (1.00)	0.198 (0.713)
21q gain	3 (2%)	118	0.888 (1.00)	0.232 (0.732)	0.113 (0.524)	1 (1.00)	1 (1.00)
22q gain	5 (4%)	116	0.723 (1.00)	0.318 (0.872)	0.2 (0.713)	0.587 (1.00)	1 (1.00)
xp gain	3 (2%)	118	0.864 (1.00)	0.686 (1.00)	0.113 (0.524)	1 (1.00)	1 (1.00)
1p loss	4 (3%)	117	0.639 (1.00)	0.0697 (0.432)	0.356 (0.896)	1 (1.00)	0.3 (0.86)
4p loss	5 (4%)	116	0.489 (1.00)	0.482 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)
4q loss	4 (3%)	117	0.508 (1.00)	0.907 (1.00)	0.619 (1.00)	1 (1.00)	1 (1.00)
9p loss	4 (3%)	117	0.841 (1.00)	0.14 (0.576)	0.356 (0.896)	1 (1.00)	0.3 (0.86)
10p loss	3 (2%)	118	0.823 (1.00)	0.301 (0.86)	0.613 (1.00)	1 (1.00)	0.234 (0.732)
12p loss	8 (7%)	113	0.582 (1.00)	0.033 (0.288)	0.274 (0.847)	1 (1.00)	0.135 (0.576)
13q loss	14 (12%)	107	0.387 (0.931)	0.219 (0.732)	0.778 (1.00)	0.844 (1.00)	0.0621 (0.403)
16p loss	5 (4%)	116	0.636 (1.00)	0.507 (1.00)	0.365 (0.896)	0.308 (0.87)	0.0554 (0.403)
18p loss	7 (6%)	114	0.155 (0.62)	0.853 (1.00)	0.713 (1.00)	1 (1.00)	0.0794 (0.449)
18q loss	7 (6%)	114	0.155 (0.62)	0.853 (1.00)	0.713 (1.00)	1 (1.00)	0.0794 (0.449)
21q loss	9 (7%)	112	0.58 (1.00)	0.0456 (0.36)	1 (1.00)	1 (1.00)	0.0272 (0.262)

'1q gain' versus 'Time to Death'

P value = 7.34e-06 (logrank test), Q value = 0.0011

Table S1. Gene #2: '1q gain' versus Clinical Feature #1: 'Time to Death'

	nPatients	nDeath	Duration Range (Median), Month
ALL	119	6	0.1 - 150.0 (30.7)
1Q GAIN MUTATED	22	5	0.1 - 114.7 (19.8)
1Q GAIN WILD-TYPE	97	1	0.2 - 150.0 (32.2)

Figure S1. Get High-res Image Gene #2: '1q gain' versus Clinical Feature #1: 'Time to Death'

'3q gain' versus 'Time to Death'

P value = 8.43e-06 (logrank test), Q value = 0.0011

Table S2. Gene #3: '3q gain' versus Clinical Feature #1: 'Time to Death'

	nPatients	nDeath	Duration Range (Median), Month
ALL	119	6	0.1 - 150.0 (30.7)
3Q GAIN MUTATED	5	2	0.3 - 88.8 (12.5)
3Q GAIN WILD-TYPE	114	4	0.1 - 150.0 (31.9)

Figure S2. Get High-res Image Gene #3: '3q gain' versus Clinical Feature #1: 'Time to Death'

'7p gain' versus 'Time to Death'

P value = 0.0208 (logrank test), Q value = 0.22

Table S3. Gene #6: '7p gain' versus Clinical Feature #1: 'Time to Death'

	nPatients	nDeath	Duration Range (Median), Month
ALL	119	6	0.1 - 150.0 (30.7)
7P GAIN MUTATED	16	3	0.2 - 114.7 (29.6)
7P GAIN WILD-TYPE	103	3	0.1 - 150.0 (30.7)

Figure S3. Get High-res Image Gene #6: '7p gain' versus Clinical Feature #1: 'Time to Death'

'7q gain' versus 'Time to Death'

P value = 0.0208 (logrank test), Q value = 0.22

Table S4. Gene #7: '7q gain' versus Clinical Feature #1: 'Time to Death'

	nPatients	nDeath	Duration Range (Median), Month
ALL	119	6	0.1 - 150.0 (30.7)
7Q GAIN MUTATED	16	3	0.2 - 114.7 (29.6)
7Q GAIN WILD-TYPE	103	3	0.1 - 150.0 (30.7)

Figure S4. Get High-res Image Gene #7: '7q gain' versus Clinical Feature #1: 'Time to Death'

'8p gain' versus 'Time to Death'

P value = 0.021 (logrank test), Q value = 0.22

Table S5. Gene #8: '8p gain' versus Clinical Feature #1: 'Time to Death'

	nPatients	nDeath	Duration Range (Median), Month
ALL	119	6	0.1 - 150.0 (30.7)
8P GAIN MUTATED	12	2	0.2 - 97.4 (24.6)
8P GAIN WILD-TYPE	107	4	0.1 - 150.0 (31.5)

Figure S5. Get High-res Image Gene #8: '8p gain' versus Clinical Feature #1: 'Time to Death'

'8q gain' versus 'Time to Death'

P value = 0.021 (logrank test), Q value = 0.22

Table S6. Gene #9: '8q gain' versus Clinical Feature #1: 'Time to Death'

	nPatients	nDeath	Duration Range (Median), Month
ALL	119	6	0.1 - 150.0 (30.7)
8Q GAIN MUTATED	12	2	0.2 - 97.4 (24.6)
8Q GAIN WILD-TYPE	107	4	0.1 - 150.0 (31.5)

Figure S6. Get High-res Image Gene #9: '8q gain' versus Clinical Feature #1: 'Time to Death'

'9p gain' versus 'YEARS_TO_BIRTH'

P value = 0.00177 (Wilcoxon-test), Q value = 0.12

Table S7. Gene #10: '9p gain' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

	nPatients	Mean (Std.Dev)
ALL	120	58.7 (12.7)
9P GAIN MUTATED	11	45.7 (15.0)
9P GAIN WILD-TYPE	109	60.0 (11.7)

Figure S7. Get High-res Image Gene #10: '9p gain' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

'9q gain' versus 'YEARS_TO_BIRTH'

P value = 0.00177 (Wilcoxon-test), Q value = 0.12

Table S8. Gene #11: '9q gain' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

	nPatients	Mean (Std.Dev)
ALL	120	58.7 (12.7)
9Q GAIN MUTATED	11	45.7 (15.0)
9Q GAIN WILD-TYPE	109	60.0 (11.7)

Figure S8. Get High-res Image Gene #11: '9q gain' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

'14q gain' versus 'YEARS_TO_BIRTH'

P value = 0.0141 (Wilcoxon-test), Q value = 0.22

Table S9. Gene #14: '14q gain' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

	nPatients	Mean (Std.Dev)
ALL	120	58.7 (12.7)
14Q GAIN MUTATED	13	49.4 (15.4)
14Q GAIN WILD-TYPE	107	59.8 (11.9)

Figure S9. Get High-res Image Gene #14: '14q gain' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

'xq gain' versus 'Time to Death'

P value = 0.0244 (logrank test), Q value = 0.24

Table S10. Gene #26: 'xq gain' versus Clinical Feature #1: 'Time to Death'

	nPatients	nDeath	Duration Range (Median), Month
ALL	119	6	0.1 - 150.0 (30.7)
XQ GAIN MUTATED	5	1	0.2 - 81.8 (5.2)
XQ GAIN WILD-TYPE	114	5	0.1 - 150.0 (31.9)

Figure S10. Get High-res Image Gene #26: 'xq gain' versus Clinical Feature #1: 'Time to Death'

'3p loss' versus 'ETHNICITY'

P value = 0.00607 (Fisher's exact test), Q value = 0.18

Table S11. Gene #28: '3p loss' versus Clinical Feature #5: 'ETHNICITY'

nPatients	HISPANIC OR LATINO	NOT HISPANIC OR LATINO
ALL	9	98
3P LOSS MUTATED	4	7
3P LOSS WILD-TYPE	5	91

Figure S11. Get High-res Image Gene #28: '3p loss' versus Clinical Feature #5: 'ETHNICITY'

'3q loss' versus 'ETHNICITY'

P value = 0.00741 (Fisher's exact test), Q value = 0.18

Table S12. Gene #29: '3q loss' versus Clinical Feature #5: 'ETHNICITY'

nPatients	HISPANIC OR LATINO	NOT HISPANIC OR LATINO
ALL	9	98
3Q LOSS MUTATED	3	3
3Q LOSS WILD-TYPE	6	95

Figure S12. Get High-res Image Gene #29: '3q loss' versus Clinical Feature #5: 'ETHNICITY'

'6p loss' versus 'ETHNICITY'

P value = 0.00646 (Fisher's exact test), Q value = 0.18

Table S13. Gene #32: '6p loss' versus Clinical Feature #5: 'ETHNICITY'

nPatients	HISPANIC OR LATINO	NOT HISPANIC OR LATINO
ALL	9	98
6P LOSS MUTATED	5	13
6P LOSS WILD-TYPE	4	85

Figure S13. Get High-res Image Gene #32: '6p loss' versus Clinical Feature #5: 'ETHNICITY'

'6q loss' versus 'ETHNICITY'

P value = 0.00484 (Fisher's exact test), Q value = 0.18

Table S14. Gene #33: '6q loss' versus Clinical Feature #5: 'ETHNICITY'

nPatients	HISPANIC OR LATINO	NOT HISPANIC OR LATINO
ALL	9	98
6Q LOSS MUTATED	5	12
6Q LOSS WILD-TYPE	4	86

Figure S14. Get High-res Image Gene #33: '6q loss' versus Clinical Feature #5: 'ETHNICITY'

'11p loss' versus 'ETHNICITY'

P value = 0.00252 (Fisher's exact test), Q value = 0.13

Table S15. Gene #36: '11p loss' versus Clinical Feature #5: 'ETHNICITY'

nPatients	HISPANIC OR LATINO	NOT HISPANIC OR LATINO
ALL	9	98
11P LOSS MUTATED	4	5
11P LOSS WILD-TYPE	5	93

Figure S15. Get High-res Image Gene #36: '11p loss' versus Clinical Feature #5: 'ETHNICITY'

'11q loss' versus 'YEARS_TO_BIRTH'

P value = 0.0117 (Wilcoxon-test), Q value = 0.21

Table S16. Gene #37: '11q loss' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

	nPatients	Mean (Std.Dev)
ALL	120	58.7 (12.7)
11Q LOSS MUTATED	7	44.4 (16.5)
11Q LOSS WILD-TYPE	113	59.5 (12.0)

Figure S16. Get High-res Image Gene #37: '11q loss' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

'11q loss' versus 'ETHNICITY'

P value = 0.0124 (Fisher's exact test), Q value = 0.21

Table S17. Gene #37: '11q loss' versus Clinical Feature #5: 'ETHNICITY'

nPatients	HISPANIC OR LATINO	NOT HISPANIC OR LATINO
ALL	9	98
11Q LOSS MUTATED	3	4
11Q LOSS WILD-TYPE	6	94

Figure S17. Get High-res Image Gene #37: '11q loss' versus Clinical Feature #5: 'ETHNICITY'

'12q loss' versus 'YEARS_TO_BIRTH'

P value = 0.0142 (Wilcoxon-test), Q value = 0.22

Table S18. Gene #39: '12q loss' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

	nPatients	Mean (Std.Dev)
ALL	120	58.7 (12.7)
12Q LOSS MUTATED	7	44.6 (17.0)
12Q LOSS WILD-TYPE	113	59.5 (11.9)

Figure S18. Get High-res Image Gene #39: '12q loss' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

'16q loss' versus 'Time to Death'

P value = 0.00925 (logrank test), Q value = 0.2

Table S19. Gene #42: '16q loss' versus Clinical Feature #1: 'Time to Death'

	nPatients	nDeath	Duration Range (Median), Month
ALL	119	6	0.1 - 150.0 (30.7)
16Q LOSS MUTATED	13	2	0.7 - 82.7 (21.1)
16Q LOSS WILD-TYPE	106	4	0.1 - 150.0 (32.3)

Figure S19. Get High-res Image Gene #42: '16q loss' versus Clinical Feature #1: 'Time to Death'

'17p loss' versus 'ETHNICITY'

P value = 0.0163 (Fisher's exact test), Q value = 0.22

Table S20. Gene #43: '17p loss' versus Clinical Feature #5: 'ETHNICITY'

nPatients	HISPANIC OR LATINO	NOT HISPANIC OR LATINO
ALL	9	98
17P LOSS MUTATED	4	10
17P LOSS WILD-TYPE	5	88

Figure S20. Get High-res Image Gene #43: '17p loss' versus Clinical Feature #5: 'ETHNICITY'

'17q loss' versus 'ETHNICITY'

P value = 0.00741 (Fisher's exact test), Q value = 0.18

Table S21. Gene #44: '17q loss' versus Clinical Feature #5: 'ETHNICITY'

nPatients	HISPANIC OR LATINO	NOT HISPANIC OR LATINO
ALL	9	98
17Q LOSS MUTATED	3	3
17Q LOSS WILD-TYPE	6	95

Figure S21. Get High-res Image Gene #44: '17q loss' versus Clinical Feature #5: 'ETHNICITY'

'19p loss' versus 'ETHNICITY'

P value = 0.0182 (Fisher's exact test), Q value = 0.22

Table S22. Gene #47: '19p loss' versus Clinical Feature #5: 'ETHNICITY'

nPatients	HISPANIC OR LATINO	NOT HISPANIC OR LATINO
ALL	9	98
19P LOSS MUTATED	2	1
19P LOSS WILD-TYPE	7	97

Figure S22. Get High-res Image Gene #47: '19p loss' versus Clinical Feature #5: 'ETHNICITY'

'19q loss' versus 'ETHNICITY'

P value = 0.0182 (Fisher's exact test), Q value = 0.22

Table S23. Gene #48: '19q loss' versus Clinical Feature #5: 'ETHNICITY'

nPatients	HISPANIC OR LATINO	NOT HISPANIC OR LATINO
ALL	9	98
19Q LOSS MUTATED	2	1
19Q LOSS WILD-TYPE	7	97

Figure S23. Get High-res Image Gene #48: '19q loss' versus Clinical Feature #5: 'ETHNICITY'

'22q loss' versus 'ETHNICITY'

P value = 0.0121 (Fisher's exact test), Q value = 0.21

Table S24. Gene #50: '22q loss' versus Clinical Feature #5: 'ETHNICITY'

nPatients	HISPANIC OR LATINO	NOT HISPANIC OR LATINO
ALL	9	98
22Q LOSS MUTATED	4	9
22Q LOSS WILD-TYPE	5	89

Figure S24. Get High-res Image Gene #50: '22q loss' versus Clinical Feature #5: 'ETHNICITY'

'xp loss' versus 'Time to Death'

P value = 0.00774 (logrank test), Q value = 0.18

Table S25. Gene #51: 'xp loss' versus Clinical Feature #1: 'Time to Death'

	nPatients	nDeath	Duration Range (Median), Month
ALL	119	6	0.1 - 150.0 (30.7)
XP LOSS MUTATED	7	2	0.2 - 88.8 (39.5)
XP LOSS WILD-TYPE	112	4	0.1 - 150.0 (30.4)

Figure S25. Get High-res Image Gene #51: 'xp loss' versus Clinical Feature #1: 'Time to Death'

'xq loss' versus 'ETHNICITY'

P value = 0.0182 (Fisher's exact test), Q value = 0.22

Table S26. Gene #52: 'xq loss' versus Clinical Feature #5: 'ETHNICITY'

nPatients	HISPANIC OR LATINO	NOT HISPANIC OR LATINO
ALL	9	98
XQ LOSS MUTATED	2	1
XQ LOSS WILD-TYPE	7	97

Figure S26. Get High-res Image Gene #52: 'xq loss' versus Clinical Feature #5: 'ETHNICITY'

Methods & Data

Input

Copy number data file = broad_values_by_arm.txt from GISTIC pipeline
Processed Copy number data file = /xchip/cga/gdac-prod/tcga-gdac/jobResults/GDAC_Correlate_Genomic_Events_Preprocess/THYM-TP/15104466/transformed.cor.cli.txt
Clinical data file = /xchip/cga/gdac-prod/tcga-gdac/jobResults/Append_Data/THYM-TP/15092844/THYM-TP.merged_data.txt
Number of patients = 121
Number of significantly arm-level cnvs = 52
Number of selected clinical features = 5
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

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] 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)

[3] 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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