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

Brain Lower Grade Glioma (Primary solid tumor)

15 January 2014 | analyses__2014_01_15

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 (2014): Correlation between copy number variations of arm-level result and selected clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1RV0M4R

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 72 arm-level events and 6 clinical features across 276 patients, 18 significant findings detected with Q value < 0.25.

3q gain cnv correlated to 'Time to Death'.
7p gain cnv correlated to 'AGE'.
7q gain cnv correlated to 'AGE'.
19q gain cnv correlated to 'Time to Death'.
20p gain cnv correlated to 'Time to Death' and 'AGE'.
20q gain cnv correlated to 'Time to Death' and 'AGE'.
1p loss cnv correlated to 'HISTOLOGICAL.TYPE'.
6p loss cnv correlated to 'Time to Death'.
6q loss cnv correlated to 'Time to Death'.
9p loss cnv correlated to 'Time to Death'.
10p loss cnv correlated to 'Time to Death' and 'AGE'.
10q loss cnv correlated to 'Time to Death' and 'AGE'.
11q loss cnv correlated to 'Time to Death'.
19q loss 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 72 arm-level events and 6 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 18 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
20p gain	24 (9%)	252	1.78e-07 (7.52e-05)	3.27e-05 (0.0137)	0.521 (1.00)	0.891 (1.00)	0.588 (1.00)	0.823 (1.00)
20q gain	25 (9%)	251	1.23e-07 (5.2e-05)	0.000317 (0.131)	0.148 (1.00)	0.678 (1.00)	0.722 (1.00)	0.823 (1.00)
10p loss	44 (16%)	232	4.5e-13 (1.92e-10)	1.92e-10 (8.15e-08)	0.0697 (1.00)	0.0763 (1.00)	0.00125 (0.509)	0.486 (1.00)
10q loss	52 (19%)	224	3.22e-06 (0.00135)	3.11e-09 (1.32e-06)	0.0315 (1.00)	0.222 (1.00)	0.00181 (0.733)	0.624 (1.00)
3q gain	7 (3%)	269	8.71e-05 (0.0363)	0.0968 (1.00)	0.707 (1.00)	0.305 (1.00)	0.0718 (1.00)	0.685 (1.00)
7p gain	68 (25%)	208	0.00425 (1.00)	0.000127 (0.0527)	0.208 (1.00)	0.473 (1.00)	0.249 (1.00)	0.552 (1.00)
7q gain	85 (31%)	191	0.00186 (0.748)	1.64e-06 (0.000688)	0.15 (1.00)	0.227 (1.00)	0.205 (1.00)	0.677 (1.00)
19q gain	14 (5%)	262	0.000574 (0.236)	0.00177 (0.717)	0.584 (1.00)	0.741 (1.00)	0.158 (1.00)	0.774 (1.00)
1p loss	94 (34%)	182	0.0766 (1.00)	0.0102 (1.00)	0.525 (1.00)	0.668 (1.00)	1.67e-22 (7.15e-20)	0.057 (1.00)
6p loss	18 (7%)	258	7.16e-05 (0.0299)	0.468 (1.00)	1 (1.00)	0.384 (1.00)	0.0979 (1.00)	0.798 (1.00)
6q loss	35 (13%)	241	0.000547 (0.225)	0.0864 (1.00)	0.587 (1.00)	0.147 (1.00)	0.00121 (0.495)	0.176 (1.00)
9p loss	63 (23%)	213	0.000449 (0.185)	0.0389 (1.00)	0.195 (1.00)	0.37 (1.00)	0.149 (1.00)	0.0466 (1.00)
11q loss	13 (5%)	263	0.00021 (0.0871)	0.39 (1.00)	0.582 (1.00)	0.127 (1.00)	0.157 (1.00)	0.235 (1.00)
19q loss	110 (40%)	166	0.246 (1.00)	0.0909 (1.00)	0.902 (1.00)	0.699 (1.00)	8.9e-19 (3.8e-16)	0.188 (1.00)
1p gain	9 (3%)	267	0.002 (0.803)	0.0454 (1.00)	0.31 (1.00)	0.0178 (1.00)	0.00986 (1.00)	1 (1.00)
1q gain	14 (5%)	262	0.43 (1.00)	0.000704 (0.289)	0.179 (1.00)	0.241 (1.00)	0.325 (1.00)	0.774 (1.00)
2p gain	6 (2%)	270	0.575 (1.00)	0.135 (1.00)	1 (1.00)	0.406 (1.00)	0.671 (1.00)	1 (1.00)
2q gain	5 (2%)	271	0.897 (1.00)	0.287 (1.00)	0.664 (1.00)	0.406 (1.00)	0.525 (1.00)	0.659 (1.00)
3p gain	7 (3%)	269	0.00604 (1.00)	0.102 (1.00)	0.254 (1.00)	0.773 (1.00)	0.183 (1.00)	0.685 (1.00)
4p gain	6 (2%)	270	0.32 (1.00)	0.974 (1.00)	0.223 (1.00)	0.854 (1.00)	0.156 (1.00)	0.668 (1.00)
6p gain	5 (2%)	271	0.736 (1.00)	0.332 (1.00)	0.184 (1.00)	0.0178 (1.00)	0.525 (1.00)	1 (1.00)
8p gain	24 (9%)	252	0.418 (1.00)	0.995 (1.00)	0.0908 (1.00)	0.546 (1.00)	0.305 (1.00)	0.823 (1.00)
8q gain	31 (11%)	245	0.424 (1.00)	0.249 (1.00)	0.127 (1.00)	0.163 (1.00)	0.0317 (1.00)	1 (1.00)
9p gain	10 (4%)	266	0.0062 (1.00)	0.023 (1.00)	0.195 (1.00)	0.866 (1.00)	0.781 (1.00)	1 (1.00)
9q gain	12 (4%)	264	0.0016 (0.651)	0.0345 (1.00)	0.0143 (1.00)	0.708 (1.00)	0.339 (1.00)	0.757 (1.00)
10p gain	30 (11%)	246	0.902 (1.00)	0.0257 (1.00)	0.0318 (1.00)	0.00466 (1.00)	0.041 (1.00)	0.00362 (1.00)
10q gain	4 (1%)	272	0.74 (1.00)	0.104 (1.00)	0.127 (1.00)		0.234 (1.00)	0.1 (1.00)
11p gain	19 (7%)	257	0.692 (1.00)	0.0488 (1.00)	0.343 (1.00)	0.739 (1.00)	0.498 (1.00)	1 (1.00)
11q gain	32 (12%)	244	0.78 (1.00)	0.024 (1.00)	0.259 (1.00)	0.922 (1.00)	0.572 (1.00)	1 (1.00)
12p gain	23 (8%)	253	0.548 (1.00)	0.825 (1.00)	0.131 (1.00)	0.358 (1.00)	1 (1.00)	0.643 (1.00)
12q gain	10 (4%)	266	0.0199 (1.00)	0.435 (1.00)	0.351 (1.00)		0.92 (1.00)	0.509 (1.00)
14q gain	3 (1%)	273	0.491 (1.00)	0.371 (1.00)	1 (1.00)		1 (1.00)	0.244 (1.00)
15q gain	4 (1%)	272	0.347 (1.00)	0.0736 (1.00)	0.627 (1.00)	0.386 (1.00)	0.687 (1.00)	0.597 (1.00)
16p gain	10 (4%)	266	0.284 (1.00)	0.109 (1.00)	1 (1.00)	0.617 (1.00)	0.156 (1.00)	0.732 (1.00)
16q gain	11 (4%)	265	0.135 (1.00)	0.284 (1.00)	0.759 (1.00)	0.386 (1.00)	0.085 (1.00)	0.341 (1.00)
17p gain	8 (3%)	268	0.0639 (1.00)	0.119 (1.00)	0.295 (1.00)	0.915 (1.00)	0.161 (1.00)	0.715 (1.00)
17q gain	9 (3%)	267	0.0704 (1.00)	0.25 (1.00)	0.513 (1.00)	0.763 (1.00)	0.528 (1.00)	1 (1.00)
18p gain	9 (3%)	267	0.0637 (1.00)	0.878 (1.00)	1 (1.00)	0.143 (1.00)	0.296 (1.00)	0.723 (1.00)
18q gain	7 (3%)	269	0.129 (1.00)	0.568 (1.00)	1 (1.00)	0.224 (1.00)	0.889 (1.00)	0.435 (1.00)
19p gain	49 (18%)	227	0.26 (1.00)	0.00213 (0.852)	0.876 (1.00)	0.608 (1.00)	0.00732 (1.00)	0.867 (1.00)
21q gain	14 (5%)	262	0.355 (1.00)	0.0903 (1.00)	0.789 (1.00)	0.391 (1.00)	0.206 (1.00)	0.774 (1.00)
22q gain	7 (3%)	269	0.251 (1.00)	0.232 (1.00)	0.707 (1.00)	0.773 (1.00)	0.061 (1.00)	0.685 (1.00)
xq gain	23 (8%)	253	0.518 (1.00)	0.401 (1.00)	0.0787 (1.00)	0.536 (1.00)	0.306 (1.00)	0.489 (1.00)
1q loss	15 (5%)	261	0.867 (1.00)	0.059 (1.00)	0.603 (1.00)	0.0921 (1.00)	0.0299 (1.00)	0.573 (1.00)
2p loss	11 (4%)	265	0.17 (1.00)	0.553 (1.00)	0.234 (1.00)	0.564 (1.00)	0.5 (1.00)	1 (1.00)
2q loss	10 (4%)	266	0.851 (1.00)	0.0436 (1.00)	0.351 (1.00)	0.816 (1.00)	0.172 (1.00)	1 (1.00)
3p loss	13 (5%)	263	0.0298 (1.00)	0.385 (1.00)	0.777 (1.00)	0.0718 (1.00)	0.517 (1.00)	1 (1.00)
3q loss	17 (6%)	259	0.0454 (1.00)	0.806 (1.00)	0.21 (1.00)	0.599 (1.00)	0.736 (1.00)	0.792 (1.00)
4p loss	43 (16%)	233	0.829 (1.00)	0.00398 (1.00)	0.619 (1.00)	0.4 (1.00)	0.0165 (1.00)	0.724 (1.00)
4q loss	54 (20%)	222	0.711 (1.00)	0.115 (1.00)	0.447 (1.00)	0.626 (1.00)	0.00958 (1.00)	0.628 (1.00)
5p loss	26 (9%)	250	0.468 (1.00)	0.0875 (1.00)	0.837 (1.00)	0.225 (1.00)	0.015 (1.00)	0.125 (1.00)
5q loss	23 (8%)	253	0.113 (1.00)	0.459 (1.00)	0.663 (1.00)	0.751 (1.00)	0.179 (1.00)	0.106 (1.00)
8p loss	10 (4%)	266	0.04 (1.00)	0.288 (1.00)	0.757 (1.00)	0.447 (1.00)	0.156 (1.00)	0.732 (1.00)
8q loss	7 (3%)	269	0.00718 (1.00)	0.454 (1.00)	0.707 (1.00)	0.391 (1.00)	0.43 (1.00)	1 (1.00)
9q loss	25 (9%)	251	0.00717 (1.00)	0.111 (1.00)	0.675 (1.00)	0.0775 (1.00)	0.747 (1.00)	1 (1.00)
11p loss	38 (14%)	238	0.285 (1.00)	0.166 (1.00)	0.387 (1.00)	0.812 (1.00)	0.166 (1.00)	0.852 (1.00)
12p loss	13 (5%)	263	0.673 (1.00)	0.372 (1.00)	0.582 (1.00)	0.251 (1.00)	0.211 (1.00)	0.762 (1.00)
12q loss	26 (9%)	250	0.566 (1.00)	0.6 (1.00)	0.685 (1.00)	0.599 (1.00)	0.0527 (1.00)	0.511 (1.00)
13q loss	68 (25%)	208	0.272 (1.00)	0.607 (1.00)	0.401 (1.00)	0.837 (1.00)	0.133 (1.00)	0.0376 (1.00)
14q loss	39 (14%)	237	0.00301 (1.00)	0.00813 (1.00)	0.303 (1.00)	0.143 (1.00)	0.388 (1.00)	0.712 (1.00)
15q loss	22 (8%)	254	0.313 (1.00)	0.545 (1.00)	0.38 (1.00)	0.732 (1.00)	0.96 (1.00)	0.642 (1.00)
16p loss	8 (3%)	268	0.208 (1.00)	0.00922 (1.00)	0.73 (1.00)	0.194 (1.00)	1 (1.00)	1 (1.00)
16q loss	14 (5%)	262	0.0727 (1.00)	0.00446 (1.00)	0.789 (1.00)	0.816 (1.00)	0.736 (1.00)	0.774 (1.00)
17p loss	12 (4%)	264	0.000774 (0.317)	0.0538 (1.00)	0.395 (1.00)	0.0247 (1.00)	0.653 (1.00)	0.348 (1.00)
17q loss	8 (3%)	268	0.0369 (1.00)	0.177 (1.00)	1 (1.00)	0.158 (1.00)	0.493 (1.00)	1 (1.00)
18p loss	36 (13%)	240	0.749 (1.00)	0.221 (1.00)	0.0501 (1.00)	0.484 (1.00)	0.501 (1.00)	1 (1.00)
18q loss	34 (12%)	242	0.491 (1.00)	0.227 (1.00)	0.202 (1.00)	0.68 (1.00)	0.244 (1.00)	1 (1.00)
19p loss	15 (5%)	261	0.913 (1.00)	0.222 (1.00)	0.426 (1.00)	0.501 (1.00)	0.844 (1.00)	0.258 (1.00)
20p loss	3 (1%)	273	0.531 (1.00)	0.52 (1.00)	0.596 (1.00)		1 (1.00)	1 (1.00)
21q loss	20 (7%)	256	0.701 (1.00)	0.503 (1.00)	0.245 (1.00)	0.0765 (1.00)	0.0534 (1.00)	0.321 (1.00)
22q loss	31 (11%)	245	0.0225 (1.00)	0.00902 (1.00)	0.182 (1.00)	0.0332 (1.00)	0.192 (1.00)	0.839 (1.00)
xq loss	35 (13%)	241	0.14 (1.00)	0.404 (1.00)	0.72 (1.00)	0.607 (1.00)	0.241 (1.00)	0.847 (1.00)

'3q gain' versus 'Time to Death'

P value = 8.71e-05 (logrank test), Q value = 0.036

Table S1. Gene #6: '3q gain' versus Clinical Feature #1: 'Time to Death'

	nPatients	nDeath	Duration Range (Median), Month
ALL	275	59	0.0 - 211.2 (15.4)
3Q GAIN MUTATED	7	4	0.2 - 41.1 (8.8)
3Q GAIN WILD-TYPE	268	55	0.0 - 211.2 (15.4)

Figure S1. Get High-res Image Gene #6: '3q gain' versus Clinical Feature #1: 'Time to Death'

'7p gain' versus 'AGE'

P value = 0.000127 (t-test), Q value = 0.053

Table S2. Gene #9: '7p gain' versus Clinical Feature #2: 'AGE'

	nPatients	Mean (Std.Dev)
ALL	276	43.1 (13.3)
7P GAIN MUTATED	68	48.6 (13.1)
7P GAIN WILD-TYPE	208	41.3 (13.0)

Figure S2. Get High-res Image Gene #9: '7p gain' versus Clinical Feature #2: 'AGE'

'7q gain' versus 'AGE'

P value = 1.64e-06 (t-test), Q value = 0.00069

Table S3. Gene #10: '7q gain' versus Clinical Feature #2: 'AGE'

	nPatients	Mean (Std.Dev)
ALL	276	43.1 (13.3)
7Q GAIN MUTATED	85	49.0 (13.2)
7Q GAIN WILD-TYPE	191	40.5 (12.6)

Figure S3. Get High-res Image Gene #10: '7q gain' versus Clinical Feature #2: 'AGE'

'19q gain' versus 'Time to Death'

P value = 0.000574 (logrank test), Q value = 0.24

Table S4. Gene #30: '19q gain' versus Clinical Feature #1: 'Time to Death'

	nPatients	nDeath	Duration Range (Median), Month
ALL	275	59	0.0 - 211.2 (15.4)
19Q GAIN MUTATED	14	5	0.5 - 26.3 (14.1)
19Q GAIN WILD-TYPE	261	54	0.0 - 211.2 (15.4)

Figure S4. Get High-res Image Gene #30: '19q gain' versus Clinical Feature #1: 'Time to Death'

'20p gain' versus 'Time to Death'

P value = 1.78e-07 (logrank test), Q value = 7.5e-05

Table S5. Gene #31: '20p gain' versus Clinical Feature #1: 'Time to Death'

	nPatients	nDeath	Duration Range (Median), Month
ALL	275	59	0.0 - 211.2 (15.4)
20P GAIN MUTATED	24	10	0.5 - 41.1 (12.3)
20P GAIN WILD-TYPE	251	49	0.0 - 211.2 (15.5)

Figure S5. Get High-res Image Gene #31: '20p gain' versus Clinical Feature #1: 'Time to Death'

'20p gain' versus 'AGE'

P value = 3.27e-05 (t-test), Q value = 0.014

Table S6. Gene #31: '20p gain' versus Clinical Feature #2: 'AGE'

	nPatients	Mean (Std.Dev)
ALL	276	43.1 (13.3)
20P GAIN MUTATED	24	53.5 (10.7)
20P GAIN WILD-TYPE	252	42.1 (13.2)

Figure S6. Get High-res Image Gene #31: '20p gain' versus Clinical Feature #2: 'AGE'

'20q gain' versus 'Time to Death'

P value = 1.23e-07 (logrank test), Q value = 5.2e-05

Table S7. Gene #32: '20q gain' versus Clinical Feature #1: 'Time to Death'

	nPatients	nDeath	Duration Range (Median), Month
ALL	275	59	0.0 - 211.2 (15.4)
20Q GAIN MUTATED	25	10	0.5 - 41.1 (12.4)
20Q GAIN WILD-TYPE	250	49	0.0 - 211.2 (15.5)

Figure S7. Get High-res Image Gene #32: '20q gain' versus Clinical Feature #1: 'Time to Death'

'20q gain' versus 'AGE'

P value = 0.000317 (t-test), Q value = 0.13

Table S8. Gene #32: '20q gain' versus Clinical Feature #2: 'AGE'

	nPatients	Mean (Std.Dev)
ALL	276	43.1 (13.3)
20Q GAIN MUTATED	25	52.5 (12.0)
20Q GAIN WILD-TYPE	251	42.2 (13.1)

Figure S8. Get High-res Image Gene #32: '20q gain' versus Clinical Feature #2: 'AGE'

'1p loss' versus 'HISTOLOGICAL.TYPE'

P value = 1.67e-22 (Fisher's exact test), Q value = 7.1e-20

Table S9. Gene #36: '1p loss' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

nPatients	ASTROCYTOMA	OLIGOASTROCYTOMA	OLIGODENDROGLIOMA
ALL	88	76	112
1P LOSS MUTATED	5	14	75
1P LOSS WILD-TYPE	83	62	37

Figure S9. Get High-res Image Gene #36: '1p loss' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

'6p loss' versus 'Time to Death'

P value = 7.16e-05 (logrank test), Q value = 0.03

Table S10. Gene #46: '6p loss' versus Clinical Feature #1: 'Time to Death'

	nPatients	nDeath	Duration Range (Median), Month
ALL	275	59	0.0 - 211.2 (15.4)
6P LOSS MUTATED	18	7	0.2 - 46.6 (15.6)
6P LOSS WILD-TYPE	257	52	0.0 - 211.2 (15.3)

Figure S10. Get High-res Image Gene #46: '6p loss' versus Clinical Feature #1: 'Time to Death'

'6q loss' versus 'Time to Death'

P value = 0.000547 (logrank test), Q value = 0.23

Table S11. Gene #47: '6q loss' versus Clinical Feature #1: 'Time to Death'

	nPatients	nDeath	Duration Range (Median), Month
ALL	275	59	0.0 - 211.2 (15.4)
6Q LOSS MUTATED	35	10	0.1 - 57.9 (17.3)
6Q LOSS WILD-TYPE	240	49	0.0 - 211.2 (15.1)

Figure S11. Get High-res Image Gene #47: '6q loss' versus Clinical Feature #1: 'Time to Death'

'9p loss' versus 'Time to Death'

P value = 0.000449 (logrank test), Q value = 0.19

Table S12. Gene #50: '9p loss' versus Clinical Feature #1: 'Time to Death'

	nPatients	nDeath	Duration Range (Median), Month
ALL	275	59	0.0 - 211.2 (15.4)
9P LOSS MUTATED	63	21	0.1 - 117.4 (14.9)
9P LOSS WILD-TYPE	212	38	0.0 - 211.2 (15.4)

Figure S12. Get High-res Image Gene #50: '9p loss' versus Clinical Feature #1: 'Time to Death'

'10p loss' versus 'Time to Death'

P value = 4.5e-13 (logrank test), Q value = 1.9e-10

Table S13. Gene #52: '10p loss' versus Clinical Feature #1: 'Time to Death'

	nPatients	nDeath	Duration Range (Median), Month
ALL	275	59	0.0 - 211.2 (15.4)
10P LOSS MUTATED	44	21	0.1 - 134.3 (12.2)
10P LOSS WILD-TYPE	231	38	0.0 - 211.2 (16.0)

Figure S13. Get High-res Image Gene #52: '10p loss' versus Clinical Feature #1: 'Time to Death'

'10p loss' versus 'AGE'

P value = 1.92e-10 (t-test), Q value = 8.1e-08

Table S14. Gene #52: '10p loss' versus Clinical Feature #2: 'AGE'

	nPatients	Mean (Std.Dev)
ALL	276	43.1 (13.3)
10P LOSS MUTATED	44	54.9 (11.1)
10P LOSS WILD-TYPE	232	40.9 (12.5)

Figure S14. Get High-res Image Gene #52: '10p loss' versus Clinical Feature #2: 'AGE'

'10q loss' versus 'Time to Death'

P value = 3.22e-06 (logrank test), Q value = 0.0014

Table S15. Gene #53: '10q loss' versus Clinical Feature #1: 'Time to Death'

	nPatients	nDeath	Duration Range (Median), Month
ALL	275	59	0.0 - 211.2 (15.4)
10Q LOSS MUTATED	52	25	0.1 - 156.2 (14.1)
10Q LOSS WILD-TYPE	223	34	0.0 - 211.2 (15.7)

Figure S15. Get High-res Image Gene #53: '10q loss' versus Clinical Feature #1: 'Time to Death'

'10q loss' versus 'AGE'

P value = 3.11e-09 (t-test), Q value = 1.3e-06

Table S16. Gene #53: '10q loss' versus Clinical Feature #2: 'AGE'

	nPatients	Mean (Std.Dev)
ALL	276	43.1 (13.3)
10Q LOSS MUTATED	52	53.4 (12.3)
10Q LOSS WILD-TYPE	224	40.7 (12.4)

Figure S16. Get High-res Image Gene #53: '10q loss' versus Clinical Feature #2: 'AGE'

'11q loss' versus 'Time to Death'

P value = 0.00021 (logrank test), Q value = 0.087

Table S17. Gene #55: '11q loss' versus Clinical Feature #1: 'Time to Death'

	nPatients	nDeath	Duration Range (Median), Month
ALL	275	59	0.0 - 211.2 (15.4)
11Q LOSS MUTATED	13	5	0.2 - 41.1 (15.0)
11Q LOSS WILD-TYPE	262	54	0.0 - 211.2 (15.4)

Figure S17. Get High-res Image Gene #55: '11q loss' versus Clinical Feature #1: 'Time to Death'

'19q loss' versus 'HISTOLOGICAL.TYPE'

P value = 8.9e-19 (Fisher's exact test), Q value = 3.8e-16

Table S18. Gene #68: '19q loss' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

nPatients	ASTROCYTOMA	OLIGOASTROCYTOMA	OLIGODENDROGLIOMA
ALL	88	76	112
19Q LOSS MUTATED	12	18	80
19Q LOSS WILD-TYPE	76	58	32

Figure S18. Get High-res Image Gene #68: '19q loss' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

Methods & Data

Input

Copy number data file = transformed.cor.cli.txt
Clinical data file = LGG-TP.merged_data.txt
Number of patients = 276
Number of significantly arm-level cnvs = 72
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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