Stomach Adenocarcinoma: Correlation between copy number variations of arm-level result and selected clinical features<BR>(primary solid tumor cohort)

Stomach Adenocarcinoma: Correlation between copy number variations of arm-level result and selected clinical features
(primary solid tumor cohort)

Maintained by TCGA GDAC Team (Broad Institute/MD Anderson Cancer Center/Harvard Medical School)

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 9 clinical features across 161 patients, 6 significant findings detected with Q value < 0.25.

20p gain cnv correlated to 'GENDER'.
20q gain cnv correlated to 'GENDER'.
1p loss cnv correlated to 'PATHOLOGICSPREAD(M)' and 'TUMOR.STAGE'.
12p loss cnv correlated to 'PATHOLOGY.N' and 'TUMOR.STAGE'.

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 9 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 6 significant findings detected.


		Clinical Features	Time to Death	AGE	GENDER	HISTOLOGICAL TYPE	PATHOLOGY T	PATHOLOGY N	PATHOLOGICSPREAD(M)	TUMOR STAGE	RADIATIONS RADIATION REGIMENINDICATION
	nCNV (%)	nWild-Type	logrank test	t-test	Fisher's exact test	Chi-square test	Fisher's exact test	Fisher's exact test	Fisher's exact test	Fisher's exact test	Fisher's exact test
1p loss	6 (4%)	155	0.00489 (1.00)	0.688 (1.00)	0.222 (1.00)	0.885 (1.00)	0.335 (1.00)	0.313 (1.00)	0.000111 (0.0726)	0.000345 (0.224)	1 (1.00)
12p loss	11 (7%)	150	0.174 (1.00)	0.705 (1.00)	0.527 (1.00)	0.361 (1.00)	0.0564 (1.00)	0.000243 (0.158)	0.46 (1.00)	0.000228 (0.148)	0.301 (1.00)
20p gain	61 (38%)	100	0.0693 (1.00)	0.207 (1.00)	0.000128 (0.0831)	0.685 (1.00)	0.0515 (1.00)	0.691 (1.00)	0.149 (1.00)	0.19 (1.00)	0.651 (1.00)
20q gain	75 (47%)	86	0.0524 (1.00)	0.134 (1.00)	0.00037 (0.24)	0.399 (1.00)	0.000745 (0.481)	0.264 (1.00)	0.0532 (1.00)	0.189 (1.00)	0.665 (1.00)
1p gain	6 (4%)	155		0.212 (1.00)	0.403 (1.00)	0.712 (1.00)	1 (1.00)	0.809 (1.00)	0.45 (1.00)	1 (1.00)	1 (1.00)
1q gain	19 (12%)	142	0.77 (1.00)	0.521 (1.00)	0.22 (1.00)	0.3 (1.00)	0.422 (1.00)	0.214 (1.00)	0.384 (1.00)	0.335 (1.00)	0.106 (1.00)
2p gain	10 (6%)	151	0.692 (1.00)	0.292 (1.00)	0.741 (1.00)	0.586 (1.00)	0.272 (1.00)	0.291 (1.00)	1 (1.00)	0.0578 (1.00)	1 (1.00)
2q gain	11 (7%)	150	0.406 (1.00)	0.588 (1.00)	0.527 (1.00)	0.605 (1.00)	0.532 (1.00)	0.291 (1.00)	0.831 (1.00)	0.213 (1.00)	1 (1.00)
3p gain	4 (2%)	157		0.543 (1.00)	0.648 (1.00)	0.862 (1.00)	0.856 (1.00)	0.394 (1.00)	1 (1.00)	0.529 (1.00)	1 (1.00)
3q gain	13 (8%)	148	0.377 (1.00)	0.0273 (1.00)	0.0157 (1.00)	0.484 (1.00)	1 (1.00)	0.767 (1.00)	0.503 (1.00)	1 (1.00)	1 (1.00)
4p gain	3 (2%)	158		0.159 (1.00)	0.273 (1.00)		0.0522 (1.00)	0.729 (1.00)	1 (1.00)	0.284 (1.00)	1 (1.00)
5p gain	26 (16%)	135	0.975 (1.00)	0.763 (1.00)	0.19 (1.00)	0.494 (1.00)	0.935 (1.00)	0.681 (1.00)	0.253 (1.00)	0.108 (1.00)	0.184 (1.00)
5q gain	6 (4%)	155	0.137 (1.00)	0.792 (1.00)	0.403 (1.00)	0.0419 (1.00)	0.901 (1.00)	0.877 (1.00)	1 (1.00)	0.594 (1.00)	1 (1.00)
6p gain	11 (7%)	150	0.788 (1.00)	0.838 (1.00)	0.758 (1.00)	0.799 (1.00)	0.243 (1.00)	0.727 (1.00)	1 (1.00)	0.453 (1.00)	1 (1.00)
6q gain	10 (6%)	151	0.35 (1.00)	0.891 (1.00)	1 (1.00)	0.78 (1.00)	0.354 (1.00)	0.746 (1.00)	0.661 (1.00)	0.719 (1.00)	1 (1.00)
7p gain	49 (30%)	112	0.524 (1.00)	0.0136 (1.00)	0.117 (1.00)	0.319 (1.00)	0.464 (1.00)	0.556 (1.00)	0.673 (1.00)	0.181 (1.00)	0.641 (1.00)
7q gain	44 (27%)	117	0.735 (1.00)	0.00432 (1.00)	0.37 (1.00)	0.446 (1.00)	0.204 (1.00)	0.643 (1.00)	0.255 (1.00)	0.157 (1.00)	1 (1.00)
8p gain	50 (31%)	111	0.599 (1.00)	0.0443 (1.00)	0.386 (1.00)	0.487 (1.00)	0.0857 (1.00)	0.585 (1.00)	0.0932 (1.00)	0.59 (1.00)	0.174 (1.00)
8q gain	68 (42%)	93	0.302 (1.00)	0.03 (1.00)	0.421 (1.00)	0.635 (1.00)	0.0122 (1.00)	0.191 (1.00)	0.153 (1.00)	0.258 (1.00)	0.651 (1.00)
9p gain	11 (7%)	150	0.844 (1.00)	0.319 (1.00)	0.353 (1.00)	0.708 (1.00)	0.051 (1.00)	0.127 (1.00)	1 (1.00)	0.00597 (1.00)	0.301 (1.00)
9q gain	15 (9%)	146	0.856 (1.00)	0.188 (1.00)	0.595 (1.00)	0.942 (1.00)	0.144 (1.00)	0.134 (1.00)	0.871 (1.00)	0.161 (1.00)	0.391 (1.00)
10p gain	23 (14%)	138	0.976 (1.00)	0.34 (1.00)	0.362 (1.00)	0.315 (1.00)	0.537 (1.00)	0.752 (1.00)	0.41 (1.00)	0.071 (1.00)	1 (1.00)
10q gain	10 (6%)	151	0.634 (1.00)	0.987 (1.00)	0.741 (1.00)	0.646 (1.00)	0.894 (1.00)	0.746 (1.00)	0.812 (1.00)	0.696 (1.00)	1 (1.00)
11p gain	4 (2%)	157		0.572 (1.00)	0.648 (1.00)	0.676 (1.00)	0.385 (1.00)	0.183 (1.00)	1 (1.00)	0.335 (1.00)	1 (1.00)
11q gain	8 (5%)	153	0.24 (1.00)	0.77 (1.00)	1 (1.00)	0.802 (1.00)	0.864 (1.00)	0.743 (1.00)	0.774 (1.00)	0.709 (1.00)	1 (1.00)
12p gain	15 (9%)	146	0.726 (1.00)	0.273 (1.00)	0.105 (1.00)	0.998 (1.00)	0.374 (1.00)	0.655 (1.00)	0.163 (1.00)	0.676 (1.00)	1 (1.00)
12q gain	10 (6%)	151	0.669 (1.00)	0.0563 (1.00)	0.741 (1.00)	0.309 (1.00)	0.894 (1.00)	0.152 (1.00)	0.812 (1.00)	0.61 (1.00)	0.277 (1.00)
13q gain	30 (19%)	131	0.331 (1.00)	0.731 (1.00)	0.222 (1.00)	0.501 (1.00)	0.676 (1.00)	0.474 (1.00)	0.617 (1.00)	0.69 (1.00)	1 (1.00)
15q gain	7 (4%)	154	0.178 (1.00)	0.414 (1.00)	0.243 (1.00)	0.364 (1.00)	0.569 (1.00)	0.0674 (1.00)	1 (1.00)	0.439 (1.00)	1 (1.00)
16p gain	12 (7%)	149	0.575 (1.00)	0.614 (1.00)	0.763 (1.00)	0.61 (1.00)	0.341 (1.00)	0.0675 (1.00)	0.118 (1.00)	0.00787 (1.00)	0.325 (1.00)
16q gain	8 (5%)	153	0.671 (1.00)	0.864 (1.00)	1 (1.00)	0.862 (1.00)	0.0719 (1.00)	0.354 (1.00)	0.195 (1.00)	0.0167 (1.00)	1 (1.00)
17p gain	6 (4%)	155	0.16 (1.00)	0.55 (1.00)	1 (1.00)	0.805 (1.00)	0.812 (1.00)	0.0818 (1.00)	0.0268 (1.00)	0.142 (1.00)	1 (1.00)
17q gain	9 (6%)	152	0.174 (1.00)	0.666 (1.00)	0.741 (1.00)	0.879 (1.00)	0.829 (1.00)	0.118 (1.00)	0.0225 (1.00)	0.197 (1.00)	1 (1.00)
18p gain	13 (8%)	148	0.61 (1.00)	0.564 (1.00)	1 (1.00)	0.813 (1.00)	1 (1.00)	0.0956 (1.00)	0.614 (1.00)	0.632 (1.00)	0.347 (1.00)
18q gain	7 (4%)	154	0.598 (1.00)	0.619 (1.00)	0.441 (1.00)	0.313 (1.00)	0.563 (1.00)	0.777 (1.00)	0.146 (1.00)	0.89 (1.00)	1 (1.00)
19p gain	10 (6%)	151	0.965 (1.00)	0.429 (1.00)	0.0155 (1.00)	0.536 (1.00)	0.806 (1.00)	0.0475 (1.00)	0.043 (1.00)	0.0455 (1.00)	1 (1.00)
19q gain	17 (11%)	144	0.309 (1.00)	0.214 (1.00)	0.121 (1.00)	0.509 (1.00)	0.404 (1.00)	0.105 (1.00)	0.219 (1.00)	0.0247 (1.00)	0.432 (1.00)
22q gain	3 (2%)	158	0.765 (1.00)	0.266 (1.00)	1 (1.00)	0.927 (1.00)	0.817 (1.00)	0.382 (1.00)	1 (1.00)	0.284 (1.00)	1 (1.00)
2p loss	3 (2%)	158			0.566 (1.00)		0.817 (1.00)	0.437 (1.00)	0.223 (1.00)	0.336 (1.00)	0.0909 (1.00)
2q loss	4 (2%)	157		0.867 (1.00)	1 (1.00)	0.308 (1.00)	0.614 (1.00)	0.0917 (1.00)	0.149 (1.00)	0.16 (1.00)	0.12 (1.00)
3p loss	10 (6%)	151	0.633 (1.00)	0.561 (1.00)	1 (1.00)	0.865 (1.00)	0.729 (1.00)	0.746 (1.00)	1 (1.00)	0.677 (1.00)	1 (1.00)
3q loss	6 (4%)	155	0.727 (1.00)	0.639 (1.00)	0.403 (1.00)	0.852 (1.00)	1 (1.00)	0.877 (1.00)	1 (1.00)	0.734 (1.00)	1 (1.00)
4p loss	24 (15%)	137	0.704 (1.00)	0.129 (1.00)	0.824 (1.00)	0.0812 (1.00)	0.0367 (1.00)	1 (1.00)	0.565 (1.00)	0.0682 (1.00)	0.161 (1.00)
4q loss	20 (12%)	141	0.748 (1.00)	0.338 (1.00)	0.466 (1.00)	0.0279 (1.00)	0.0243 (1.00)	0.837 (1.00)	1 (1.00)	0.301 (1.00)	0.117 (1.00)
5p loss	7 (4%)	154	0.415 (1.00)	0.607 (1.00)	1 (1.00)	0.022 (1.00)	0.614 (1.00)	0.375 (1.00)	1 (1.00)	0.397 (1.00)	1 (1.00)
5q loss	15 (9%)	146	0.12 (1.00)	0.5 (1.00)	0.286 (1.00)	0.000403 (0.26)	0.0522 (1.00)	0.903 (1.00)	0.242 (1.00)	0.181 (1.00)	0.391 (1.00)
6p loss	8 (5%)	153	0.958 (1.00)	0.0474 (1.00)	0.715 (1.00)	0.0136 (1.00)	0.134 (1.00)	0.166 (1.00)	0.578 (1.00)	0.229 (1.00)	1 (1.00)
6q loss	12 (7%)	149	0.611 (1.00)	0.218 (1.00)	0.763 (1.00)	0.191 (1.00)	0.202 (1.00)	0.428 (1.00)	0.85 (1.00)	0.0368 (1.00)	1 (1.00)
7p loss	3 (2%)	158	0.213 (1.00)	0.192 (1.00)	0.273 (1.00)	0.721 (1.00)	0.0916 (1.00)	0.0806 (1.00)	1 (1.00)	0.456 (1.00)	1 (1.00)
7q loss	5 (3%)	156	0.208 (1.00)	0.14 (1.00)	0.0819 (1.00)	0.454 (1.00)	0.379 (1.00)	0.477 (1.00)	1 (1.00)	0.929 (1.00)	1 (1.00)
8p loss	10 (6%)	151	0.27 (1.00)	0.439 (1.00)	0.741 (1.00)	0.0385 (1.00)	0.592 (1.00)	0.4 (1.00)	0.812 (1.00)	0.625 (1.00)	1 (1.00)
8q loss	3 (2%)	158		0.607 (1.00)	1 (1.00)	0.00448 (1.00)			1 (1.00)		1 (1.00)
9p loss	26 (16%)	135	0.0551 (1.00)	0.513 (1.00)	0.663 (1.00)	0.414 (1.00)	0.0526 (1.00)	0.357 (1.00)	1 (1.00)	0.625 (1.00)	0.591 (1.00)
9q loss	11 (7%)	150	0.199 (1.00)	0.368 (1.00)	1 (1.00)	0.675 (1.00)	0.187 (1.00)	0.212 (1.00)	0.831 (1.00)	0.968 (1.00)	0.301 (1.00)
10p loss	10 (6%)	151	0.203 (1.00)	0.355 (1.00)	0.318 (1.00)	0.0191 (1.00)	0.0663 (1.00)	0.452 (1.00)	0.661 (1.00)	0.342 (1.00)	0.0315 (1.00)
10q loss	9 (6%)	152	0.263 (1.00)	0.676 (1.00)	0.741 (1.00)	0.0248 (1.00)	0.302 (1.00)	0.652 (1.00)	0.792 (1.00)	0.25 (1.00)	0.253 (1.00)
11p loss	12 (7%)	149	0.347 (1.00)	0.237 (1.00)	0.548 (1.00)	0.297 (1.00)	0.168 (1.00)	0.834 (1.00)	0.0806 (1.00)	0.489 (1.00)	1 (1.00)
11q loss	9 (6%)	152	0.356 (1.00)	0.466 (1.00)	0.315 (1.00)	0.469 (1.00)	0.24 (1.00)	0.713 (1.00)	0.36 (1.00)	0.506 (1.00)	1 (1.00)
12q loss	6 (4%)	155	0.335 (1.00)	0.21 (1.00)	0.0819 (1.00)	0.705 (1.00)	0.191 (1.00)	0.0333 (1.00)	1 (1.00)	0.0852 (1.00)	1 (1.00)
13q loss	5 (3%)	156		0.866 (1.00)	1 (1.00)	0.325 (1.00)	0.702 (1.00)	0.356 (1.00)	0.635 (1.00)	0.577 (1.00)	0.148 (1.00)
14q loss	10 (6%)	151	0.208 (1.00)	0.0776 (1.00)	1 (1.00)	0.905 (1.00)	0.879 (1.00)	0.519 (1.00)	0.416 (1.00)	0.816 (1.00)	1 (1.00)
15q loss	10 (6%)	151	0.58 (1.00)	0.328 (1.00)	1 (1.00)	0.117 (1.00)	0.109 (1.00)	0.427 (1.00)	0.812 (1.00)	0.641 (1.00)	0.0315 (1.00)
16p loss	9 (6%)	152	0.606 (1.00)	0.396 (1.00)	0.0853 (1.00)	0.386 (1.00)	0.192 (1.00)	0.81 (1.00)	1 (1.00)	0.862 (1.00)	1 (1.00)
16q loss	14 (9%)	147	0.539 (1.00)	0.941 (1.00)	0.406 (1.00)	0.464 (1.00)	0.124 (1.00)	0.264 (1.00)	1 (1.00)	0.849 (1.00)	0.369 (1.00)
17p loss	32 (20%)	129	0.463 (1.00)	0.351 (1.00)	0.547 (1.00)	0.022 (1.00)	0.0683 (1.00)	0.286 (1.00)	0.927 (1.00)	0.436 (1.00)	0.0541 (1.00)
17q loss	9 (6%)	152	0.858 (1.00)	0.667 (1.00)	0.487 (1.00)	0.0316 (1.00)	0.936 (1.00)	0.368 (1.00)	0.247 (1.00)	0.407 (1.00)	0.253 (1.00)
18p loss	12 (7%)	149	0.278 (1.00)	0.872 (1.00)	1 (1.00)	0.952 (1.00)	0.553 (1.00)	0.362 (1.00)	0.587 (1.00)	0.38 (1.00)	1 (1.00)
18q loss	24 (15%)	137	0.213 (1.00)	0.46 (1.00)	0.505 (1.00)	0.836 (1.00)	0.579 (1.00)	0.224 (1.00)	0.249 (1.00)	0.438 (1.00)	1 (1.00)
19p loss	16 (10%)	145	0.671 (1.00)	0.905 (1.00)	0.283 (1.00)	0.544 (1.00)	0.54 (1.00)	0.284 (1.00)	0.759 (1.00)	0.511 (1.00)	1 (1.00)
19q loss	12 (7%)	149	0.879 (1.00)	0.182 (1.00)	0.364 (1.00)	0.559 (1.00)	0.421 (1.00)	0.233 (1.00)	0.702 (1.00)	0.141 (1.00)	1 (1.00)
20p loss	4 (2%)	157	0.286 (1.00)	0.873 (1.00)	0.304 (1.00)	0.862 (1.00)	0.253 (1.00)	0.726 (1.00)	0.0855 (1.00)	0.307 (1.00)	1 (1.00)
21q loss	29 (18%)	132	0.996 (1.00)	0.668 (1.00)	1 (1.00)	0.647 (1.00)	0.413 (1.00)	0.977 (1.00)	0.852 (1.00)	0.691 (1.00)	1 (1.00)
22q loss	22 (14%)	139	0.655 (1.00)	0.465 (1.00)	1 (1.00)	0.208 (1.00)	0.67 (1.00)	0.694 (1.00)	0.731 (1.00)	0.551 (1.00)	0.525 (1.00)
Xq loss	7 (4%)	154	0.139 (1.00)	0.289 (1.00)	0.702 (1.00)	0.207 (1.00)	0.0874 (1.00)	0.374 (1.00)	1 (1.00)	0.166 (1.00)	0.202 (1.00)

'20p gain mutation analysis' versus 'GENDER'

P value = 0.000128 (Fisher's exact test), Q value = 0.083

Table S1. Gene #34: '20p gain mutation analysis' versus Clinical Feature #3: 'GENDER'

nPatients	FEMALE	MALE
ALL	65	96
20P GAIN MUTATED	13	48
20P GAIN WILD-TYPE	52	48

Figure S1. Get High-res Image Gene #34: '20p gain mutation analysis' versus Clinical Feature #3: 'GENDER'

'20q gain mutation analysis' versus 'GENDER'

P value = 0.00037 (Fisher's exact test), Q value = 0.24

Table S2. Gene #35: '20q gain mutation analysis' versus Clinical Feature #3: 'GENDER'

nPatients	FEMALE	MALE
ALL	65	96
20Q GAIN MUTATED	19	56
20Q GAIN WILD-TYPE	46	40

Figure S2. Get High-res Image Gene #35: '20q gain mutation analysis' versus Clinical Feature #3: 'GENDER'

'1p loss mutation analysis' versus 'PATHOLOGICSPREAD(M)'

P value = 0.000111 (Fisher's exact test), Q value = 0.073

Table S3. Gene #37: '1p loss mutation analysis' versus Clinical Feature #7: 'PATHOLOGICSPREAD(M)'

nPatients	M0	M1	MX
ALL	132	18	11
1P LOSS MUTATED	1	5	0
1P LOSS WILD-TYPE	131	13	11

Figure S3. Get High-res Image Gene #37: '1p loss mutation analysis' versus Clinical Feature #7: 'PATHOLOGICSPREAD(M)'

'1p loss mutation analysis' versus 'TUMOR.STAGE'

P value = 0.000345 (Fisher's exact test), Q value = 0.22

Table S4. Gene #37: '1p loss mutation analysis' versus Clinical Feature #8: 'TUMOR.STAGE'

nPatients	I	II	III	IV
ALL	25	43	48	29
1P LOSS MUTATED	0	0	0	5
1P LOSS WILD-TYPE	25	43	48	24

Figure S4. Get High-res Image Gene #37: '1p loss mutation analysis' versus Clinical Feature #8: 'TUMOR.STAGE'

'12p loss mutation analysis' versus 'PATHOLOGY.N'

P value = 0.000243 (Fisher's exact test), Q value = 0.16

Table S5. Gene #58: '12p loss mutation analysis' versus Clinical Feature #6: 'PATHOLOGY.N'

nPatients	N0	N1	N2	N3
ALL	50	57	24	19
12P LOSS MUTATED	10	0	0	1
12P LOSS WILD-TYPE	40	57	24	18

Figure S5. Get High-res Image Gene #58: '12p loss mutation analysis' versus Clinical Feature #6: 'PATHOLOGY.N'

'12p loss mutation analysis' versus 'TUMOR.STAGE'

P value = 0.000228 (Fisher's exact test), Q value = 0.15

Table S6. Gene #58: '12p loss mutation analysis' versus Clinical Feature #8: 'TUMOR.STAGE'

nPatients	I	II	III	IV
ALL	25	43	48	29
12P LOSS MUTATED	7	3	0	1
12P LOSS WILD-TYPE	18	40	48	28

Figure S6. Get High-res Image Gene #58: '12p loss mutation analysis' versus Clinical Feature #8: 'TUMOR.STAGE'

Methods & Data

Input

Mutation data file = broad_values_by_arm.mutsig.cluster.txt
Clinical data file = STAD-TP.clin.merged.picked.txt
Number of patients = 161
Number of significantly arm-level cnvs = 74
Number of selected clinical features = 9
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)

Made with Nozzle