Correlation between copy number variations of arm-level result and molecular subtypes

Pancreatic Adenocarcinoma (Primary solid tumor)

16 April 2014 | analyses__2014_04_16

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 molecular subtypes. Broad Institute of MIT and Harvard. doi:10.7908/C1PZ57G0

Overview

Introduction

This pipeline computes the correlation between significant arm-level copy number variations (cnvs) and molecular subtypes.

Summary

Testing the association between copy number variation 71 arm-level events and 8 molecular subtypes across 91 patients, 26 significant findings detected with P value < 0.05 and Q value < 0.25.

12p gain cnv correlated to 'CN_CNMF'.
12q gain cnv correlated to 'CN_CNMF'.
16p gain cnv correlated to 'CN_CNMF'.
16q gain cnv correlated to 'CN_CNMF'.
18p gain cnv correlated to 'METHLYATION_CNMF'.
20q gain cnv correlated to 'CN_CNMF'.
5q loss cnv correlated to 'CN_CNMF'.
6p loss cnv correlated to 'METHLYATION_CNMF' and 'MRNASEQ_CHIERARCHICAL'.
6q loss cnv correlated to 'CN_CNMF', 'METHLYATION_CNMF', and 'MRNASEQ_CHIERARCHICAL'.
10q loss cnv correlated to 'CN_CNMF'.
12q loss cnv correlated to 'CN_CNMF'.
13q loss cnv correlated to 'CN_CNMF'.
15q loss cnv correlated to 'CN_CNMF', 'METHLYATION_CNMF', and 'MIRSEQ_MATURE_CHIERARCHICAL'.
17p loss cnv correlated to 'CN_CNMF', 'METHLYATION_CNMF', 'MRNASEQ_CHIERARCHICAL', 'MIRSEQ_CNMF', 'MIRSEQ_MATURE_CNMF', and 'MIRSEQ_MATURE_CHIERARCHICAL'.
21q loss cnv correlated to 'CN_CNMF'.
xq loss cnv correlated to 'CN_CNMF'.

Results

Overview of the results

Table 1. Get Full Table Overview of the association between significant copy number variation of 71 arm-level events and 8 molecular subtypes. Shown in the table are P values (Q values). Thresholded by P value < 0.05 and Q value < 0.25, 26 significant findings detected.


		Clinical Features	CN CNMF	METHLYATION CNMF	MRNASEQ CNMF	MRNASEQ CHIERARCHICAL	MIRSEQ CNMF	MIRSEQ CHIERARCHICAL	MIRSEQ MATURE CNMF	MIRSEQ MATURE CHIERARCHICAL
	nCNV (%)	nWild-Type	Fisher's exact test	Fisher's exact test	Fisher's exact test	Fisher's exact test	Fisher's exact test	Fisher's exact test	Fisher's exact test	Fisher's exact test
17p loss	37 (41%)	54	1.38e-11 (7.84e-09)	4.26e-11 (2.42e-08)	0.00053 (0.285)	4.22e-06 (0.00236)	9.2e-07 (0.000519)	0.000516 (0.279)	1.2e-06 (0.000673)	8.96e-06 (0.005)
6q loss	41 (45%)	50	8.13e-06 (0.00454)	3.87e-07 (0.000219)	0.00217 (1.00)	8.15e-07 (0.00046)	0.00452 (1.00)	0.00106 (0.562)	0.000562 (0.301)	0.000519 (0.28)
15q loss	15 (16%)	76	0.000251 (0.137)	0.000146 (0.0806)	0.0228 (1.00)	0.000559 (0.3)	0.00154 (0.806)	0.00534 (1.00)	0.0621 (1.00)	8.78e-05 (0.0487)
6p loss	32 (35%)	59	0.000754 (0.402)	7.94e-05 (0.0442)	0.302 (1.00)	0.000303 (0.165)	0.164 (1.00)	0.178 (1.00)	0.0137 (1.00)	0.0118 (1.00)
12p gain	10 (11%)	81	1.46e-06 (0.000819)	0.013 (1.00)	0.733 (1.00)	0.0257 (1.00)	0.754 (1.00)	0.309 (1.00)	0.473 (1.00)	0.16 (1.00)
12q gain	7 (8%)	84	0.000218 (0.12)	0.0536 (1.00)	0.303 (1.00)	0.122 (1.00)	0.628 (1.00)	0.463 (1.00)	0.523 (1.00)	0.266 (1.00)
16p gain	10 (11%)	81	0.000154 (0.0853)	0.00476 (1.00)	0.385 (1.00)	0.191 (1.00)	0.462 (1.00)	0.12 (1.00)	0.252 (1.00)	0.0554 (1.00)
16q gain	11 (12%)	80	0.000227 (0.125)	0.00221 (1.00)	0.45 (1.00)	0.105 (1.00)	0.0362 (1.00)	0.191 (1.00)	0.149 (1.00)	0.0252 (1.00)
18p gain	13 (14%)	78	0.00049 (0.265)	0.000191 (0.105)	0.0372 (1.00)	0.00472 (1.00)	0.114 (1.00)	0.0014 (0.739)	0.00194 (1.00)	0.00212 (1.00)
20q gain	20 (22%)	71	9.84e-06 (0.00548)	0.0466 (1.00)	0.223 (1.00)	0.0748 (1.00)	0.698 (1.00)	0.277 (1.00)	0.32 (1.00)	0.132 (1.00)
5q loss	8 (9%)	83	0.000369 (0.2)	0.0242 (1.00)	0.0818 (1.00)	0.0602 (1.00)	0.495 (1.00)	0.0381 (1.00)	0.00449 (1.00)	0.0442 (1.00)
10q loss	15 (16%)	76	0.000154 (0.0853)	0.0676 (1.00)	0.483 (1.00)	0.0112 (1.00)	0.804 (1.00)	0.00817 (1.00)	0.198 (1.00)	0.1 (1.00)
12q loss	13 (14%)	78	0.000275 (0.151)	0.00204 (1.00)	0.643 (1.00)	0.105 (1.00)	0.748 (1.00)	0.0619 (1.00)	0.418 (1.00)	0.165 (1.00)
13q loss	11 (12%)	80	0.000282 (0.154)	0.308 (1.00)	0.0628 (1.00)	0.191 (1.00)	0.301 (1.00)	0.0564 (1.00)	0.309 (1.00)	0.0707 (1.00)
21q loss	32 (35%)	59	2.44e-06 (0.00137)	0.00496 (1.00)	0.0194 (1.00)	0.00557 (1.00)	0.0323 (1.00)	0.0874 (1.00)	0.0207 (1.00)	0.105 (1.00)
xq loss	9 (10%)	82	0.000357 (0.194)	0.193 (1.00)	0.269 (1.00)	0.732 (1.00)	0.0909 (1.00)	0.316 (1.00)	0.0701 (1.00)	0.274 (1.00)
1p gain	8 (9%)	83	0.556 (1.00)	0.162 (1.00)	0.594 (1.00)	0.311 (1.00)	0.457 (1.00)	0.404 (1.00)	0.265 (1.00)	0.525 (1.00)
1q gain	24 (26%)	67	0.00752 (1.00)	0.0254 (1.00)	0.452 (1.00)	0.0681 (1.00)	0.362 (1.00)	0.282 (1.00)	0.0527 (1.00)	0.169 (1.00)
2p gain	6 (7%)	85	0.136 (1.00)	0.0838 (1.00)	0.186 (1.00)	0.0126 (1.00)	0.628 (1.00)	0.41 (1.00)	0.662 (1.00)	0.192 (1.00)
2q gain	7 (8%)	84	0.448 (1.00)	0.366 (1.00)	0.594 (1.00)	0.00719 (1.00)	0.744 (1.00)	0.882 (1.00)	1 (1.00)	0.525 (1.00)
3p gain	5 (5%)	86	0.133 (1.00)	0.0668 (1.00)	0.707 (1.00)	0.667 (1.00)	0.0865 (1.00)	1 (1.00)	0.433 (1.00)	1 (1.00)
3q gain	10 (11%)	81	0.0141 (1.00)	0.0116 (1.00)	0.423 (1.00)	0.191 (1.00)	0.817 (1.00)	0.336 (1.00)	0.691 (1.00)	0.314 (1.00)
5p gain	12 (13%)	79	0.00532 (1.00)	0.039 (1.00)	0.437 (1.00)	0.31 (1.00)	0.769 (1.00)	1 (1.00)	0.34 (1.00)	0.671 (1.00)
5q gain	8 (9%)	83	0.12 (1.00)	0.162 (1.00)	0.563 (1.00)	0.732 (1.00)	0.843 (1.00)	0.895 (1.00)	1 (1.00)	1 (1.00)
7p gain	25 (27%)	66	0.00295 (1.00)	0.00055 (0.295)	0.0369 (1.00)	0.000772 (0.412)	0.034 (1.00)	0.0102 (1.00)	0.0169 (1.00)	0.00285 (1.00)
7q gain	22 (24%)	69	0.00332 (1.00)	0.0039 (1.00)	0.138 (1.00)	0.00449 (1.00)	0.131 (1.00)	0.0235 (1.00)	0.0406 (1.00)	0.0182 (1.00)
8p gain	13 (14%)	78	0.00586 (1.00)	0.039 (1.00)	0.782 (1.00)	0.051 (1.00)	0.769 (1.00)	0.473 (1.00)	0.721 (1.00)	0.44 (1.00)
8q gain	24 (26%)	67	0.00185 (0.967)	0.0011 (0.581)	0.228 (1.00)	0.00141 (0.743)	0.26 (1.00)	0.181 (1.00)	0.0398 (1.00)	0.0405 (1.00)
9p gain	3 (3%)	88	0.0691 (1.00)	0.361 (1.00)	0.602 (1.00)	0.315 (1.00)	0.578 (1.00)	0.305 (1.00)	0.456 (1.00)	0.324 (1.00)
9q gain	3 (3%)	88	0.0691 (1.00)	0.361 (1.00)	0.602 (1.00)	0.315 (1.00)	0.578 (1.00)	0.305 (1.00)	0.456 (1.00)	0.324 (1.00)
10p gain	4 (4%)	87	0.0557 (1.00)	0.182 (1.00)	0.322 (1.00)	0.315 (1.00)	0.262 (1.00)	1 (1.00)	0.596 (1.00)	0.324 (1.00)
10q gain	6 (7%)	85	0.0166 (1.00)	0.023 (1.00)	0.183 (1.00)	0.325 (1.00)	0.132 (1.00)	0.532 (1.00)	0.345 (1.00)	0.145 (1.00)
11p gain	9 (10%)	82	0.0115 (1.00)	0.0156 (1.00)	0.434 (1.00)	0.529 (1.00)	0.45 (1.00)	0.657 (1.00)	0.818 (1.00)	0.389 (1.00)
11q gain	7 (8%)	84	0.0778 (1.00)	0.323 (1.00)	0.774 (1.00)	0.311 (1.00)	0.779 (1.00)	0.882 (1.00)	0.888 (1.00)	0.525 (1.00)
13q gain	9 (10%)	82	1 (1.00)	0.456 (1.00)	0.347 (1.00)	0.515 (1.00)	0.178 (1.00)	0.0535 (1.00)	0.447 (1.00)	0.4 (1.00)
14q gain	10 (11%)	81	0.0141 (1.00)	0.335 (1.00)	0.757 (1.00)	0.768 (1.00)	0.0796 (1.00)	0.911 (1.00)	0.631 (1.00)	1 (1.00)
15q gain	7 (8%)	84	0.508 (1.00)	0.375 (1.00)	0.469 (1.00)	0.446 (1.00)	0.884 (1.00)	0.488 (1.00)	0.0751 (1.00)	0.412 (1.00)
17q gain	4 (4%)	87	0.0557 (1.00)	0.131 (1.00)	0.457 (1.00)	0.325 (1.00)	0.624 (1.00)	0.104 (1.00)	0.682 (1.00)	0.145 (1.00)
18q gain	4 (4%)	87	0.0557 (1.00)	0.361 (1.00)	0.602 (1.00)	0.315 (1.00)	0.864 (1.00)	0.305 (1.00)	0.795 (1.00)	0.324 (1.00)
19p gain	4 (4%)	87	0.343 (1.00)	0.674 (1.00)	0.806 (1.00)	1 (1.00)	0.299 (1.00)	0.532 (1.00)	0.345 (1.00)	0.564 (1.00)
19q gain	12 (13%)	79	0.0581 (1.00)	0.188 (1.00)	0.337 (1.00)	0.589 (1.00)	0.304 (1.00)	0.516 (1.00)	0.141 (1.00)	0.44 (1.00)
20p gain	15 (16%)	76	0.00141 (0.742)	0.0114 (1.00)	0.092 (1.00)	0.102 (1.00)	0.911 (1.00)	0.262 (1.00)	0.701 (1.00)	0.121 (1.00)
22q gain	6 (7%)	85	0.136 (1.00)	0.00483 (1.00)	0.304 (1.00)	0.202 (1.00)	0.858 (1.00)	0.273 (1.00)	0.848 (1.00)	0.369 (1.00)
xq gain	3 (3%)	88	1 (1.00)	1 (1.00)	0.0811 (1.00)	0.569 (1.00)	0.664 (1.00)	0.0926 (1.00)	0.456 (1.00)	0.0911 (1.00)
1p loss	15 (16%)	76	0.0147 (1.00)	0.000472 (0.256)	0.0501 (1.00)	0.00691 (1.00)	0.624 (1.00)	0.0827 (1.00)	0.113 (1.00)	0.316 (1.00)
1q loss	4 (4%)	87	0.343 (1.00)	0.0615 (1.00)	0.798 (1.00)	0.315 (1.00)	1 (1.00)	0.592 (1.00)	0.158 (1.00)	0.793 (1.00)
2p loss	7 (8%)	84	0.0386 (1.00)	0.122 (1.00)	0.594 (1.00)	0.731 (1.00)	0.684 (1.00)	0.404 (1.00)	0.888 (1.00)	0.525 (1.00)
2q loss	3 (3%)	88	0.0691 (1.00)	0.361 (1.00)	0.322 (1.00)	0.315 (1.00)	0.864 (1.00)	0.305 (1.00)	0.795 (1.00)	0.324 (1.00)
3p loss	14 (15%)	77	0.00487 (1.00)	0.0978 (1.00)	0.857 (1.00)	0.453 (1.00)	0.806 (1.00)	0.54 (1.00)	0.206 (1.00)	0.164 (1.00)
3q loss	10 (11%)	81	0.144 (1.00)	0.124 (1.00)	0.733 (1.00)	0.529 (1.00)	0.643 (1.00)	0.901 (1.00)	0.139 (1.00)	0.479 (1.00)
4p loss	12 (13%)	79	0.101 (1.00)	0.0497 (1.00)	0.0793 (1.00)	0.302 (1.00)	0.204 (1.00)	0.488 (1.00)	0.459 (1.00)	0.148 (1.00)
4q loss	11 (12%)	80	0.184 (1.00)	0.00429 (1.00)	0.0412 (1.00)	0.39 (1.00)	0.205 (1.00)	0.461 (1.00)	0.571 (1.00)	0.0496 (1.00)
5p loss	4 (4%)	87	0.0557 (1.00)	0.182 (1.00)	0.183 (1.00)	0.325 (1.00)	0.132 (1.00)	0.104 (1.00)	0.142 (1.00)	0.145 (1.00)
8p loss	13 (14%)	78	0.281 (1.00)	0.0297 (1.00)	0.0119 (1.00)	0.051 (1.00)	0.163 (1.00)	0.0155 (1.00)	0.0408 (1.00)	0.00463 (1.00)
8q loss	3 (3%)	88	0.196 (1.00)	0.184 (1.00)	0.322 (1.00)	0.315 (1.00)	0.578 (1.00)	1 (1.00)	0.795 (1.00)	0.601 (1.00)
9p loss	36 (40%)	55	0.00311 (1.00)	0.0235 (1.00)	0.0345 (1.00)	0.553 (1.00)	0.235 (1.00)	0.102 (1.00)	0.0324 (1.00)	0.142 (1.00)
9q loss	24 (26%)	67	0.0816 (1.00)	0.274 (1.00)	0.723 (1.00)	1 (1.00)	0.238 (1.00)	0.783 (1.00)	0.187 (1.00)	0.681 (1.00)
10p loss	15 (16%)	76	0.00279 (1.00)	0.0855 (1.00)	0.495 (1.00)	0.0293 (1.00)	0.446 (1.00)	0.043 (1.00)	0.0775 (1.00)	0.224 (1.00)
11p loss	8 (9%)	83	0.0278 (1.00)	0.656 (1.00)	0.199 (1.00)	1 (1.00)	0.0745 (1.00)	0.355 (1.00)	0.0932 (1.00)	0.23 (1.00)
11q loss	10 (11%)	81	0.144 (1.00)	0.639 (1.00)	0.487 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)	0.473 (1.00)	1 (1.00)
12p loss	10 (11%)	81	0.0117 (1.00)	0.0116 (1.00)	0.0266 (1.00)	0.0257 (1.00)	0.0478 (1.00)	0.0782 (1.00)	0.473 (1.00)	0.0133 (1.00)
14q loss	7 (8%)	84	0.883 (1.00)	0.0075 (1.00)	0.227 (1.00)	0.731 (1.00)	0.419 (1.00)	0.523 (1.00)	0.313 (1.00)	0.113 (1.00)
16p loss	3 (3%)	88	0.0276 (1.00)	0.361 (1.00)	0.798 (1.00)	0.315 (1.00)	0.262 (1.00)	1 (1.00)	0.316 (1.00)	0.324 (1.00)
16q loss	3 (3%)	88	0.117 (1.00)	0.184 (1.00)	0.322 (1.00)	0.315 (1.00)	0.864 (1.00)	0.305 (1.00)	0.316 (1.00)	0.324 (1.00)
17q loss	12 (13%)	79	0.00096 (0.51)	0.039 (1.00)	0.617 (1.00)	0.39 (1.00)	0.462 (1.00)	0.626 (1.00)	0.278 (1.00)	0.519 (1.00)
18p loss	32 (35%)	59	0.806 (1.00)	0.0993 (1.00)	0.233 (1.00)	0.68 (1.00)	0.359 (1.00)	0.0801 (1.00)	0.311 (1.00)	0.387 (1.00)
18q loss	52 (57%)	39	0.00481 (1.00)	0.0016 (0.841)	0.399 (1.00)	0.104 (1.00)	0.0362 (1.00)	0.761 (1.00)	0.0968 (1.00)	0.242 (1.00)
19p loss	11 (12%)	80	0.000891 (0.474)	0.0793 (1.00)	0.0343 (1.00)	0.00942 (1.00)	0.479 (1.00)	0.0619 (1.00)	0.214 (1.00)	0.383 (1.00)
19q loss	6 (7%)	85	0.107 (1.00)	0.567 (1.00)	0.0418 (1.00)	0.145 (1.00)	0.267 (1.00)	0.0147 (1.00)	0.473 (1.00)	0.106 (1.00)
20p loss	9 (10%)	82	0.0249 (1.00)	0.0786 (1.00)	0.164 (1.00)	0.319 (1.00)	0.0237 (1.00)	0.399 (1.00)	0.035 (1.00)	0.274 (1.00)
22q loss	20 (22%)	71	0.00567 (1.00)	0.0223 (1.00)	0.134 (1.00)	0.124 (1.00)	0.0803 (1.00)	0.228 (1.00)	0.0686 (1.00)	0.347 (1.00)

'12p gain' versus 'CN_CNMF'

P value = 1.46e-06 (Fisher's exact test), Q value = 0.00082

Table S1. Gene #19: '12p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	24	46	21
12P GAIN MUTATED	1	0	9
12P GAIN WILD-TYPE	23	46	12

Figure S1. Get High-res Image Gene #19: '12p gain' versus Molecular Subtype #1: 'CN_CNMF'

'12q gain' versus 'CN_CNMF'

P value = 0.000218 (Fisher's exact test), Q value = 0.12

Table S2. Gene #20: '12q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	24	46	21
12Q GAIN MUTATED	1	0	6
12Q GAIN WILD-TYPE	23	46	15

Figure S2. Get High-res Image Gene #20: '12q gain' versus Molecular Subtype #1: 'CN_CNMF'

'16p gain' versus 'CN_CNMF'

P value = 0.000154 (Fisher's exact test), Q value = 0.085

Table S3. Gene #24: '16p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	24	46	21
16P GAIN MUTATED	3	0	7
16P GAIN WILD-TYPE	21	46	14

Figure S3. Get High-res Image Gene #24: '16p gain' versus Molecular Subtype #1: 'CN_CNMF'

'16q gain' versus 'CN_CNMF'

P value = 0.000227 (Fisher's exact test), Q value = 0.12

Table S4. Gene #25: '16q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	24	46	21
16Q GAIN MUTATED	5	0	6
16Q GAIN WILD-TYPE	19	46	15

Figure S4. Get High-res Image Gene #25: '16q gain' versus Molecular Subtype #1: 'CN_CNMF'

'18p gain' versus 'METHLYATION_CNMF'

P value = 0.000191 (Fisher's exact test), Q value = 0.11

Table S5. Gene #27: '18p gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	31	35	24
18P GAIN MUTATED	10	0	2
18P GAIN WILD-TYPE	21	35	22

Figure S5. Get High-res Image Gene #27: '18p gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'20q gain' versus 'CN_CNMF'

P value = 9.84e-06 (Fisher's exact test), Q value = 0.0055

Table S6. Gene #32: '20q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	24	46	21
20Q GAIN MUTATED	3	4	13
20Q GAIN WILD-TYPE	21	42	8

Figure S6. Get High-res Image Gene #32: '20q gain' versus Molecular Subtype #1: 'CN_CNMF'

'5q loss' versus 'CN_CNMF'

P value = 0.000369 (Fisher's exact test), Q value = 0.2

Table S7. Gene #44: '5q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	24	46	21
5Q LOSS MUTATED	2	0	6
5Q LOSS WILD-TYPE	22	46	15

Figure S7. Get High-res Image Gene #44: '5q loss' versus Molecular Subtype #1: 'CN_CNMF'

'6p loss' versus 'METHLYATION_CNMF'

P value = 7.94e-05 (Fisher's exact test), Q value = 0.044

Table S8. Gene #45: '6p loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	31	35	24
6P LOSS MUTATED	15	3	13
6P LOSS WILD-TYPE	16	32	11

Figure S8. Get High-res Image Gene #45: '6p loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'6p loss' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.000303 (Fisher's exact test), Q value = 0.17

Table S9. Gene #45: '6p loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	1	31	52
6P LOSS MUTATED	0	3	25
6P LOSS WILD-TYPE	1	28	27

Figure S9. Get High-res Image Gene #45: '6p loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'6q loss' versus 'CN_CNMF'

P value = 8.13e-06 (Fisher's exact test), Q value = 0.0045

Table S10. Gene #46: '6q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	24	46	21
6Q LOSS MUTATED	14	10	17
6Q LOSS WILD-TYPE	10	36	4

Figure S10. Get High-res Image Gene #46: '6q loss' versus Molecular Subtype #1: 'CN_CNMF'

'6q loss' versus 'METHLYATION_CNMF'

P value = 3.87e-07 (Fisher's exact test), Q value = 0.00022

Table S11. Gene #46: '6q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	31	35	24
6Q LOSS MUTATED	23	4	13
6Q LOSS WILD-TYPE	8	31	11

Figure S11. Get High-res Image Gene #46: '6q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'6q loss' versus 'MRNASEQ_CHIERARCHICAL'

P value = 8.15e-07 (Fisher's exact test), Q value = 0.00046

Table S12. Gene #46: '6q loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	1	31	52
6Q LOSS MUTATED	0	3	33
6Q LOSS WILD-TYPE	1	28	19

Figure S12. Get High-res Image Gene #46: '6q loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'10q loss' versus 'CN_CNMF'

P value = 0.000154 (Fisher's exact test), Q value = 0.085

Table S13. Gene #52: '10q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	24	46	21
10Q LOSS MUTATED	6	1	8
10Q LOSS WILD-TYPE	18	45	13

Figure S13. Get High-res Image Gene #52: '10q loss' versus Molecular Subtype #1: 'CN_CNMF'

'12q loss' versus 'CN_CNMF'

P value = 0.000275 (Fisher's exact test), Q value = 0.15

Table S14. Gene #56: '12q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	24	46	21
12Q LOSS MUTATED	4	1	8
12Q LOSS WILD-TYPE	20	45	13

Figure S14. Get High-res Image Gene #56: '12q loss' versus Molecular Subtype #1: 'CN_CNMF'

'13q loss' versus 'CN_CNMF'

P value = 0.000282 (Fisher's exact test), Q value = 0.15

Table S15. Gene #57: '13q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	24	46	21
13Q LOSS MUTATED	2	1	8
13Q LOSS WILD-TYPE	22	45	13

Figure S15. Get High-res Image Gene #57: '13q loss' versus Molecular Subtype #1: 'CN_CNMF'

'15q loss' versus 'CN_CNMF'

P value = 0.000251 (Fisher's exact test), Q value = 0.14

Table S16. Gene #59: '15q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	24	46	21
15Q LOSS MUTATED	8	1	6
15Q LOSS WILD-TYPE	16	45	15

Figure S16. Get High-res Image Gene #59: '15q loss' versus Molecular Subtype #1: 'CN_CNMF'

'15q loss' versus 'METHLYATION_CNMF'

P value = 0.000146 (Fisher's exact test), Q value = 0.081

Table S17. Gene #59: '15q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	31	35	24
15Q LOSS MUTATED	11	0	4
15Q LOSS WILD-TYPE	20	35	20

Figure S17. Get High-res Image Gene #59: '15q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'15q loss' versus 'MIRSEQ_MATURE_CHIERARCHICAL'

P value = 8.78e-05 (Fisher's exact test), Q value = 0.049

Table S18. Gene #59: '15q loss' versus Molecular Subtype #8: 'MIRSEQ_MATURE_CHIERARCHICAL'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	26	20	38
15Q LOSS MUTATED	0	1	14
15Q LOSS WILD-TYPE	26	19	24

Figure S18. Get High-res Image Gene #59: '15q loss' versus Molecular Subtype #8: 'MIRSEQ_MATURE_CHIERARCHICAL'

'17p loss' versus 'CN_CNMF'

P value = 1.38e-11 (Fisher's exact test), Q value = 7.8e-09

Table S19. Gene #62: '17p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	24	46	21
17P LOSS MUTATED	18	3	16
17P LOSS WILD-TYPE	6	43	5

Figure S19. Get High-res Image Gene #62: '17p loss' versus Molecular Subtype #1: 'CN_CNMF'

'17p loss' versus 'METHLYATION_CNMF'

P value = 4.26e-11 (Fisher's exact test), Q value = 2.4e-08

Table S20. Gene #62: '17p loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	31	35	24
17P LOSS MUTATED	25	1	11
17P LOSS WILD-TYPE	6	34	13

Figure S20. Get High-res Image Gene #62: '17p loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'17p loss' versus 'MRNASEQ_CHIERARCHICAL'

P value = 4.22e-06 (Fisher's exact test), Q value = 0.0024

Table S21. Gene #62: '17p loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	1	31	52
17P LOSS MUTATED	0	3	31
17P LOSS WILD-TYPE	1	28	21

Figure S21. Get High-res Image Gene #62: '17p loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'17p loss' versus 'MIRSEQ_CNMF'

P value = 9.2e-07 (Fisher's exact test), Q value = 0.00052

Table S22. Gene #62: '17p loss' versus Molecular Subtype #5: 'MIRSEQ_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4
ALL	31	19	12	22
17P LOSS MUTATED	24	6	1	3
17P LOSS WILD-TYPE	7	13	11	19

Figure S22. Get High-res Image Gene #62: '17p loss' versus Molecular Subtype #5: 'MIRSEQ_CNMF'

'17p loss' versus 'MIRSEQ_MATURE_CNMF'

P value = 1.2e-06 (Fisher's exact test), Q value = 0.00067

Table S23. Gene #62: '17p loss' versus Molecular Subtype #7: 'MIRSEQ_MATURE_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	38	19	27
17P LOSS MUTATED	26	6	2
17P LOSS WILD-TYPE	12	13	25

Figure S23. Get High-res Image Gene #62: '17p loss' versus Molecular Subtype #7: 'MIRSEQ_MATURE_CNMF'

'17p loss' versus 'MIRSEQ_MATURE_CHIERARCHICAL'

P value = 8.96e-06 (Fisher's exact test), Q value = 0.005

Table S24. Gene #62: '17p loss' versus Molecular Subtype #8: 'MIRSEQ_MATURE_CHIERARCHICAL'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	26	20	38
17P LOSS MUTATED	8	1	25
17P LOSS WILD-TYPE	18	19	13

Figure S24. Get High-res Image Gene #62: '17p loss' versus Molecular Subtype #8: 'MIRSEQ_MATURE_CHIERARCHICAL'

'21q loss' versus 'CN_CNMF'

P value = 2.44e-06 (Fisher's exact test), Q value = 0.0014

Table S25. Gene #69: '21q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	24	46	21
21Q LOSS MUTATED	15	5	12
21Q LOSS WILD-TYPE	9	41	9

Figure S25. Get High-res Image Gene #69: '21q loss' versus Molecular Subtype #1: 'CN_CNMF'

'xq loss' versus 'CN_CNMF'

P value = 0.000357 (Fisher's exact test), Q value = 0.19

Table S26. Gene #71: 'xq loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	24	46	21
XQ LOSS MUTATED	3	0	6
XQ LOSS WILD-TYPE	21	46	15

Figure S26. Get High-res Image Gene #71: 'xq loss' versus Molecular Subtype #1: 'CN_CNMF'

Methods & Data

Input

Copy number data file = transformed.cor.cli.txt
Molecular subtypes file = PAAD-TP.transferedmergedcluster.txt
Number of patients = 91
Number of significantly arm-level cnvs = 71
Number of molecular subtypes = 8
Exclude genes that fewer than K tumors have mutations, K = 3

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] 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)

[2] 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