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

Acute Myeloid Leukemia (Primary blood derived cancer - Peripheral blood)

23 May 2013 | analyses__2013_05_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 molecular subtypes. Broad Institute of MIT and Harvard. doi:10.7908/C1R49NT9

Overview

Introduction

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

Summary

Testing the association between copy number variation 22 arm-level results and 6 molecular subtypes across 191 patients, 20 significant findings detected with Q value < 0.25.

1p gain cnv correlated to 'CN_CNMF'.
4p gain cnv correlated to 'CN_CNMF'.
4q gain cnv correlated to 'CN_CNMF'.
8p gain cnv correlated to 'CN_CNMF' and 'METHLYATION_CNMF'.
8q gain cnv correlated to 'CN_CNMF'.
10q gain cnv correlated to 'CN_CNMF'.
11p gain cnv correlated to 'CN_CNMF'.
11q gain cnv correlated to 'CN_CNMF'.
17q gain cnv correlated to 'CN_CNMF'.
21q gain cnv correlated to 'CN_CNMF'.
5q loss cnv correlated to 'CN_CNMF'.
7p loss cnv correlated to 'CN_CNMF' and 'METHLYATION_CNMF'.
7q loss cnv correlated to 'CN_CNMF', 'METHLYATION_CNMF', and 'MIRSEQ_CHIERARCHICAL'.
17p loss cnv correlated to 'CN_CNMF'.
17q loss cnv correlated to 'CN_CNMF'.
18p 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 22 arm-level results and 6 molecular subtypes. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 20 significant findings detected.


		Molecular subtypes	CN CNMF	METHLYATION CNMF	MRNASEQ CNMF	MRNASEQ CHIERARCHICAL	MIRSEQ CNMF	MIRSEQ CHIERARCHICAL
	nCNV (%)	nWild-Type	Chi-square test	Chi-square test	Fisher's exact test	Fisher's exact test	Fisher's exact test	Fisher's exact test
7q loss	0 (0%)	173	6.33e-08 (7.86e-06)	9.23e-05 (0.0109)	0.0272 (1.00)	0.0211 (1.00)	0.0122 (1.00)	0.00099 (0.113)
8p gain	0 (0%)	171	2.44e-05 (0.00295)	0.00189 (0.21)	0.0674 (1.00)	0.0126 (1.00)	0.0124 (1.00)	0.157 (1.00)
7p loss	0 (0%)	176	1.61e-06 (0.000198)	0.0017 (0.191)	0.00277 (0.297)	0.00279 (0.297)	0.0269 (1.00)	0.00265 (0.286)
1p gain	0 (0%)	188	0.00135 (0.153)	0.185 (1.00)	0.186 (1.00)	0.552 (1.00)	0.0923 (1.00)	0.0481 (1.00)
4p gain	0 (0%)	187	9.82e-05 (0.0115)	0.0502 (1.00)		0.55 (1.00)	0.343 (1.00)	0.831 (1.00)
4q gain	0 (0%)	187	9.82e-05 (0.0115)	0.0502 (1.00)		0.55 (1.00)	0.343 (1.00)	0.831 (1.00)
8q gain	0 (0%)	170	6.42e-05 (0.00764)	0.00509 (0.509)	0.0434 (1.00)	0.0125 (1.00)	0.00717 (0.695)	0.223 (1.00)
10q gain	0 (0%)	188	0.000979 (0.113)	0.185 (1.00)	0.186 (1.00)	0.552 (1.00)	0.552 (1.00)	0.222 (1.00)
11p gain	0 (0%)	187	3.32e-15 (4.29e-13)	0.0808 (1.00)	0.467 (1.00)	1 (1.00)	0.523 (1.00)	0.0704 (1.00)
11q gain	0 (0%)	184	9.42e-12 (1.21e-09)	0.00516 (0.511)	0.0668 (1.00)	0.425 (1.00)	0.291 (1.00)	0.271 (1.00)
17q gain	0 (0%)	188	6.81e-06 (0.000831)	0.38 (1.00)	1 (1.00)	0.552 (1.00)	0.482 (1.00)	0.222 (1.00)
21q gain	0 (0%)	183	2.62e-15 (3.41e-13)	0.203 (1.00)	0.124 (1.00)	1 (1.00)	0.0814 (1.00)	0.198 (1.00)
5q loss	0 (0%)	185	6.1e-11 (7.75e-09)	0.0134 (1.00)	0.224 (1.00)	0.664 (1.00)	0.0318 (1.00)	0.0205 (1.00)
17p loss	0 (0%)	181	2.2e-10 (2.77e-08)	0.00255 (0.281)	0.0752 (1.00)	0.167 (1.00)	0.00541 (0.53)	0.00451 (0.456)
17q loss	0 (0%)	186	4.94e-10 (6.18e-08)	0.0335 (1.00)	0.224 (1.00)	0.664 (1.00)	0.00335 (0.352)	0.00258 (0.281)
18p loss	0 (0%)	186	5.17e-05 (0.00621)	0.0335 (1.00)	1 (1.00)	1 (1.00)	0.248 (1.00)	0.329 (1.00)
13q gain	0 (0%)	188	0.00355 (0.369)	0.185 (1.00)	0.186 (1.00)	0.552 (1.00)	0.552 (1.00)	0.222 (1.00)
19p gain	0 (0%)	186	0.0342 (1.00)	0.633 (1.00)	1 (1.00)	1 (1.00)	0.651 (1.00)	0.607 (1.00)
19q gain	0 (0%)	186	0.0342 (1.00)	0.633 (1.00)	1 (1.00)	1 (1.00)	0.651 (1.00)	0.607 (1.00)
22q gain	0 (0%)	183	0.00406 (0.414)	0.0206 (1.00)	0.0349 (1.00)	0.269 (1.00)	0.0651 (1.00)	0.0493 (1.00)
12p loss	0 (0%)	188	0.0191 (1.00)	0.0326 (1.00)	0.618 (1.00)	0.552 (1.00)	0.793 (1.00)	0.222 (1.00)
18q loss	0 (0%)	188	0.00355 (0.369)	0.185 (1.00)	0.786 (1.00)	1 (1.00)	0.0618 (1.00)	0.0481 (1.00)

'1p gain' versus 'CN_CNMF'

P value = 0.00135 (Chi-square test), Q value = 0.15

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

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4	CLUS_5
ALL	142	15	15	18	1
1P GAIN CNV	0	2	0	1	0
1P GAIN WILD-TYPE	142	13	15	17	1

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

'4p gain' versus 'CN_CNMF'

P value = 9.82e-05 (Chi-square test), Q value = 0.011

Table S2. Gene #2: '4p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4	CLUS_5
ALL	142	15	15	18	1
4P GAIN CNV	0	0	1	3	0
4P GAIN WILD-TYPE	142	15	14	15	1

Figure S2. Get High-res Image Gene #2: '4p gain' versus Molecular Subtype #1: 'CN_CNMF'

'4q gain' versus 'CN_CNMF'

P value = 9.82e-05 (Chi-square test), Q value = 0.011

Table S3. Gene #3: '4q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4	CLUS_5
ALL	142	15	15	18	1
4Q GAIN CNV	0	0	1	3	0
4Q GAIN WILD-TYPE	142	15	14	15	1

Figure S3. Get High-res Image Gene #3: '4q gain' versus Molecular Subtype #1: 'CN_CNMF'

'8p gain' versus 'CN_CNMF'

P value = 2.44e-05 (Chi-square test), Q value = 0.003

Table S4. Gene #4: '8p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4	CLUS_5
ALL	142	15	15	18	1
8P GAIN CNV	8	1	4	6	1
8P GAIN WILD-TYPE	134	14	11	12	0

Figure S4. Get High-res Image Gene #4: '8p gain' versus Molecular Subtype #1: 'CN_CNMF'

'8p gain' versus 'METHLYATION_CNMF'

P value = 0.00189 (Chi-square test), Q value = 0.21

Table S5. Gene #4: '8p gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4	CLUS_5
ALL	46	44	61	14	20
8P GAIN CNV	2	1	14	0	2
8P GAIN WILD-TYPE	44	43	47	14	18

Figure S5. Get High-res Image Gene #4: '8p gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'8q gain' versus 'CN_CNMF'

P value = 6.42e-05 (Chi-square test), Q value = 0.0076

Table S6. Gene #5: '8q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4	CLUS_5
ALL	142	15	15	18	1
8Q GAIN CNV	9	1	4	6	1
8Q GAIN WILD-TYPE	133	14	11	12	0

Figure S6. Get High-res Image Gene #5: '8q gain' versus Molecular Subtype #1: 'CN_CNMF'

'10q gain' versus 'CN_CNMF'

P value = 0.000979 (Chi-square test), Q value = 0.11

Table S7. Gene #6: '10q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4	CLUS_5
ALL	142	15	15	18	1
10Q GAIN CNV	0	1	2	0	0
10Q GAIN WILD-TYPE	142	14	13	18	1

Figure S7. Get High-res Image Gene #6: '10q gain' versus Molecular Subtype #1: 'CN_CNMF'

'11p gain' versus 'CN_CNMF'

P value = 3.32e-15 (Chi-square test), Q value = 4.3e-13

Table S8. Gene #7: '11p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4	CLUS_5
ALL	142	15	15	18	1
11P GAIN CNV	0	3	0	0	1
11P GAIN WILD-TYPE	142	12	15	18	0

Figure S8. Get High-res Image Gene #7: '11p gain' versus Molecular Subtype #1: 'CN_CNMF'

'11q gain' versus 'CN_CNMF'

P value = 9.42e-12 (Chi-square test), Q value = 1.2e-09

Table S9. Gene #8: '11q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4	CLUS_5
ALL	142	15	15	18	1
11Q GAIN CNV	0	4	0	2	1
11Q GAIN WILD-TYPE	142	11	15	16	0

Figure S9. Get High-res Image Gene #8: '11q gain' versus Molecular Subtype #1: 'CN_CNMF'

'17q gain' versus 'CN_CNMF'

P value = 6.81e-06 (Chi-square test), Q value = 0.00083

Table S10. Gene #10: '17q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4	CLUS_5
ALL	142	15	15	18	1
17Q GAIN CNV	0	0	0	3	0
17Q GAIN WILD-TYPE	142	15	15	15	1

Figure S10. Get High-res Image Gene #10: '17q gain' versus Molecular Subtype #1: 'CN_CNMF'

'21q gain' versus 'CN_CNMF'

P value = 2.62e-15 (Chi-square test), Q value = 3.4e-13

Table S11. Gene #13: '21q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4	CLUS_5
ALL	142	15	15	18	1
21Q GAIN CNV	0	0	7	1	0
21Q GAIN WILD-TYPE	142	15	8	17	1

Figure S11. Get High-res Image Gene #13: '21q gain' versus Molecular Subtype #1: 'CN_CNMF'

'5q loss' versus 'CN_CNMF'

P value = 6.1e-11 (Chi-square test), Q value = 7.7e-09

Table S12. Gene #15: '5q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4	CLUS_5
ALL	142	15	15	18	1
5Q LOSS CNV	0	0	3	2	1
5Q LOSS WILD-TYPE	142	15	12	16	0

Figure S12. Get High-res Image Gene #15: '5q loss' versus Molecular Subtype #1: 'CN_CNMF'

'7p loss' versus 'CN_CNMF'

P value = 1.61e-06 (Chi-square test), Q value = 2e-04

Table S13. Gene #16: '7p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4	CLUS_5
ALL	142	15	15	18	1
7P LOSS CNV	6	0	2	6	1
7P LOSS WILD-TYPE	136	15	13	12	0

Figure S13. Get High-res Image Gene #16: '7p loss' versus Molecular Subtype #1: 'CN_CNMF'

'7p loss' versus 'METHLYATION_CNMF'

P value = 0.0017 (Chi-square test), Q value = 0.19

Table S14. Gene #16: '7p loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4	CLUS_5
ALL	46	44	61	14	20
7P LOSS CNV	1	0	12	1	1
7P LOSS WILD-TYPE	45	44	49	13	19

Figure S14. Get High-res Image Gene #16: '7p loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'7q loss' versus 'CN_CNMF'

P value = 6.33e-08 (Chi-square test), Q value = 7.9e-06

Table S15. Gene #17: '7q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4	CLUS_5
ALL	142	15	15	18	1
7Q LOSS CNV	6	0	4	7	1
7Q LOSS WILD-TYPE	136	15	11	11	0

Figure S15. Get High-res Image Gene #17: '7q loss' versus Molecular Subtype #1: 'CN_CNMF'

'7q loss' versus 'METHLYATION_CNMF'

P value = 9.23e-05 (Chi-square test), Q value = 0.011

Table S16. Gene #17: '7q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4	CLUS_5
ALL	46	44	61	14	20
7Q LOSS CNV	1	0	15	1	1
7Q LOSS WILD-TYPE	45	44	46	13	19

Figure S16. Get High-res Image Gene #17: '7q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'7q loss' versus 'MIRSEQ_CHIERARCHICAL'

P value = 0.00099 (Fisher's exact test), Q value = 0.11

Table S17. Gene #17: '7q loss' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	35	79	65
7Q LOSS CNV	9	2	6
7Q LOSS WILD-TYPE	26	77	59

Figure S17. Get High-res Image Gene #17: '7q loss' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

'17p loss' versus 'CN_CNMF'

P value = 2.2e-10 (Chi-square test), Q value = 2.8e-08

Table S18. Gene #19: '17p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4	CLUS_5
ALL	142	15	15	18	1
17P LOSS CNV	0	1	3	5	1
17P LOSS WILD-TYPE	142	14	12	13	0

Figure S18. Get High-res Image Gene #19: '17p loss' versus Molecular Subtype #1: 'CN_CNMF'

'17q loss' versus 'CN_CNMF'

P value = 4.94e-10 (Chi-square test), Q value = 6.2e-08

Table S19. Gene #20: '17q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4	CLUS_5
ALL	142	15	15	18	1
17Q LOSS CNV	0	1	2	1	1
17Q LOSS WILD-TYPE	142	14	13	17	0

Figure S19. Get High-res Image Gene #20: '17q loss' versus Molecular Subtype #1: 'CN_CNMF'

'18p loss' versus 'CN_CNMF'

P value = 5.17e-05 (Chi-square test), Q value = 0.0062

Table S20. Gene #21: '18p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4	CLUS_5
ALL	142	15	15	18	1
18P LOSS CNV	0	0	2	3	0
18P LOSS WILD-TYPE	142	15	13	15	1

Figure S20. Get High-res Image Gene #21: '18p loss' versus Molecular Subtype #1: 'CN_CNMF'

Methods & Data

Input

Mutation data file = broad_values_by_arm.mutsig.cluster.txt
Molecular subtypes file = LAML-TB.transferedmergedcluster.txt
Number of patients = 191
Number of significantly arm-level cnvs = 22
Number of molecular subtypes = 6
Exclude genes that fewer than K tumors have mutations, K = 3

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

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

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] Greenwood and Nikulin, A guide to chi-squared testing, Wiley, New York. ISBN 047155779X (1996)

[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)

Made with Nozzle