Acute Myeloid Leukemia: Correlation between gene mutation status and molecular subtypes
(primary blood tumor (peripheral) cohort)
Maintained by TCGA GDAC Team (Broad Institute/MD Anderson Cancer Center/Harvard Medical School)
Overview
Introduction

This pipeline computes the correlation between significantly recurrent gene mutations and molecular subtypes.

Summary

Testing the association between mutation status of 24 genes and 6 molecular subtypes across 197 patients, 23 significant findings detected with P value < 0.05 and Q value < 0.25.

- WT1 mutation correlated to 'METHLYATION_CNMF'.

- RUNX1 mutation correlated to 'MRNASEQ_CNMF' and 'MIRSEQ_CHIERARCHICAL'.

- DNMT3A mutation correlated to 'METHLYATION_CNMF', 'MIRSEQ_CNMF', and 'MIRSEQ_CHIERARCHICAL'.

- FLT3 mutation correlated to 'METHLYATION_CNMF', 'MRNASEQ_CNMF', 'MIRSEQ_CNMF', and 'MIRSEQ_CHIERARCHICAL'.

- IDH1 mutation correlated to 'METHLYATION_CNMF'.

- IDH2 mutation correlated to 'METHLYATION_CNMF'.

- NPM1 mutation correlated to 'CN_CNMF', 'METHLYATION_CNMF', 'MRNASEQ_CNMF', 'MIRSEQ_CNMF', and 'MIRSEQ_CHIERARCHICAL'.

- TP53 mutation correlated to 'CN_CNMF', 'METHLYATION_CNMF', 'MRNASEQ_CNMF', 'MIRSEQ_CNMF', and 'MIRSEQ_CHIERARCHICAL'.

- FAM5C mutation correlated to 'CN_CNMF'.

Results
Overview of the results

Table 1. Get Full Table Overview of the association between mutation status of 24 genes and 6 molecular subtypes. Shown in the table are P values (Q values). Thresholded by P value < 0.05 and Q value < 0.25, 23 significant findings detected.

|  | Clinical Features | CN CNMF | METHLYATION CNMF | MRNASEQ CNMF | MRNASEQ CHIERARCHICAL | MIRSEQ CNMF | MIRSEQ CHIERARCHICAL
| nMutated (%) | nWild-Type | Chi-square test | Chi-square test | Fisher's exact test | Fisher's exact test | Fisher's exact test | Fisher's exact test
NPM1 | 54 (27%) | 143 | 0.000935 (0.11) | 3.11e-18 (4.25e-16) | 1.79e-13 (2.44e-11) | 0.00649 (0.746) | 2.17e-20 (2.99e-18) | 1.79e-21 (2.49e-19)
TP53 | 15 (8%) | 182 | 1.52e-10 (2.05e-08) | 2.81e-09 (3.74e-07) | 0.000687 (0.0817) | 0.0625 (1.00) | 0.000668 (0.0802) | 0.000144 (0.0176)
FLT3 | 56 (28%) | 141 | 0.0164 (1.00) | 4.52e-05 (0.00565) | 1.86e-07 (2.42e-05) | 0.0209 (1.00) | 0.000285 (0.0345) | 1.28e-05 (0.00162)
DNMT3A | 51 (26%) | 146 | 0.978 (1.00) | 3.03e-05 (0.00382) | 0.0122 (1.00) | 0.195 (1.00) | 5.71e-05 (0.00702) | 5.45e-06 (0.000698)
RUNX1 | 18 (9%) | 179 | 0.381 (1.00) | 0.011 (1.00) | 0.00152 (0.178) | 0.0926 (1.00) | 0.00649 (0.746) | 5.1e-05 (0.00632)
WT1 | 12 (6%) | 185 | 0.581 (1.00) | 2.19e-06 (0.000282) | 0.0817 (1.00) | 1 (1.00) | 0.666 (1.00) | 0.516 (1.00)
IDH1 | 19 (10%) | 178 | 0.968 (1.00) | 7.04e-09 (9.3e-07) | 0.423 (1.00) | 0.268 (1.00) | 0.307 (1.00) | 0.236 (1.00)
IDH2 | 20 (10%) | 177 | 0.269 (1.00) | 1.31e-09 (1.76e-07) | 0.725 (1.00) | 1 (1.00) | 0.896 (1.00) | 0.895 (1.00)
FAM5C | 5 (3%) | 192 | 1.15e-07 (1.51e-05) | 0.611 (1.00) | 0.729 (1.00) | 0.665 (1.00) | 1 (1.00) | 1 (1.00)
NRAS | 15 (8%) | 182 | 0.0145 (1.00) | 0.571 (1.00) | 0.645 (1.00) | 0.539 (1.00) | 0.938 (1.00) | 0.878 (1.00)
U2AF1 | 8 (4%) | 189 | 0.776 (1.00) | 0.24 (1.00) | 0.232 (1.00) | 0.426 (1.00) | 0.176 (1.00) | 0.171 (1.00)
KRAS | 8 (4%) | 189 | 0.533 (1.00) | 0.925 (1.00) | 0.326 (1.00) | 0.225 (1.00) | 0.0996 (1.00) | 0.063 (1.00)
PTPN11 | 9 (5%) | 188 | 0.485 (1.00) | 0.903 (1.00) | 0.0476 (1.00) | 1 (1.00) | 0.176 (1.00) | 0.447 (1.00)
TET2 | 17 (9%) | 180 | 0.464 (1.00) | 0.534 (1.00) | 0.256 (1.00) | 0.776 (1.00) | 0.512 (1.00) | 0.428 (1.00)
KIT | 8 (4%) | 189 | 0.885 (1.00) | 0.00779 (0.88) | 0.326 (1.00) | 0.688 (1.00) | 0.115 (1.00) | 0.113 (1.00)
PHF6 | 6 (3%) | 191 | 0.317 (1.00) | 0.396 (1.00) | 0.729 (1.00) | 0.17 (1.00) | 0.515 (1.00) | 0.148 (1.00)
SMC1A | 7 (4%) | 190 | 0.826 (1.00) | 0.359 (1.00) | 0.37 (1.00) | 0.043 (1.00) | 0.153 (1.00) | 0.106 (1.00)
SMC3 | 7 (4%) | 190 | 0.77 (1.00) | 0.564 (1.00) | 0.552 (1.00) | 0.426 (1.00) | 0.426 (1.00) | 0.48 (1.00)
RAD21 | 5 (3%) | 192 | 0.757 (1.00) | 0.543 (1.00) | 0.608 (1.00) | 1 (1.00) | 0.373 (1.00) | 0.287 (1.00)
STAG2 | 6 (3%) | 191 | 0.776 (1.00) | 0.0344 (1.00) | 0.132 (1.00) | 0.17 (1.00) | 0.852 (1.00) | 0.222 (1.00)
EZH2 | 3 (2%) | 194 | 0.00614 (0.713) |  | 0.261 (1.00) | 1 (1.00) | 0.222 (1.00) | 0.229 (1.00)
ASXL1 | 5 (3%) | 192 | 0.757 (1.00) | 0.187 (1.00) | 0.261 (1.00) | 0.552 (1.00) | 0.222 (1.00) | 0.229 (1.00)
PHACTR1 | 3 (2%) | 194 |  | 0.424 (1.00) |  | 1 (1.00) | 0.222 (1.00) | 0.229 (1.00)
DIS3 | 3 (2%) | 194 | 0.553 (1.00) |  |  | 1 (1.00) | 0.089 (1.00) | 0.0958 (1.00)

'WT1 MUTATION STATUS' versus 'METHLYATION_CNMF'

P value = 2.19e-06 (Chi-square test), Q value = 0.00028

Table S1. Gene #2: 'WT1 MUTATION STATUS' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4 | CLUS_5 | CLUS_6
--- | --- | --- | --- | --- | --- | ---
ALL | 48 | 18 | 26 | 39 | 48 | 12
WT1 MUTATED | 1 | 0 | 2 | 3 | 0 | 5
WT1 WILD-TYPE | 47 | 18 | 24 | 36 | 48 | 7

Figure S1. Get High-res Image Gene #2: 'WT1 MUTATION STATUS' versus Clinical Feature #2: 'METHLYATION_CNMF'

'RUNX1 MUTATION STATUS' versus 'MRNASEQ_CNMF'

P value = 0.00152 (Fisher's exact test), Q value = 0.18

Table S2. Gene #3: 'RUNX1 MUTATION STATUS' versus Clinical Feature #3: 'MRNASEQ_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3
--- | --- | --- | ---
ALL | 73 | 52 | 45
RUNX1 MUTATED | 13 | 3 | 0
RUNX1 WILD-TYPE | 60 | 49 | 45

Figure S2. Get High-res Image Gene #3: 'RUNX1 MUTATION STATUS' versus Clinical Feature #3: 'MRNASEQ_CNMF'

'RUNX1 MUTATION STATUS' versus 'MIRSEQ_CHIERARCHICAL'

P value = 5.1e-05 (Fisher's exact test), Q value = 0.0063

Table S3. Gene #3: 'RUNX1 MUTATION STATUS' versus Clinical Feature #6: 'MIRSEQ_CHIERARCHICAL'

nPatients | CLUS_1 | CLUS_2 | CLUS_3
--- | --- | --- | ---
ALL | 38 | 81 | 65
RUNX1 MUTATED | 4 | 0 | 12
RUNX1 WILD-TYPE | 34 | 81 | 53

Figure S3. Get High-res Image Gene #3: 'RUNX1 MUTATION STATUS' versus Clinical Feature #6: 'MIRSEQ_CHIERARCHICAL'

'DNMT3A MUTATION STATUS' versus 'METHLYATION_CNMF'

P value = 3.03e-05 (Chi-square test), Q value = 0.0038

Table S4. Gene #4: 'DNMT3A MUTATION STATUS' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4 | CLUS_5 | CLUS_6
--- | --- | --- | --- | --- | --- | ---
ALL | 48 | 18 | 26 | 39 | 48 | 12
DNMT3A MUTATED | 25 | 0 | 5 | 6 | 12 | 1
DNMT3A WILD-TYPE | 23 | 18 | 21 | 33 | 36 | 11

Figure S4. Get High-res Image Gene #4: 'DNMT3A MUTATION STATUS' versus Clinical Feature #2: 'METHLYATION_CNMF'

'DNMT3A MUTATION STATUS' versus 'MIRSEQ_CNMF'

P value = 5.71e-05 (Fisher's exact test), Q value = 0.007

Table S5. Gene #4: 'DNMT3A MUTATION STATUS' versus Clinical Feature #5: 'MIRSEQ_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3
--- | --- | --- | ---
ALL | 84 | 40 | 60
DNMT3A MUTATED | 33 | 3 | 9
DNMT3A WILD-TYPE | 51 | 37 | 51

Figure S5. Get High-res Image Gene #4: 'DNMT3A MUTATION STATUS' versus Clinical Feature #5: 'MIRSEQ_CNMF'

'DNMT3A MUTATION STATUS' versus 'MIRSEQ_CHIERARCHICAL'

P value = 5.45e-06 (Fisher's exact test), Q value = 7e-04

Table S6. Gene #4: 'DNMT3A MUTATION STATUS' versus Clinical Feature #6: 'MIRSEQ_CHIERARCHICAL'

nPatients | CLUS_1 | CLUS_2 | CLUS_3
--- | --- | --- | ---
ALL | 38 | 81 | 65
DNMT3A MUTATED | 3 | 34 | 8
DNMT3A WILD-TYPE | 35 | 47 | 57

Figure S6. Get High-res Image Gene #4: 'DNMT3A MUTATION STATUS' versus Clinical Feature #6: 'MIRSEQ_CHIERARCHICAL'

'FLT3 MUTATION STATUS' versus 'METHLYATION_CNMF'

P value = 4.52e-05 (Chi-square test), Q value = 0.0056

Table S7. Gene #5: 'FLT3 MUTATION STATUS' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4 | CLUS_5 | CLUS_6
--- | --- | --- | --- | --- | --- | ---
ALL | 48 | 18 | 26 | 39 | 48 | 12
FLT3 MUTATED | 26 | 5 | 3 | 8 | 7 | 6
FLT3 WILD-TYPE | 22 | 13 | 23 | 31 | 41 | 6

Figure S7. Get High-res Image Gene #5: 'FLT3 MUTATION STATUS' versus Clinical Feature #2: 'METHLYATION_CNMF'

'FLT3 MUTATION STATUS' versus 'MRNASEQ_CNMF'

P value = 1.86e-07 (Fisher's exact test), Q value = 2.4e-05

Table S8. Gene #5: 'FLT3 MUTATION STATUS' versus Clinical Feature #3: 'MRNASEQ_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3
--- | --- | --- | ---
ALL | 73 | 52 | 45
FLT3 MUTATED | 6 | 20 | 23
FLT3 WILD-TYPE | 67 | 32 | 22

Figure S8. Get High-res Image Gene #5: 'FLT3 MUTATION STATUS' versus Clinical Feature #3: 'MRNASEQ_CNMF'

'FLT3 MUTATION STATUS' versus 'MIRSEQ_CNMF'

P value = 0.000285 (Fisher's exact test), Q value = 0.034

Table S9. Gene #5: 'FLT3 MUTATION STATUS' versus Clinical Feature #5: 'MIRSEQ_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3
--- | --- | --- | ---
ALL | 84 | 40 | 60
FLT3 MUTATED | 36 | 4 | 14
FLT3 WILD-TYPE | 48 | 36 | 46

Figure S9. Get High-res Image Gene #5: 'FLT3 MUTATION STATUS' versus Clinical Feature #5: 'MIRSEQ_CNMF'

'FLT3 MUTATION STATUS' versus 'MIRSEQ_CHIERARCHICAL'

P value = 1.28e-05 (Fisher's exact test), Q value = 0.0016

Table S10. Gene #5: 'FLT3 MUTATION STATUS' versus Clinical Feature #6: 'MIRSEQ_CHIERARCHICAL'

nPatients | CLUS_1 | CLUS_2 | CLUS_3
--- | --- | --- | ---
ALL | 38 | 81 | 65
FLT3 MUTATED | 4 | 38 | 12
FLT3 WILD-TYPE | 34 | 43 | 53

Figure S10. Get High-res Image Gene #5: 'FLT3 MUTATION STATUS' versus Clinical Feature #6: 'MIRSEQ_CHIERARCHICAL'

'IDH1 MUTATION STATUS' versus 'METHLYATION_CNMF'

P value = 7.04e-09 (Chi-square test), Q value = 9.3e-07

Table S11. Gene #6: 'IDH1 MUTATION STATUS' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4 | CLUS_5 | CLUS_6
--- | --- | --- | --- | --- | --- | ---
ALL | 48 | 18 | 26 | 39 | 48 | 12
IDH1 MUTATED | 4 | 0 | 12 | 0 | 3 | 0
IDH1 WILD-TYPE | 44 | 18 | 14 | 39 | 45 | 12

Figure S11. Get High-res Image Gene #6: 'IDH1 MUTATION STATUS' versus Clinical Feature #2: 'METHLYATION_CNMF'

'IDH2 MUTATION STATUS' versus 'METHLYATION_CNMF'

P value = 1.31e-09 (Chi-square test), Q value = 1.8e-07

Table S12. Gene #7: 'IDH2 MUTATION STATUS' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4 | CLUS_5 | CLUS_6
--- | --- | --- | --- | --- | --- | ---
ALL | 48 | 18 | 26 | 39 | 48 | 12
IDH2 MUTATED | 0 | 0 | 12 | 2 | 4 | 0
IDH2 WILD-TYPE | 48 | 18 | 14 | 37 | 44 | 12

Figure S12. Get High-res Image Gene #7: 'IDH2 MUTATION STATUS' versus Clinical Feature #2: 'METHLYATION_CNMF'

'NPM1 MUTATION STATUS' versus 'CN_CNMF'

P value = 0.000935 (Chi-square test), Q value = 0.11

Table S13. Gene #8: 'NPM1 MUTATION STATUS' versus Clinical Feature #1: 'CN_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4 | CLUS_5
--- | --- | --- | --- | --- | ---
ALL | 139 | 15 | 15 | 18 | 1
NPM1 MUTATED | 50 | 0 | 1 | 1 | 0
NPM1 WILD-TYPE | 89 | 15 | 14 | 17 | 1

Figure S13. Get High-res Image Gene #8: 'NPM1 MUTATION STATUS' versus Clinical Feature #1: 'CN_CNMF'

'NPM1 MUTATION STATUS' versus 'METHLYATION_CNMF'

P value = 3.11e-18 (Chi-square test), Q value = 4.3e-16

Table S14. Gene #8: 'NPM1 MUTATION STATUS' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4 | CLUS_5 | CLUS_6
--- | --- | --- | --- | --- | --- | ---
ALL | 48 | 18 | 26 | 39 | 48 | 12
NPM1 MUTATED | 36 | 0 | 11 | 0 | 2 | 4
NPM1 WILD-TYPE | 12 | 18 | 15 | 39 | 46 | 8

Figure S14. Get High-res Image Gene #8: 'NPM1 MUTATION STATUS' versus Clinical Feature #2: 'METHLYATION_CNMF'

'NPM1 MUTATION STATUS' versus 'MRNASEQ_CNMF'

P value = 1.79e-13 (Fisher's exact test), Q value = 2.4e-11

Table S15. Gene #8: 'NPM1 MUTATION STATUS' versus Clinical Feature #3: 'MRNASEQ_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3
--- | --- | --- | ---
ALL | 73 | 52 | 45
NPM1 MUTATED | 1 | 22 | 25
NPM1 WILD-TYPE | 72 | 30 | 20

Figure S15. Get High-res Image Gene #8: 'NPM1 MUTATION STATUS' versus Clinical Feature #3: 'MRNASEQ_CNMF'

'NPM1 MUTATION STATUS' versus 'MIRSEQ_CNMF'

P value = 2.17e-20 (Fisher's exact test), Q value = 3e-18

Table S16. Gene #8: 'NPM1 MUTATION STATUS' versus Clinical Feature #5: 'MIRSEQ_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3
--- | --- | --- | ---
ALL | 84 | 40 | 60
NPM1 MUTATED | 50 | 0 | 1
NPM1 WILD-TYPE | 34 | 40 | 59

Figure S16. Get High-res Image Gene #8: 'NPM1 MUTATION STATUS' versus Clinical Feature #5: 'MIRSEQ_CNMF'

'NPM1 MUTATION STATUS' versus 'MIRSEQ_CHIERARCHICAL'

P value = 1.79e-21 (Fisher's exact test), Q value = 2.5e-19

Table S17. Gene #8: 'NPM1 MUTATION STATUS' versus Clinical Feature #6: 'MIRSEQ_CHIERARCHICAL'

nPatients | CLUS_1 | CLUS_2 | CLUS_3
--- | --- | --- | ---
ALL | 38 | 81 | 65
NPM1 MUTATED | 0 | 50 | 1
NPM1 WILD-TYPE | 38 | 31 | 64

Figure S17. Get High-res Image Gene #8: 'NPM1 MUTATION STATUS' versus Clinical Feature #6: 'MIRSEQ_CHIERARCHICAL'

'TP53 MUTATION STATUS' versus 'CN_CNMF'

P value = 1.52e-10 (Chi-square test), Q value = 2.1e-08

Table S18. Gene #10: 'TP53 MUTATION STATUS' versus Clinical Feature #1: 'CN_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4 | CLUS_5
--- | --- | --- | --- | --- | ---
ALL | 139 | 15 | 15 | 18 | 1
TP53 MUTATED | 0 | 3 | 6 | 6 | 0
TP53 WILD-TYPE | 139 | 12 | 9 | 12 | 1

Figure S18. Get High-res Image Gene #10: 'TP53 MUTATION STATUS' versus Clinical Feature #1: 'CN_CNMF'

'TP53 MUTATION STATUS' versus 'METHLYATION_CNMF'

P value = 2.81e-09 (Chi-square test), Q value = 3.7e-07

Table S19. Gene #10: 'TP53 MUTATION STATUS' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4 | CLUS_5 | CLUS_6
--- | --- | --- | --- | --- | --- | ---
ALL | 48 | 18 | 26 | 39 | 48 | 12
TP53 MUTATED | 0 | 0 | 0 | 0 | 15 | 0
TP53 WILD-TYPE | 48 | 18 | 26 | 39 | 33 | 12

Figure S19. Get High-res Image Gene #10: 'TP53 MUTATION STATUS' versus Clinical Feature #2: 'METHLYATION_CNMF'

'TP53 MUTATION STATUS' versus 'MRNASEQ_CNMF'

P value = 0.000687 (Fisher's exact test), Q value = 0.082

Table S20. Gene #10: 'TP53 MUTATION STATUS' versus Clinical Feature #3: 'MRNASEQ_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3
--- | --- | --- | ---
ALL | 73 | 52 | 45
TP53 MUTATED | 12 | 1 | 0
TP53 WILD-TYPE | 61 | 51 | 45

Figure S20. Get High-res Image Gene #10: 'TP53 MUTATION STATUS' versus Clinical Feature #3: 'MRNASEQ_CNMF'

'TP53 MUTATION STATUS' versus 'MIRSEQ_CNMF'

P value = 0.000668 (Fisher's exact test), Q value = 0.08

Table S21. Gene #10: 'TP53 MUTATION STATUS' versus Clinical Feature #5: 'MIRSEQ_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3
--- | --- | --- | ---
ALL | 84 | 40 | 60
TP53 MUTATED | 2 | 9 | 3
TP53 WILD-TYPE | 82 | 31 | 57

Figure S21. Get High-res Image Gene #10: 'TP53 MUTATION STATUS' versus Clinical Feature #5: 'MIRSEQ_CNMF'

'TP53 MUTATION STATUS' versus 'MIRSEQ_CHIERARCHICAL'

P value = 0.000144 (Fisher's exact test), Q value = 0.018

Table S22. Gene #10: 'TP53 MUTATION STATUS' versus Clinical Feature #6: 'MIRSEQ_CHIERARCHICAL'

nPatients | CLUS_1 | CLUS_2 | CLUS_3
--- | --- | --- | ---
ALL | 38 | 81 | 65
TP53 MUTATED | 9 | 1 | 4
TP53 WILD-TYPE | 29 | 80 | 61

Figure S22. Get High-res Image Gene #10: 'TP53 MUTATION STATUS' versus Clinical Feature #6: 'MIRSEQ_CHIERARCHICAL'

'FAM5C MUTATION STATUS' versus 'CN_CNMF'

P value = 1.15e-07 (Chi-square test), Q value = 1.5e-05

Table S23. Gene #20: 'FAM5C MUTATION STATUS' versus Clinical Feature #1: 'CN_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4 | CLUS_5
--- | --- | --- | --- | --- | ---
ALL | 139 | 15 | 15 | 18 | 1
FAM5C MUTATED | 4 | 0 | 0 | 0 | 1
FAM5C WILD-TYPE | 135 | 15 | 15 | 18 | 0

Figure S23. Get High-res Image Gene #20: 'FAM5C MUTATION STATUS' versus Clinical Feature #1: 'CN_CNMF'

Methods & Data
Input

- Mutation data file = LAML-TB.mutsig.cluster.txt

- Molecular subtypes file = LAML-TB.transferedmergedcluster.txt

- Number of patients = 197

- Number of significantly mutated genes = 24

- 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.

- Analysis Results (MD5 checksum)

- Auxiliary Data (MD5 checksum)

- MAGE-TAB File (MD5 checksum)

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)
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