This pipeline computes the correlation between cancer subtypes identified by different molecular patterns and selected clinical features.
Testing the association between subtypes identified by 8 different clustering approaches and 8 clinical features across 103 patients, 9 significant findings detected with P value < 0.05 and Q value < 0.25.
-
CNMF clustering analysis on array-based mRNA expression data identified 2 subtypes that do not correlate to any clinical features.
-
Consensus hierarchical clustering analysis on array-based mRNA expression data identified 3 subtypes that do not correlate to any clinical features.
-
4 subtypes identified in current cancer cohort by 'Copy Number Ratio CNMF subtypes'. These subtypes do not correlate to any clinical features.
-
3 subtypes identified in current cancer cohort by 'METHLYATION CNMF'. These subtypes correlate to 'PATHOLOGY.T' and 'TUMOR.STAGE'.
-
CNMF clustering analysis on sequencing-based mRNA expression data identified 3 subtypes that correlate to 'PATHOLOGY.T' and 'TUMOR.STAGE'.
-
Consensus hierarchical clustering analysis on sequencing-based mRNA expression data identified 3 subtypes that correlate to 'GENDER', 'PATHOLOGY.T', 'PATHOLOGICSPREAD(M)', and 'TUMOR.STAGE'.
-
4 subtypes identified in current cancer cohort by 'MIRSEQ CNMF'. These subtypes do not correlate to any clinical features.
-
4 subtypes identified in current cancer cohort by 'MIRSEQ CHIERARCHICAL'. These subtypes correlate to 'PATHOLOGY.T'.
Clinical Features |
Time to Death |
AGE | GENDER |
KARNOFSKY PERFORMANCE SCORE |
PATHOLOGY T |
PATHOLOGY N |
PATHOLOGICSPREAD(M) |
TUMOR STAGE |
Statistical Tests | logrank test | ANOVA | Fisher's exact test | ANOVA | Chi-square test | Chi-square test | Chi-square test | Chi-square test |
mRNA CNMF subtypes |
100 (1.00) |
0.182 (1.00) |
0.585 (1.00) |
0.0623 (1.00) |
1 (1.00) |
0.292 (1.00) |
||
mRNA cHierClus subtypes |
100 (1.00) |
0.948 (1.00) |
1 (1.00) |
0.216 (1.00) |
1 (1.00) |
|||
Copy Number Ratio CNMF subtypes |
0.12 (1.00) |
0.575 (1.00) |
0.707 (1.00) |
0.421 (1.00) |
0.0662 (1.00) |
0.551 (1.00) |
0.152 (1.00) |
0.0318 (1.00) |
METHLYATION CNMF |
0.15 (1.00) |
0.0523 (1.00) |
0.226 (1.00) |
0.144 (1.00) |
6.37e-08 (3.69e-06) |
0.142 (1.00) |
0.0567 (1.00) |
7.93e-06 (0.000452) |
RNAseq CNMF subtypes |
0.0277 (1.00) |
0.00648 (0.318) |
0.0242 (1.00) |
0.000102 (0.00552) |
0.636 (1.00) |
0.0115 (0.521) |
9.52e-05 (0.00524) |
|
RNAseq cHierClus subtypes |
0.0127 (0.557) |
0.454 (1.00) |
0.000595 (0.031) |
0.578 (1.00) |
0.000293 (0.0155) |
0.0583 (1.00) |
0.00397 (0.198) |
2.81e-05 (0.00157) |
MIRSEQ CNMF |
0.99 (1.00) |
0.118 (1.00) |
0.00719 (0.345) |
0.488 (1.00) |
0.0113 (0.521) |
0.185 (1.00) |
0.192 (1.00) |
0.0283 (1.00) |
MIRSEQ CHIERARCHICAL |
0.344 (1.00) |
0.496 (1.00) |
0.0367 (1.00) |
0.324 (1.00) |
0.00108 (0.0553) |
0.288 (1.00) |
0.343 (1.00) |
0.00899 (0.422) |
Cluster Labels | 1 | 2 |
---|---|---|
Number of samples | 7 | 9 |
P value = 100 (logrank test), Q value = 1
nPatients | nDeath | Duration Range (Median), Month | |
---|---|---|---|
ALL | 16 | 2 | 0.5 - 58.5 (7.8) |
subtype1 | 7 | 1 | 0.5 - 53.8 (5.9) |
subtype2 | 9 | 1 | 1.1 - 58.5 (10.8) |
P value = 0.182 (t-test), Q value = 1
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 16 | 57.9 (11.5) |
subtype1 | 7 | 53.6 (10.3) |
subtype2 | 9 | 61.3 (11.7) |
P value = 0.585 (Fisher's exact test), Q value = 1
nPatients | FEMALE | MALE |
---|---|---|
ALL | 4 | 12 |
subtype1 | 1 | 6 |
subtype2 | 3 | 6 |
P value = 0.0623 (Chi-square test), Q value = 1
nPatients | T1 | T2 | T3+T4 |
---|---|---|---|
ALL | 7 | 7 | 2 |
subtype1 | 1 | 4 | 2 |
subtype2 | 6 | 3 | 0 |
P value = 0.292 (Chi-square test), Q value = 1
nPatients | I | II | III | IV |
---|---|---|---|---|
ALL | 5 | 2 | 1 | 1 |
subtype1 | 1 | 1 | 1 | 1 |
subtype2 | 4 | 1 | 0 | 0 |
Cluster Labels | 1 | 2 | 3 |
---|---|---|---|
Number of samples | 4 | 7 | 5 |
P value = 100 (logrank test), Q value = 1
nPatients | nDeath | Duration Range (Median), Month | |
---|---|---|---|
ALL | 16 | 2 | 0.5 - 58.5 (7.8) |
subtype1 | 4 | 1 | 10.8 - 58.5 (40.4) |
subtype2 | 7 | 1 | 0.5 - 25.1 (4.4) |
subtype3 | 5 | 0 | 0.7 - 53.8 (4.1) |
P value = 0.948 (ANOVA), Q value = 1
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 16 | 57.9 (11.5) |
subtype1 | 4 | 57.0 (5.0) |
subtype2 | 7 | 57.4 (13.0) |
subtype3 | 5 | 59.4 (14.8) |
P value = 1 (Fisher's exact test), Q value = 1
nPatients | FEMALE | MALE |
---|---|---|
ALL | 4 | 12 |
subtype1 | 1 | 3 |
subtype2 | 2 | 5 |
subtype3 | 1 | 4 |
P value = 0.216 (Chi-square test), Q value = 1
nPatients | T1 | T2 | T3+T4 |
---|---|---|---|
ALL | 7 | 7 | 2 |
subtype1 | 3 | 1 | 0 |
subtype2 | 1 | 4 | 2 |
subtype3 | 3 | 2 | 0 |
P value = NA (Chi-square test), Q value = 1
nPatients | I | II | III | IV |
---|---|---|---|---|
ALL | 5 | 2 | 1 | 1 |
subtype1 | 2 | 0 | 0 | 0 |
subtype2 | 1 | 2 | 1 | 1 |
subtype3 | 2 | 0 | 0 | 0 |
Cluster Labels | 1 | 2 | 3 | 4 |
---|---|---|---|---|
Number of samples | 21 | 16 | 25 | 41 |
P value = 0.12 (logrank test), Q value = 1
nPatients | nDeath | Duration Range (Median), Month | |
---|---|---|---|
ALL | 96 | 14 | 0.0 - 182.7 (13.7) |
subtype1 | 20 | 2 | 0.0 - 182.7 (9.5) |
subtype2 | 15 | 1 | 0.0 - 50.5 (13.6) |
subtype3 | 25 | 6 | 0.1 - 80.8 (11.1) |
subtype4 | 36 | 5 | 0.2 - 129.9 (24.9) |
P value = 0.575 (ANOVA), Q value = 1
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 100 | 59.7 (12.4) |
subtype1 | 20 | 60.1 (11.2) |
subtype2 | 15 | 55.5 (9.1) |
subtype3 | 25 | 60.1 (14.1) |
subtype4 | 40 | 60.8 (13.1) |
P value = 0.707 (Fisher's exact test), Q value = 1
nPatients | FEMALE | MALE |
---|---|---|
ALL | 33 | 70 |
subtype1 | 6 | 15 |
subtype2 | 4 | 12 |
subtype3 | 7 | 18 |
subtype4 | 16 | 25 |
P value = 0.421 (ANOVA), Q value = 1
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 21 | 87.6 (23.9) |
subtype1 | 4 | 97.5 (5.0) |
subtype2 | 5 | 96.0 (5.5) |
subtype3 | 5 | 74.0 (41.6) |
subtype4 | 7 | 85.7 (20.7) |
P value = 0.0662 (Chi-square test), Q value = 1
nPatients | T1 | T2 | T3+T4 |
---|---|---|---|
ALL | 58 | 13 | 32 |
subtype1 | 13 | 4 | 4 |
subtype2 | 10 | 4 | 2 |
subtype3 | 10 | 2 | 13 |
subtype4 | 25 | 3 | 13 |
P value = 0.551 (Chi-square test), Q value = 1
nPatients | N0 | N1 | N2 |
---|---|---|---|
ALL | 20 | 11 | 4 |
subtype1 | 2 | 1 | 0 |
subtype2 | 3 | 0 | 0 |
subtype3 | 7 | 7 | 3 |
subtype4 | 8 | 3 | 1 |
P value = 0.152 (Chi-square test), Q value = 1
nPatients | M0 | M1 | MX |
---|---|---|---|
ALL | 54 | 5 | 35 |
subtype1 | 11 | 0 | 6 |
subtype2 | 7 | 0 | 7 |
subtype3 | 12 | 4 | 8 |
subtype4 | 24 | 1 | 14 |
P value = 0.0318 (Chi-square test), Q value = 1
nPatients | I | II | III | IV |
---|---|---|---|---|
ALL | 53 | 7 | 23 | 9 |
subtype1 | 12 | 2 | 2 | 1 |
subtype2 | 9 | 1 | 2 | 0 |
subtype3 | 10 | 1 | 6 | 7 |
subtype4 | 22 | 3 | 13 | 1 |
Cluster Labels | 1 | 2 | 3 |
---|---|---|---|
Number of samples | 21 | 26 | 38 |
P value = 0.15 (logrank test), Q value = 1
nPatients | nDeath | Duration Range (Median), Month | |
---|---|---|---|
ALL | 78 | 12 | 0.0 - 182.7 (15.7) |
subtype1 | 19 | 4 | 0.0 - 80.8 (26.0) |
subtype2 | 25 | 6 | 0.2 - 182.7 (12.0) |
subtype3 | 34 | 2 | 0.0 - 129.9 (14.8) |
P value = 0.0523 (ANOVA), Q value = 1
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 82 | 60.0 (12.7) |
subtype1 | 20 | 65.8 (10.0) |
subtype2 | 25 | 59.4 (16.3) |
subtype3 | 37 | 57.3 (10.2) |
P value = 0.226 (Fisher's exact test), Q value = 1
nPatients | FEMALE | MALE |
---|---|---|
ALL | 28 | 57 |
subtype1 | 6 | 15 |
subtype2 | 12 | 14 |
subtype3 | 10 | 28 |
P value = 0.144 (ANOVA), Q value = 1
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 20 | 92.0 (13.2) |
subtype1 | 6 | 81.7 (20.4) |
subtype2 | 1 | 100.0 (NA) |
subtype3 | 13 | 96.2 (5.1) |
P value = 6.37e-08 (Chi-square test), Q value = 3.7e-06
nPatients | T1 | T2 | T3+T4 |
---|---|---|---|
ALL | 49 | 6 | 30 |
subtype1 | 15 | 0 | 6 |
subtype2 | 4 | 1 | 21 |
subtype3 | 30 | 5 | 3 |
P value = 0.142 (Chi-square test), Q value = 1
nPatients | N0 | N1 | N2 |
---|---|---|---|
ALL | 20 | 9 | 4 |
subtype1 | 3 | 2 | 1 |
subtype2 | 9 | 7 | 3 |
subtype3 | 8 | 0 | 0 |
P value = 0.0567 (Chi-square test), Q value = 1
nPatients | M0 | M1 | MX |
---|---|---|---|
ALL | 45 | 4 | 33 |
subtype1 | 13 | 1 | 6 |
subtype2 | 16 | 3 | 7 |
subtype3 | 16 | 0 | 20 |
P value = 7.93e-06 (Chi-square test), Q value = 0.00045
nPatients | I | II | III | IV |
---|---|---|---|---|
ALL | 46 | 5 | 22 | 8 |
subtype1 | 14 | 1 | 3 | 2 |
subtype2 | 4 | 1 | 15 | 6 |
subtype3 | 28 | 3 | 4 | 0 |
Cluster Labels | 1 | 2 | 3 |
---|---|---|---|
Number of samples | 26 | 23 | 25 |
P value = 0.0277 (logrank test), Q value = 1
nPatients | nDeath | Duration Range (Median), Month | |
---|---|---|---|
ALL | 71 | 13 | 0.5 - 182.7 (15.5) |
subtype1 | 24 | 3 | 0.5 - 54.9 (13.1) |
subtype2 | 22 | 8 | 0.9 - 93.3 (12.2) |
subtype3 | 25 | 2 | 6.4 - 182.7 (26.0) |
P value = 0.00648 (ANOVA), Q value = 0.32
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 71 | 59.7 (13.2) |
subtype1 | 24 | 56.5 (12.1) |
subtype2 | 22 | 55.8 (14.6) |
subtype3 | 25 | 66.3 (10.5) |
P value = 0.0242 (Fisher's exact test), Q value = 1
nPatients | FEMALE | MALE |
---|---|---|
ALL | 22 | 52 |
subtype1 | 5 | 21 |
subtype2 | 12 | 11 |
subtype3 | 5 | 20 |
P value = 0.000102 (Chi-square test), Q value = 0.0055
nPatients | T1 | T2 | T3+T4 |
---|---|---|---|
ALL | 38 | 9 | 27 |
subtype1 | 20 | 5 | 1 |
subtype2 | 5 | 2 | 16 |
subtype3 | 13 | 2 | 10 |
P value = 0.636 (Chi-square test), Q value = 1
nPatients | N0 | N1 | N2 |
---|---|---|---|
ALL | 15 | 11 | 3 |
subtype1 | 2 | 0 | 0 |
subtype2 | 6 | 7 | 2 |
subtype3 | 7 | 4 | 1 |
P value = 0.0115 (Chi-square test), Q value = 0.52
nPatients | M0 | M1 | MX |
---|---|---|---|
ALL | 46 | 5 | 16 |
subtype1 | 14 | 0 | 7 |
subtype2 | 12 | 5 | 5 |
subtype3 | 20 | 0 | 4 |
P value = 9.52e-05 (Chi-square test), Q value = 0.0052
nPatients | I | II | III | IV |
---|---|---|---|---|
ALL | 35 | 3 | 20 | 8 |
subtype1 | 19 | 0 | 2 | 0 |
subtype2 | 4 | 1 | 9 | 7 |
subtype3 | 12 | 2 | 9 | 1 |
Cluster Labels | 1 | 2 | 3 |
---|---|---|---|
Number of samples | 18 | 36 | 20 |
P value = 0.0127 (logrank test), Q value = 0.56
nPatients | nDeath | Duration Range (Median), Month | |
---|---|---|---|
ALL | 71 | 13 | 0.5 - 182.7 (15.5) |
subtype1 | 17 | 6 | 2.8 - 80.8 (10.8) |
subtype2 | 34 | 3 | 0.5 - 182.7 (13.8) |
subtype3 | 20 | 4 | 0.9 - 123.6 (25.2) |
P value = 0.454 (ANOVA), Q value = 1
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 71 | 59.7 (13.2) |
subtype1 | 17 | 57.3 (15.0) |
subtype2 | 34 | 59.3 (11.7) |
subtype3 | 20 | 62.6 (14.0) |
P value = 0.000595 (Fisher's exact test), Q value = 0.031
nPatients | FEMALE | MALE |
---|---|---|
ALL | 22 | 52 |
subtype1 | 11 | 7 |
subtype2 | 4 | 32 |
subtype3 | 7 | 13 |
P value = 0.578 (ANOVA), Q value = 1
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 11 | 86.4 (29.1) |
subtype1 | 3 | 93.3 (5.8) |
subtype2 | 7 | 95.7 (5.3) |
subtype3 | 1 | 0.0 (NA) |
P value = 0.000293 (Chi-square test), Q value = 0.016
nPatients | T1 | T2 | T3+T4 |
---|---|---|---|
ALL | 38 | 9 | 27 |
subtype1 | 7 | 2 | 9 |
subtype2 | 26 | 6 | 4 |
subtype3 | 5 | 1 | 14 |
P value = 0.0583 (Chi-square test), Q value = 1
nPatients | N0 | N1 | N2 |
---|---|---|---|
ALL | 15 | 11 | 3 |
subtype1 | 1 | 6 | 2 |
subtype2 | 4 | 1 | 0 |
subtype3 | 10 | 4 | 1 |
P value = 0.00397 (Chi-square test), Q value = 0.2
nPatients | M0 | M1 | MX |
---|---|---|---|
ALL | 46 | 5 | 16 |
subtype1 | 9 | 4 | 4 |
subtype2 | 19 | 0 | 11 |
subtype3 | 18 | 1 | 1 |
P value = 2.81e-05 (Chi-square test), Q value = 0.0016
nPatients | I | II | III | IV |
---|---|---|---|---|
ALL | 35 | 3 | 20 | 8 |
subtype1 | 6 | 1 | 3 | 6 |
subtype2 | 24 | 1 | 4 | 1 |
subtype3 | 5 | 1 | 13 | 1 |
Cluster Labels | 1 | 2 | 3 | 4 |
---|---|---|---|---|
Number of samples | 24 | 34 | 29 | 16 |
P value = 0.99 (logrank test), Q value = 1
nPatients | nDeath | Duration Range (Median), Month | |
---|---|---|---|
ALL | 96 | 14 | 0.0 - 182.7 (13.7) |
subtype1 | 24 | 4 | 0.0 - 63.7 (18.1) |
subtype2 | 32 | 5 | 0.2 - 182.7 (17.4) |
subtype3 | 24 | 3 | 0.0 - 123.6 (13.0) |
subtype4 | 16 | 2 | 0.5 - 86.7 (11.3) |
P value = 0.118 (ANOVA), Q value = 1
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 100 | 59.7 (12.4) |
subtype1 | 24 | 62.1 (12.6) |
subtype2 | 34 | 56.2 (13.7) |
subtype3 | 26 | 63.1 (10.1) |
subtype4 | 16 | 58.0 (11.5) |
P value = 0.00719 (Fisher's exact test), Q value = 0.35
nPatients | FEMALE | MALE |
---|---|---|
ALL | 33 | 70 |
subtype1 | 3 | 21 |
subtype2 | 16 | 18 |
subtype3 | 6 | 23 |
subtype4 | 8 | 8 |
P value = 0.488 (ANOVA), Q value = 1
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 21 | 87.6 (23.9) |
subtype1 | 5 | 94.0 (5.5) |
subtype2 | 11 | 80.9 (31.8) |
subtype3 | 4 | 95.0 (5.8) |
subtype4 | 1 | 100.0 (NA) |
P value = 0.0113 (Chi-square test), Q value = 0.52
nPatients | T1 | T2 | T3+T4 |
---|---|---|---|
ALL | 58 | 13 | 32 |
subtype1 | 13 | 2 | 9 |
subtype2 | 19 | 2 | 13 |
subtype3 | 22 | 4 | 3 |
subtype4 | 4 | 5 | 7 |
P value = 0.185 (Chi-square test), Q value = 1
nPatients | N0 | N1 | N2 |
---|---|---|---|
ALL | 20 | 11 | 4 |
subtype1 | 7 | 2 | 1 |
subtype2 | 5 | 6 | 3 |
subtype3 | 5 | 0 | 0 |
subtype4 | 3 | 3 | 0 |
P value = 0.192 (Chi-square test), Q value = 1
nPatients | M0 | M1 | MX |
---|---|---|---|
ALL | 54 | 5 | 35 |
subtype1 | 14 | 0 | 8 |
subtype2 | 17 | 3 | 14 |
subtype3 | 14 | 0 | 11 |
subtype4 | 9 | 2 | 2 |
P value = 0.0283 (Chi-square test), Q value = 1
nPatients | I | II | III | IV |
---|---|---|---|---|
ALL | 53 | 7 | 23 | 9 |
subtype1 | 12 | 2 | 8 | 0 |
subtype2 | 18 | 3 | 6 | 7 |
subtype3 | 20 | 1 | 4 | 0 |
subtype4 | 3 | 1 | 5 | 2 |
Cluster Labels | 1 | 2 | 3 | 4 |
---|---|---|---|---|
Number of samples | 24 | 40 | 11 | 28 |
P value = 0.344 (logrank test), Q value = 1
nPatients | nDeath | Duration Range (Median), Month | |
---|---|---|---|
ALL | 96 | 14 | 0.0 - 182.7 (13.7) |
subtype1 | 24 | 5 | 0.9 - 86.7 (18.1) |
subtype2 | 36 | 7 | 0.2 - 182.7 (17.8) |
subtype3 | 10 | 0 | 3.8 - 96.9 (22.6) |
subtype4 | 26 | 2 | 0.0 - 123.6 (6.6) |
P value = 0.496 (ANOVA), Q value = 1
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 100 | 59.7 (12.4) |
subtype1 | 24 | 63.0 (13.2) |
subtype2 | 39 | 58.7 (13.8) |
subtype3 | 10 | 57.1 (12.0) |
subtype4 | 27 | 59.1 (9.6) |
P value = 0.0367 (Fisher's exact test), Q value = 1
nPatients | FEMALE | MALE |
---|---|---|
ALL | 33 | 70 |
subtype1 | 4 | 20 |
subtype2 | 18 | 22 |
subtype3 | 1 | 10 |
subtype4 | 10 | 18 |
P value = 0.324 (ANOVA), Q value = 1
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 21 | 87.6 (23.9) |
subtype1 | 4 | 70.0 (46.9) |
subtype2 | 11 | 89.1 (17.0) |
subtype3 | 2 | 100.0 (0.0) |
subtype4 | 4 | 95.0 (5.8) |
P value = 0.00108 (Chi-square test), Q value = 0.055
nPatients | T1 | T2 | T3+T4 |
---|---|---|---|
ALL | 58 | 13 | 32 |
subtype1 | 9 | 2 | 13 |
subtype2 | 22 | 3 | 15 |
subtype3 | 10 | 0 | 1 |
subtype4 | 17 | 8 | 3 |
P value = 0.288 (Chi-square test), Q value = 1
nPatients | N0 | N1 | N2 |
---|---|---|---|
ALL | 20 | 11 | 4 |
subtype1 | 8 | 4 | 1 |
subtype2 | 7 | 7 | 3 |
subtype3 | 1 | 0 | 0 |
subtype4 | 4 | 0 | 0 |
P value = 0.343 (Chi-square test), Q value = 1
nPatients | M0 | M1 | MX |
---|---|---|---|
ALL | 54 | 5 | 35 |
subtype1 | 17 | 1 | 6 |
subtype2 | 19 | 4 | 17 |
subtype3 | 7 | 0 | 3 |
subtype4 | 11 | 0 | 9 |
P value = 0.00899 (Chi-square test), Q value = 0.42
nPatients | I | II | III | IV |
---|---|---|---|---|
ALL | 53 | 7 | 23 | 9 |
subtype1 | 9 | 2 | 12 | 1 |
subtype2 | 21 | 3 | 7 | 8 |
subtype3 | 9 | 0 | 1 | 0 |
subtype4 | 14 | 2 | 3 | 0 |
-
Cluster data file = KIRP-TP.mergedcluster.txt
-
Clinical data file = KIRP-TP.clin.merged.picked.txt
-
Number of patients = 103
-
Number of clustering approaches = 8
-
Number of selected clinical features = 8
-
Exclude small clusters that include fewer than K patients, K = 3
consensus non-negative matrix factorization clustering approach (Brunet et al. 2004)
Resampling-based clustering method (Monti et al. 2003)
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
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 two tumor subtypes using 't.test' function in R
For binary clinical features, two-tailed Fisher's exact tests (Fisher 1922) were used to estimate the P values using the 'fisher.test' function in R
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
For continuous numerical clinical features, one-way analysis of variance (Howell 2002) was applied to compare the clinical values between tumor subtypes using 'anova' function in R
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.
This is an experimental feature. The full results of the analysis summarized in this report can be downloaded from the TCGA Data Coordination Center.