This pipeline computes the correlation between cancer subtypes identified by different molecular patterns and selected clinical features.
Testing the association between subtypes identified by 6 different clustering approaches and 5 clinical features across 200 patients, 5 significant findings detected with P value < 0.05 and Q value < 0.25.
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4 subtypes identified in current cancer cohort by 'Copy Number Ratio CNMF subtypes'. These subtypes correlate to 'Time to Death'.
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5 subtypes identified in current cancer cohort by 'METHLYATION CNMF'. These subtypes correlate to 'Time to Death' and 'AGE'.
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CNMF clustering analysis on sequencing-based mRNA expression data identified 3 subtypes that do not correlate to any clinical features.
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Consensus hierarchical clustering analysis on sequencing-based mRNA expression data identified 6 subtypes that correlate to 'Time to Death' and 'AGE'.
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4 subtypes identified in current cancer cohort by 'MIRSEQ CNMF'. These subtypes do not correlate to any clinical features.
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3 subtypes identified in current cancer cohort by 'MIRSEQ CHIERARCHICAL'. These subtypes do not correlate to any clinical features.
Clinical Features |
Time to Death |
AGE | GENDER | RACE | ETHNICITY |
Statistical Tests | logrank test | Kruskal-Wallis (anova) | Fisher's exact test | Fisher's exact test | Fisher's exact test |
Copy Number Ratio CNMF subtypes |
0.00158 (0.041) |
0.0376 (0.865) |
0.0393 (0.865) |
1 (1.00) |
0.296 (1.00) |
METHLYATION CNMF |
9.57e-05 (0.00268) |
2.57e-09 (7.72e-08) |
0.321 (1.00) |
0.675 (1.00) |
1 (1.00) |
RNAseq CNMF subtypes |
0.502 (1.00) |
0.24 (1.00) |
0.099 (1.00) |
0.0358 (0.86) |
0.581 (1.00) |
RNAseq cHierClus subtypes |
0.000903 (0.0244) |
3.26e-05 (0.000947) |
0.411 (1.00) |
0.144 (1.00) |
0.0828 (1.00) |
MIRSEQ CNMF |
0.0943 (1.00) |
0.0105 (0.262) |
0.921 (1.00) |
0.857 (1.00) |
1 (1.00) |
MIRSEQ CHIERARCHICAL |
0.194 (1.00) |
0.457 (1.00) |
0.388 (1.00) |
0.957 (1.00) |
1 (1.00) |
Cluster Labels | 1 | 2 | 3 | 4 |
---|---|---|---|---|
Number of samples | 147 | 14 | 27 | 3 |
P value = 0.00158 (logrank test), Q value = 0.041
nPatients | nDeath | Duration Range (Median), Month | |
---|---|---|---|
ALL | 168 | 106 | 0.9 - 94.1 (12.0) |
subtype1 | 130 | 76 | 0.9 - 94.1 (14.4) |
subtype2 | 11 | 8 | 0.9 - 42.0 (10.0) |
subtype3 | 25 | 21 | 1.0 - 73.0 (9.0) |
subtype4 | 2 | 1 | 4.0 - 15.0 (9.5) |
P value = 0.0376 (Kruskal-Wallis (anova)), Q value = 0.87
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 191 | 55.2 (16.1) |
subtype1 | 147 | 53.7 (16.1) |
subtype2 | 14 | 62.4 (13.1) |
subtype3 | 27 | 58.7 (16.6) |
subtype4 | 3 | 67.7 (6.7) |
P value = 0.0393 (Fisher's exact test), Q value = 0.87
nPatients | FEMALE | MALE |
---|---|---|
ALL | 87 | 104 |
subtype1 | 73 | 74 |
subtype2 | 6 | 8 |
subtype3 | 6 | 21 |
subtype4 | 2 | 1 |
P value = 1 (Fisher's exact test), Q value = 1
nPatients | ASIAN | BLACK OR AFRICAN AMERICAN | WHITE |
---|---|---|---|
ALL | 2 | 14 | 173 |
subtype1 | 2 | 11 | 132 |
subtype2 | 0 | 1 | 13 |
subtype3 | 0 | 2 | 25 |
subtype4 | 0 | 0 | 3 |
P value = 0.296 (Fisher's exact test), Q value = 1
nPatients | HISPANIC OR LATINO | NOT HISPANIC OR LATINO |
---|---|---|
ALL | 3 | 185 |
subtype1 | 2 | 142 |
subtype2 | 1 | 13 |
subtype3 | 0 | 27 |
subtype4 | 0 | 3 |
Cluster Labels | 1 | 2 | 3 | 4 | 5 |
---|---|---|---|---|---|
Number of samples | 48 | 45 | 65 | 14 | 22 |
P value = 9.57e-05 (logrank test), Q value = 0.0027
nPatients | nDeath | Duration Range (Median), Month | |
---|---|---|---|
ALL | 169 | 106 | 0.9 - 94.1 (12.0) |
subtype1 | 42 | 30 | 1.0 - 69.0 (8.1) |
subtype2 | 42 | 13 | 0.9 - 94.1 (21.6) |
subtype3 | 55 | 43 | 0.9 - 56.1 (12.0) |
subtype4 | 13 | 7 | 1.0 - 42.0 (13.0) |
subtype5 | 17 | 13 | 4.0 - 73.0 (12.0) |
P value = 2.57e-09 (Kruskal-Wallis (anova)), Q value = 7.7e-08
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 194 | 55.1 (16.0) |
subtype1 | 48 | 55.9 (14.1) |
subtype2 | 45 | 45.6 (15.5) |
subtype3 | 65 | 63.1 (12.9) |
subtype4 | 14 | 63.5 (11.2) |
subtype5 | 22 | 43.9 (16.0) |
P value = 0.321 (Fisher's exact test), Q value = 1
nPatients | FEMALE | MALE |
---|---|---|
ALL | 89 | 105 |
subtype1 | 24 | 24 |
subtype2 | 24 | 21 |
subtype3 | 26 | 39 |
subtype4 | 8 | 6 |
subtype5 | 7 | 15 |
P value = 0.675 (Fisher's exact test), Q value = 1
nPatients | ASIAN | BLACK OR AFRICAN AMERICAN | WHITE |
---|---|---|---|
ALL | 2 | 13 | 177 |
subtype1 | 1 | 2 | 45 |
subtype2 | 1 | 2 | 41 |
subtype3 | 0 | 6 | 59 |
subtype4 | 0 | 2 | 12 |
subtype5 | 0 | 1 | 20 |
P value = 1 (Fisher's exact test), Q value = 1
nPatients | HISPANIC OR LATINO | NOT HISPANIC OR LATINO |
---|---|---|
ALL | 1 | 190 |
subtype1 | 0 | 48 |
subtype2 | 0 | 44 |
subtype3 | 1 | 63 |
subtype4 | 0 | 14 |
subtype5 | 0 | 21 |
Cluster Labels | 1 | 2 | 3 |
---|---|---|---|
Number of samples | 74 | 54 | 45 |
P value = 0.502 (logrank test), Q value = 1
nPatients | nDeath | Duration Range (Median), Month | |
---|---|---|---|
ALL | 151 | 94 | 0.9 - 94.1 (12.0) |
subtype1 | 65 | 39 | 1.0 - 94.1 (16.1) |
subtype2 | 48 | 31 | 0.9 - 75.1 (10.5) |
subtype3 | 38 | 24 | 0.9 - 62.0 (12.0) |
P value = 0.24 (Kruskal-Wallis (anova)), Q value = 1
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 173 | 55.3 (16.1) |
subtype1 | 74 | 54.4 (17.3) |
subtype2 | 54 | 58.4 (13.9) |
subtype3 | 45 | 52.9 (16.4) |
P value = 0.099 (Fisher's exact test), Q value = 1
nPatients | FEMALE | MALE |
---|---|---|
ALL | 80 | 93 |
subtype1 | 31 | 43 |
subtype2 | 22 | 32 |
subtype3 | 27 | 18 |
P value = 0.0358 (Fisher's exact test), Q value = 0.86
nPatients | ASIAN | BLACK OR AFRICAN AMERICAN | WHITE |
---|---|---|---|
ALL | 2 | 13 | 156 |
subtype1 | 1 | 3 | 68 |
subtype2 | 1 | 2 | 51 |
subtype3 | 0 | 8 | 37 |
P value = 0.581 (Fisher's exact test), Q value = 1
nPatients | HISPANIC OR LATINO | NOT HISPANIC OR LATINO |
---|---|---|
ALL | 1 | 169 |
subtype1 | 0 | 71 |
subtype2 | 1 | 53 |
subtype3 | 0 | 45 |
Cluster Labels | 1 | 2 | 3 | 4 | 5 | 6 |
---|---|---|---|---|---|---|
Number of samples | 16 | 14 | 15 | 58 | 26 | 44 |
P value = 0.000903 (logrank test), Q value = 0.024
nPatients | nDeath | Duration Range (Median), Month | |
---|---|---|---|
ALL | 151 | 94 | 0.9 - 94.1 (12.0) |
subtype1 | 15 | 4 | 0.9 - 62.0 (46.1) |
subtype2 | 14 | 5 | 0.9 - 75.1 (20.0) |
subtype3 | 13 | 6 | 6.0 - 94.1 (19.0) |
subtype4 | 50 | 38 | 1.0 - 73.0 (11.5) |
subtype5 | 23 | 13 | 1.0 - 62.0 (10.0) |
subtype6 | 36 | 28 | 1.0 - 69.0 (9.5) |
P value = 3.26e-05 (Kruskal-Wallis (anova)), Q value = 0.00095
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 173 | 55.3 (16.1) |
subtype1 | 16 | 47.8 (14.9) |
subtype2 | 14 | 57.7 (14.6) |
subtype3 | 15 | 36.6 (13.9) |
subtype4 | 58 | 59.8 (15.5) |
subtype5 | 26 | 53.3 (16.7) |
subtype6 | 44 | 58.7 (13.0) |
P value = 0.411 (Fisher's exact test), Q value = 1
nPatients | FEMALE | MALE |
---|---|---|
ALL | 80 | 93 |
subtype1 | 9 | 7 |
subtype2 | 6 | 8 |
subtype3 | 6 | 9 |
subtype4 | 22 | 36 |
subtype5 | 16 | 10 |
subtype6 | 21 | 23 |
P value = 0.144 (Fisher's exact test), Q value = 1
nPatients | ASIAN | BLACK OR AFRICAN AMERICAN | WHITE |
---|---|---|---|
ALL | 2 | 13 | 156 |
subtype1 | 0 | 2 | 13 |
subtype2 | 0 | 0 | 14 |
subtype3 | 0 | 0 | 15 |
subtype4 | 1 | 3 | 53 |
subtype5 | 0 | 6 | 20 |
subtype6 | 1 | 2 | 41 |
P value = 0.0828 (Fisher's exact test), Q value = 1
nPatients | HISPANIC OR LATINO | NOT HISPANIC OR LATINO |
---|---|---|
ALL | 1 | 169 |
subtype1 | 0 | 15 |
subtype2 | 1 | 13 |
subtype3 | 0 | 15 |
subtype4 | 0 | 56 |
subtype5 | 0 | 26 |
subtype6 | 0 | 44 |
Cluster Labels | 1 | 2 | 3 | 4 |
---|---|---|---|---|
Number of samples | 60 | 38 | 43 | 47 |
P value = 0.0943 (logrank test), Q value = 1
nPatients | nDeath | Duration Range (Median), Month | |
---|---|---|---|
ALL | 164 | 102 | 0.9 - 94.1 (12.0) |
subtype1 | 53 | 38 | 1.0 - 69.0 (9.0) |
subtype2 | 34 | 18 | 0.9 - 62.0 (14.5) |
subtype3 | 35 | 23 | 1.0 - 94.1 (12.0) |
subtype4 | 42 | 23 | 0.9 - 73.0 (15.5) |
P value = 0.0105 (Kruskal-Wallis (anova)), Q value = 0.26
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 188 | 54.9 (16.2) |
subtype1 | 60 | 57.4 (14.3) |
subtype2 | 38 | 56.6 (14.9) |
subtype3 | 43 | 57.4 (18.0) |
subtype4 | 47 | 48.0 (16.2) |
P value = 0.921 (Fisher's exact test), Q value = 1
nPatients | FEMALE | MALE |
---|---|---|
ALL | 87 | 101 |
subtype1 | 26 | 34 |
subtype2 | 17 | 21 |
subtype3 | 21 | 22 |
subtype4 | 23 | 24 |
P value = 0.857 (Fisher's exact test), Q value = 1
nPatients | ASIAN | BLACK OR AFRICAN AMERICAN | WHITE |
---|---|---|---|
ALL | 2 | 13 | 171 |
subtype1 | 1 | 4 | 55 |
subtype2 | 0 | 2 | 36 |
subtype3 | 0 | 2 | 40 |
subtype4 | 1 | 5 | 40 |
P value = 1 (Fisher's exact test), Q value = 1
nPatients | HISPANIC OR LATINO | NOT HISPANIC OR LATINO |
---|---|---|
ALL | 1 | 184 |
subtype1 | 1 | 59 |
subtype2 | 0 | 38 |
subtype3 | 0 | 41 |
subtype4 | 0 | 46 |
Cluster Labels | 1 | 2 | 3 |
---|---|---|---|
Number of samples | 70 | 35 | 83 |
P value = 0.194 (logrank test), Q value = 1
nPatients | nDeath | Duration Range (Median), Month | |
---|---|---|---|
ALL | 164 | 102 | 0.9 - 94.1 (12.0) |
subtype1 | 62 | 42 | 1.0 - 69.0 (9.5) |
subtype2 | 30 | 16 | 0.9 - 62.0 (18.0) |
subtype3 | 72 | 44 | 0.9 - 94.1 (13.5) |
P value = 0.457 (Kruskal-Wallis (anova)), Q value = 1
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 188 | 54.9 (16.2) |
subtype1 | 70 | 55.8 (14.8) |
subtype2 | 35 | 57.3 (15.2) |
subtype3 | 83 | 53.1 (17.6) |
P value = 0.388 (Fisher's exact test), Q value = 1
nPatients | FEMALE | MALE |
---|---|---|
ALL | 87 | 101 |
subtype1 | 36 | 34 |
subtype2 | 13 | 22 |
subtype3 | 38 | 45 |
P value = 0.957 (Fisher's exact test), Q value = 1
nPatients | ASIAN | BLACK OR AFRICAN AMERICAN | WHITE |
---|---|---|---|
ALL | 2 | 13 | 171 |
subtype1 | 1 | 6 | 63 |
subtype2 | 0 | 2 | 33 |
subtype3 | 1 | 5 | 75 |
P value = 1 (Fisher's exact test), Q value = 1
nPatients | HISPANIC OR LATINO | NOT HISPANIC OR LATINO |
---|---|---|
ALL | 1 | 184 |
subtype1 | 0 | 70 |
subtype2 | 0 | 35 |
subtype3 | 1 | 79 |
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Cluster data file = LAML-TB.mergedcluster.txt
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Clinical data file = LAML-TB.merged_data.txt
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Number of patients = 200
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Number of clustering approaches = 6
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Number of selected clinical features = 5
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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 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 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.
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.