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 3 clinical features across 138 patients, no significant finding detected with P value < 0.05.
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3 subtypes identified in current cancer cohort by 'CN CNMF'. These subtypes do not correlate to any clinical features.
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3 subtypes identified in current cancer cohort by 'METHLYATION CNMF'. These subtypes do not correlate to any clinical features.
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CNMF clustering analysis on RPPA data identified 3 subtypes that do not correlate to any clinical features.
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Consensus hierarchical clustering analysis on RPPA data identified 3 subtypes that do not correlate to any clinical features.
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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 3 subtypes that do not correlate to any clinical features.
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CNMF clustering analysis on sequencing-based miR expression data identified 3 subtypes that do not correlate to any clinical features.
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Consensus hierarchical clustering analysis on sequencing-based miR expression data identified 3 subtypes that do not correlate to any clinical features.
Clinical Features |
Time to Death |
AGE | GENDER |
Statistical Tests | logrank test | ANOVA | Fisher's exact test |
CN CNMF | 0.716 | 0.198 | 0.0743 |
METHLYATION CNMF | 0.247 | 0.287 | 0.386 |
RPPA CNMF subtypes | 0.143 | 0.365 | 0.93 |
RPPA cHierClus subtypes | 0.165 | 0.585 | 0.313 |
RNAseq CNMF subtypes | 0.222 | 0.457 | 0.649 |
RNAseq cHierClus subtypes | 0.101 | 0.614 | 0.621 |
MIRseq CNMF subtypes | 0.167 | 0.526 | 0.945 |
MIRseq cHierClus subtypes | 0.261 | 0.843 | 0.925 |
Cluster Labels | 1 | 2 | 3 |
---|---|---|---|
Number of samples | 41 | 52 | 45 |
P value = 0.716 (logrank test)
nPatients | nDeath | Duration Range (Median), Month | |
---|---|---|---|
ALL | 18 | 11 | 0.2 - 131.1 (41.8) |
subtype1 | 3 | 3 | 32.5 - 131.1 (64.4) |
subtype2 | 8 | 4 | 0.2 - 117.9 (41.8) |
subtype3 | 7 | 4 | 5.6 - 120.5 (27.0) |
P value = 0.198 (ANOVA)
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 19 | 56.8 (16.0) |
subtype1 | 3 | 45.3 (15.4) |
subtype2 | 9 | 63.2 (13.5) |
subtype3 | 7 | 53.4 (17.5) |
P value = 0.0743 (Fisher's exact test)
nPatients | FEMALE | MALE |
---|---|---|
ALL | 46 | 92 |
subtype1 | 13 | 28 |
subtype2 | 23 | 29 |
subtype3 | 10 | 35 |
Cluster Labels | 1 | 2 | 3 |
---|---|---|---|
Number of samples | 29 | 57 | 50 |
P value = 0.247 (logrank test)
nPatients | nDeath | Duration Range (Median), Month | |
---|---|---|---|
ALL | 17 | 11 | 5.6 - 131.1 (44.0) |
subtype1 | 5 | 3 | 12.6 - 131.1 (64.4) |
subtype2 | 4 | 3 | 26.4 - 120.5 (90.3) |
subtype3 | 8 | 5 | 5.6 - 84.7 (29.7) |
P value = 0.287 (ANOVA)
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 18 | 56.7 (16.5) |
subtype1 | 5 | 51.0 (16.3) |
subtype2 | 4 | 68.0 (17.6) |
subtype3 | 9 | 54.8 (15.5) |
P value = 0.386 (Fisher's exact test)
nPatients | FEMALE | MALE |
---|---|---|
ALL | 45 | 91 |
subtype1 | 10 | 19 |
subtype2 | 22 | 35 |
subtype3 | 13 | 37 |
Cluster Labels | 1 | 2 | 3 |
---|---|---|---|
Number of samples | 40 | 34 | 25 |
P value = 0.143 (logrank test)
nPatients | nDeath | Duration Range (Median), Month | |
---|---|---|---|
ALL | 16 | 11 | 5.6 - 131.1 (41.8) |
subtype1 | 8 | 5 | 10.1 - 131.1 (41.8) |
subtype2 | 2 | 1 | 62.8 - 80.0 (71.4) |
subtype3 | 6 | 5 | 5.6 - 84.7 (23.9) |
P value = 0.365 (ANOVA)
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 17 | 56.2 (16.9) |
subtype1 | 8 | 58.1 (17.2) |
subtype2 | 3 | 65.7 (15.0) |
subtype3 | 6 | 49.0 (16.8) |
P value = 0.93 (Fisher's exact test)
nPatients | FEMALE | MALE |
---|---|---|
ALL | 35 | 64 |
subtype1 | 15 | 25 |
subtype2 | 11 | 23 |
subtype3 | 9 | 16 |
Cluster Labels | 1 | 2 | 3 |
---|---|---|---|
Number of samples | 36 | 40 | 23 |
P value = 0.165 (logrank test)
nPatients | nDeath | Duration Range (Median), Month | |
---|---|---|---|
ALL | 16 | 11 | 5.6 - 131.1 (41.8) |
subtype1 | 3 | 1 | 62.8 - 120.5 (80.0) |
subtype2 | 8 | 6 | 10.1 - 131.1 (33.3) |
subtype3 | 5 | 4 | 5.6 - 84.7 (32.5) |
P value = 0.585 (ANOVA)
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 17 | 56.2 (16.9) |
subtype1 | 3 | 62.7 (18.4) |
subtype2 | 8 | 58.0 (17.3) |
subtype3 | 6 | 50.7 (16.9) |
P value = 0.313 (Fisher's exact test)
nPatients | FEMALE | MALE |
---|---|---|
ALL | 35 | 64 |
subtype1 | 14 | 22 |
subtype2 | 16 | 24 |
subtype3 | 5 | 18 |
Cluster Labels | 1 | 2 | 3 |
---|---|---|---|
Number of samples | 43 | 40 | 42 |
P value = 0.222 (logrank test)
nPatients | nDeath | Duration Range (Median), Month | |
---|---|---|---|
ALL | 15 | 10 | 10.1 - 131.1 (44.0) |
subtype1 | 6 | 5 | 15.3 - 117.9 (51.2) |
subtype2 | 5 | 4 | 10.1 - 131.1 (32.5) |
subtype3 | 4 | 1 | 27.0 - 84.7 (62.0) |
P value = 0.457 (ANOVA)
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 16 | 55.4 (17.0) |
subtype1 | 6 | 59.8 (24.2) |
subtype2 | 5 | 47.2 (10.1) |
subtype3 | 5 | 58.2 (11.3) |
P value = 0.649 (Fisher's exact test)
nPatients | FEMALE | MALE |
---|---|---|
ALL | 43 | 82 |
subtype1 | 13 | 30 |
subtype2 | 16 | 24 |
subtype3 | 14 | 28 |
Cluster Labels | 1 | 2 | 3 |
---|---|---|---|
Number of samples | 54 | 33 | 38 |
P value = 0.101 (logrank test)
nPatients | nDeath | Duration Range (Median), Month | |
---|---|---|---|
ALL | 15 | 10 | 10.1 - 131.1 (44.0) |
subtype1 | 4 | 1 | 44.0 - 84.7 (72.2) |
subtype2 | 4 | 4 | 15.3 - 117.9 (44.6) |
subtype3 | 7 | 5 | 10.1 - 131.1 (32.5) |
P value = 0.614 (ANOVA)
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 16 | 55.4 (17.0) |
subtype1 | 5 | 50.4 (8.1) |
subtype2 | 4 | 62.2 (27.6) |
subtype3 | 7 | 55.0 (15.7) |
P value = 0.621 (Fisher's exact test)
nPatients | FEMALE | MALE |
---|---|---|
ALL | 43 | 82 |
subtype1 | 20 | 34 |
subtype2 | 9 | 24 |
subtype3 | 14 | 24 |
Cluster Labels | 1 | 2 | 3 |
---|---|---|---|
Number of samples | 57 | 45 | 31 |
P value = 0.167 (logrank test)
nPatients | nDeath | Duration Range (Median), Month | |
---|---|---|---|
ALL | 16 | 10 | 0.2 - 131.1 (53.4) |
subtype1 | 3 | 3 | 62.8 - 117.9 (64.4) |
subtype2 | 8 | 6 | 10.1 - 131.1 (29.7) |
subtype3 | 5 | 1 | 0.2 - 120.5 (80.0) |
P value = 0.526 (ANOVA)
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 16 | 55.1 (16.6) |
subtype1 | 3 | 60.3 (22.5) |
subtype2 | 8 | 50.1 (17.1) |
subtype3 | 5 | 59.8 (13.3) |
P value = 0.945 (Fisher's exact test)
nPatients | FEMALE | MALE |
---|---|---|
ALL | 44 | 89 |
subtype1 | 19 | 38 |
subtype2 | 14 | 31 |
subtype3 | 11 | 20 |
Cluster Labels | 1 | 2 | 3 |
---|---|---|---|
Number of samples | 16 | 87 | 30 |
P value = 0.261 (logrank test)
nPatients | nDeath | Duration Range (Median), Month | |
---|---|---|---|
ALL | 16 | 10 | 0.2 - 131.1 (53.4) |
subtype1 | 2 | 0 | 0.2 - 84.7 (42.5) |
subtype2 | 8 | 6 | 15.3 - 131.1 (72.4) |
subtype3 | 6 | 4 | 10.1 - 80.0 (29.7) |
P value = 0.843 (ANOVA)
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 16 | 55.1 (16.6) |
subtype1 | 2 | 56.0 (4.2) |
subtype2 | 8 | 54.1 (21.8) |
subtype3 | 6 | 56.0 (12.6) |
P value = 0.925 (Fisher's exact test)
nPatients | FEMALE | MALE |
---|---|---|
ALL | 44 | 89 |
subtype1 | 6 | 10 |
subtype2 | 28 | 59 |
subtype3 | 10 | 20 |
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Cluster data file = SKCM.mergedcluster.txt
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Clinical data file = SKCM.clin.merged.picked.txt
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Number of patients = 138
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Number of clustering approaches = 8
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Number of selected clinical features = 3
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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 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 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
This is an experimental feature. The full results of the analysis summarized in this report can be downloaded from the TCGA Data Coordination Center.