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 7 clinical features across 25 patients, no significant finding detected with P value < 0.05 and Q value < 0.25.
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2 subtypes identified in current cancer cohort by 'Copy Number Ratio CNMF subtypes'. 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 sequencing-based mRNA expression data identified 4 subtypes that do not correlate to any clinical features.
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Consensus hierarchical clustering analysis on sequencing-based mRNA expression data identified 5 subtypes that do not correlate to any clinical features.
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3 subtypes identified in current cancer cohort by 'MIRSEQ CNMF'. These subtypes do not correlate to any clinical features.
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2 subtypes identified in current cancer cohort by 'MIRSEQ CHIERARCHICAL'. These subtypes do not correlate to any clinical features.
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3 subtypes identified in current cancer cohort by 'MIRseq Mature CNMF subtypes'. These subtypes do not correlate to any clinical features.
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4 subtypes identified in current cancer cohort by 'MIRseq Mature cHierClus subtypes'. These subtypes do not correlate to any clinical features.
Clinical Features |
Time to Death |
AGE | GENDER |
DISTANT METASTASIS |
LYMPH NODE METASTASIS |
TUMOR STAGECODE |
NEOPLASM DISEASESTAGE |
Statistical Tests | logrank test | ANOVA | Fisher's exact test | Chi-square test | Chi-square test | ANOVA | Chi-square test |
Copy Number Ratio CNMF subtypes |
100 (1.00) |
0.164 (1.00) |
1 (1.00) |
0.085 (1.00) |
0.487 (1.00) |
||
METHLYATION CNMF |
100 (1.00) |
0.463 (1.00) |
0.846 (1.00) |
0.128 (1.00) |
0.34 (1.00) |
||
RNAseq CNMF subtypes |
100 (1.00) |
0.76 (1.00) |
0.841 (1.00) |
0.177 (1.00) |
0.39 (1.00) |
||
RNAseq cHierClus subtypes |
100 (1.00) |
0.395 (1.00) |
0.653 (1.00) |
0.327 (1.00) |
0.559 (1.00) |
||
MIRSEQ CNMF |
100 (1.00) |
0.127 (1.00) |
0.597 (1.00) |
0.225 (1.00) |
0.16 (1.00) |
||
MIRSEQ CHIERARCHICAL |
100 (1.00) |
0.715 (1.00) |
0.604 (1.00) |
0.286 (1.00) |
0.56 (1.00) |
||
MIRseq Mature CNMF subtypes |
100 (1.00) |
0.785 (1.00) |
0.236 (1.00) |
0.313 (1.00) |
0.127 (1.00) |
||
MIRseq Mature cHierClus subtypes |
100 (1.00) |
0.494 (1.00) |
0.588 (1.00) |
0.492 (1.00) |
0.265 (1.00) |
Cluster Labels | 1 | 2 | 3 |
---|---|---|---|
Number of samples | 1 | 19 | 5 |
P value = 100 (logrank test), Q value = 1
nPatients | nDeath | Duration Range (Median), Month | |
---|---|---|---|
ALL | 23 | 2 | 0.6 - 142.5 (51.0) |
subtype2 | 18 | 2 | 0.6 - 142.5 (51.6) |
subtype3 | 5 | 0 | 2.5 - 89.7 (20.9) |
P value = 0.164 (t-test), Q value = 1
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 24 | 51.8 (14.6) |
subtype2 | 19 | 49.3 (13.8) |
subtype3 | 5 | 61.2 (15.2) |
P value = 1 (Fisher's exact test), Q value = 1
nPatients | FEMALE | MALE |
---|---|---|
ALL | 10 | 14 |
subtype2 | 8 | 11 |
subtype3 | 2 | 3 |
P value = 0.085 (Chi-square test), Q value = 1
nPatients | N0 | N1 | NX |
---|---|---|---|
ALL | 13 | 2 | 9 |
subtype2 | 12 | 2 | 5 |
subtype3 | 1 | 0 | 4 |
P value = 0.487 (Chi-square test), Q value = 1
nPatients | STAGE I | STAGE II | STAGE III | STAGE IV |
---|---|---|---|---|
ALL | 8 | 11 | 2 | 3 |
subtype2 | 7 | 8 | 1 | 3 |
subtype3 | 1 | 3 | 1 | 0 |
Cluster Labels | 1 | 2 | 3 |
---|---|---|---|
Number of samples | 4 | 16 | 5 |
P value = 100 (logrank test), Q value = 1
nPatients | nDeath | Duration Range (Median), Month | |
---|---|---|---|
ALL | 24 | 2 | 0.6 - 142.5 (44.0) |
subtype1 | 4 | 0 | 23.5 - 80.4 (54.8) |
subtype2 | 15 | 2 | 2.5 - 142.5 (52.3) |
subtype3 | 5 | 0 | 0.6 - 75.7 (11.2) |
P value = 0.463 (ANOVA), Q value = 1
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 25 | 52.3 (14.6) |
subtype1 | 4 | 57.5 (11.8) |
subtype2 | 16 | 53.1 (16.1) |
subtype3 | 5 | 45.6 (10.4) |
P value = 0.846 (Fisher's exact test), Q value = 1
nPatients | FEMALE | MALE |
---|---|---|
ALL | 11 | 14 |
subtype1 | 1 | 3 |
subtype2 | 8 | 8 |
subtype3 | 2 | 3 |
P value = 0.128 (Chi-square test), Q value = 1
nPatients | N0 | N1 | NX |
---|---|---|---|
ALL | 13 | 2 | 10 |
subtype1 | 3 | 0 | 1 |
subtype2 | 10 | 1 | 5 |
subtype3 | 0 | 1 | 4 |
P value = 0.34 (Chi-square test), Q value = 1
nPatients | STAGE I | STAGE II | STAGE III | STAGE IV |
---|---|---|---|---|
ALL | 8 | 12 | 2 | 3 |
subtype1 | 1 | 3 | 0 | 0 |
subtype2 | 4 | 9 | 1 | 2 |
subtype3 | 3 | 0 | 1 | 1 |
Cluster Labels | 1 | 2 | 3 | 4 |
---|---|---|---|---|
Number of samples | 3 | 11 | 7 | 4 |
P value = 100 (logrank test), Q value = 1
nPatients | nDeath | Duration Range (Median), Month | |
---|---|---|---|
ALL | 24 | 2 | 0.6 - 142.5 (44.0) |
subtype1 | 3 | 0 | 37.0 - 89.7 (65.2) |
subtype2 | 10 | 0 | 2.5 - 142.5 (24.5) |
subtype3 | 7 | 2 | 20.9 - 114.2 (67.8) |
subtype4 | 4 | 0 | 0.6 - 75.7 (29.6) |
P value = 0.76 (ANOVA), Q value = 1
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 25 | 52.3 (14.6) |
subtype1 | 3 | 55.3 (11.9) |
subtype2 | 11 | 52.2 (17.5) |
subtype3 | 7 | 55.1 (13.1) |
subtype4 | 4 | 45.5 (12.0) |
P value = 0.841 (Fisher's exact test), Q value = 1
nPatients | FEMALE | MALE |
---|---|---|
ALL | 11 | 14 |
subtype1 | 2 | 1 |
subtype2 | 5 | 6 |
subtype3 | 3 | 4 |
subtype4 | 1 | 3 |
P value = 0.177 (Chi-square test), Q value = 1
nPatients | N0 | N1 | NX |
---|---|---|---|
ALL | 13 | 2 | 10 |
subtype1 | 1 | 0 | 2 |
subtype2 | 7 | 0 | 4 |
subtype3 | 5 | 1 | 1 |
subtype4 | 0 | 1 | 3 |
P value = 0.39 (Chi-square test), Q value = 1
nPatients | STAGE I | STAGE II | STAGE III | STAGE IV |
---|---|---|---|---|
ALL | 8 | 12 | 2 | 3 |
subtype1 | 1 | 2 | 0 | 0 |
subtype2 | 4 | 5 | 1 | 1 |
subtype3 | 0 | 5 | 1 | 1 |
subtype4 | 3 | 0 | 0 | 1 |
Cluster Labels | 1 | 2 | 3 | 4 | 5 |
---|---|---|---|---|---|
Number of samples | 5 | 5 | 9 | 3 | 3 |
P value = 100 (logrank test), Q value = 1
nPatients | nDeath | Duration Range (Median), Month | |
---|---|---|---|
ALL | 24 | 2 | 0.6 - 142.5 (44.0) |
subtype1 | 5 | 2 | 28.1 - 114.2 (67.8) |
subtype2 | 5 | 0 | 0.6 - 75.7 (23.5) |
subtype3 | 8 | 0 | 3.5 - 142.5 (25.7) |
subtype4 | 3 | 0 | 2.5 - 87.9 (20.9) |
subtype5 | 3 | 0 | 37.0 - 89.7 (65.2) |
P value = 0.395 (ANOVA), Q value = 1
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 25 | 52.3 (14.6) |
subtype1 | 5 | 55.4 (15.1) |
subtype2 | 5 | 45.0 (10.5) |
subtype3 | 9 | 49.4 (14.9) |
subtype4 | 3 | 65.0 (19.7) |
subtype5 | 3 | 55.3 (11.9) |
P value = 0.653 (Chi-square test), Q value = 1
nPatients | FEMALE | MALE |
---|---|---|
ALL | 11 | 14 |
subtype1 | 2 | 3 |
subtype2 | 1 | 4 |
subtype3 | 4 | 5 |
subtype4 | 2 | 1 |
subtype5 | 2 | 1 |
P value = 0.327 (Chi-square test), Q value = 1
nPatients | N0 | N1 | NX |
---|---|---|---|
ALL | 13 | 2 | 10 |
subtype1 | 4 | 1 | 0 |
subtype2 | 1 | 1 | 3 |
subtype3 | 6 | 0 | 3 |
subtype4 | 1 | 0 | 2 |
subtype5 | 1 | 0 | 2 |
P value = 0.559 (Chi-square test), Q value = 1
nPatients | STAGE I | STAGE II | STAGE III | STAGE IV |
---|---|---|---|---|
ALL | 8 | 12 | 2 | 3 |
subtype1 | 0 | 3 | 1 | 1 |
subtype2 | 3 | 1 | 0 | 1 |
subtype3 | 4 | 3 | 1 | 1 |
subtype4 | 0 | 3 | 0 | 0 |
subtype5 | 1 | 2 | 0 | 0 |
Cluster Labels | 1 | 2 | 3 |
---|---|---|---|
Number of samples | 9 | 8 | 8 |
P value = 100 (logrank test), Q value = 1
nPatients | nDeath | Duration Range (Median), Month | |
---|---|---|---|
ALL | 24 | 2 | 0.6 - 142.5 (44.0) |
subtype1 | 8 | 2 | 0.6 - 142.5 (39.5) |
subtype2 | 8 | 0 | 3.5 - 102.8 (51.1) |
subtype3 | 8 | 0 | 11.2 - 114.2 (46.9) |
P value = 0.127 (ANOVA), Q value = 1
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 25 | 52.3 (14.6) |
subtype1 | 9 | 58.4 (17.9) |
subtype2 | 8 | 53.5 (9.1) |
subtype3 | 8 | 44.2 (12.5) |
P value = 0.597 (Fisher's exact test), Q value = 1
nPatients | FEMALE | MALE |
---|---|---|
ALL | 11 | 14 |
subtype1 | 3 | 6 |
subtype2 | 3 | 5 |
subtype3 | 5 | 3 |
P value = 0.225 (Chi-square test), Q value = 1
nPatients | N0 | N1 | NX |
---|---|---|---|
ALL | 13 | 2 | 10 |
subtype1 | 3 | 2 | 4 |
subtype2 | 4 | 0 | 4 |
subtype3 | 6 | 0 | 2 |
P value = 0.16 (Chi-square test), Q value = 1
nPatients | STAGE I | STAGE II | STAGE III | STAGE IV |
---|---|---|---|---|
ALL | 8 | 12 | 2 | 3 |
subtype1 | 4 | 3 | 0 | 2 |
subtype2 | 1 | 6 | 0 | 1 |
subtype3 | 3 | 3 | 2 | 0 |
Cluster Labels | 1 | 2 |
---|---|---|
Number of samples | 4 | 21 |
P value = 100 (logrank test), Q value = 1
nPatients | nDeath | Duration Range (Median), Month | |
---|---|---|---|
ALL | 24 | 2 | 0.6 - 142.5 (44.0) |
subtype1 | 4 | 1 | 0.6 - 75.7 (30.2) |
subtype2 | 20 | 1 | 2.5 - 142.5 (44.0) |
P value = 0.715 (t-test), Q value = 1
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 25 | 52.3 (14.6) |
subtype1 | 4 | 49.2 (17.5) |
subtype2 | 21 | 52.9 (14.4) |
P value = 0.604 (Fisher's exact test), Q value = 1
nPatients | FEMALE | MALE |
---|---|---|
ALL | 11 | 14 |
subtype1 | 1 | 3 |
subtype2 | 10 | 11 |
P value = 0.286 (Chi-square test), Q value = 1
nPatients | N0 | N1 | NX |
---|---|---|---|
ALL | 13 | 2 | 10 |
subtype1 | 1 | 1 | 2 |
subtype2 | 12 | 1 | 8 |
P value = 0.56 (Chi-square test), Q value = 1
nPatients | STAGE I | STAGE II | STAGE III | STAGE IV |
---|---|---|---|---|
ALL | 8 | 12 | 2 | 3 |
subtype1 | 2 | 1 | 0 | 1 |
subtype2 | 6 | 11 | 2 | 2 |
Cluster Labels | 1 | 2 | 3 |
---|---|---|---|
Number of samples | 10 | 7 | 8 |
P value = 100 (logrank test), Q value = 1
nPatients | nDeath | Duration Range (Median), Month | |
---|---|---|---|
ALL | 24 | 2 | 0.6 - 142.5 (44.0) |
subtype1 | 10 | 0 | 2.5 - 102.8 (25.7) |
subtype2 | 7 | 0 | 11.2 - 114.2 (67.8) |
subtype3 | 7 | 2 | 0.6 - 142.5 (51.0) |
P value = 0.785 (ANOVA), Q value = 1
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 25 | 52.3 (14.6) |
subtype1 | 10 | 52.1 (15.7) |
subtype2 | 7 | 49.6 (13.3) |
subtype3 | 8 | 55.0 (15.6) |
P value = 0.236 (Fisher's exact test), Q value = 1
nPatients | FEMALE | MALE |
---|---|---|
ALL | 11 | 14 |
subtype1 | 4 | 6 |
subtype2 | 5 | 2 |
subtype3 | 2 | 6 |
P value = 0.313 (Chi-square test), Q value = 1
nPatients | N0 | N1 | NX |
---|---|---|---|
ALL | 13 | 2 | 10 |
subtype1 | 6 | 0 | 4 |
subtype2 | 4 | 0 | 3 |
subtype3 | 3 | 2 | 3 |
P value = 0.127 (Chi-square test), Q value = 1
nPatients | STAGE I | STAGE II | STAGE III | STAGE IV |
---|---|---|---|---|
ALL | 8 | 12 | 2 | 3 |
subtype1 | 3 | 6 | 0 | 1 |
subtype2 | 1 | 4 | 2 | 0 |
subtype3 | 4 | 2 | 0 | 2 |
Cluster Labels | 1 | 2 | 3 | 4 | 5 | 6 |
---|---|---|---|---|---|---|
Number of samples | 2 | 6 | 2 | 4 | 7 | 4 |
P value = 100 (logrank test), Q value = 1
nPatients | nDeath | Duration Range (Median), Month | |
---|---|---|---|
ALL | 21 | 2 | 0.6 - 142.5 (51.0) |
subtype2 | 6 | 1 | 23.4 - 142.5 (74.1) |
subtype4 | 4 | 1 | 0.6 - 75.7 (30.2) |
subtype5 | 7 | 0 | 2.5 - 102.8 (25.9) |
subtype6 | 4 | 0 | 23.5 - 72.7 (38.2) |
P value = 0.494 (ANOVA), Q value = 1
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 21 | 51.4 (14.6) |
subtype2 | 6 | 49.2 (15.0) |
subtype4 | 4 | 49.2 (17.5) |
subtype5 | 7 | 58.3 (14.1) |
subtype6 | 4 | 45.0 (12.6) |
P value = 0.588 (Fisher's exact test), Q value = 1
nPatients | FEMALE | MALE |
---|---|---|
ALL | 8 | 13 |
subtype2 | 4 | 2 |
subtype4 | 1 | 3 |
subtype5 | 2 | 5 |
subtype6 | 1 | 3 |
P value = 0.492 (Chi-square test), Q value = 1
nPatients | N0 | N1 | NX |
---|---|---|---|
ALL | 11 | 2 | 8 |
subtype2 | 4 | 1 | 1 |
subtype4 | 1 | 1 | 2 |
subtype5 | 3 | 0 | 4 |
subtype6 | 3 | 0 | 1 |
P value = 0.265 (Chi-square test), Q value = 1
nPatients | STAGE I | STAGE II | STAGE III | STAGE IV |
---|---|---|---|---|
ALL | 6 | 11 | 1 | 3 |
subtype2 | 0 | 4 | 1 | 1 |
subtype4 | 2 | 1 | 0 | 1 |
subtype5 | 1 | 5 | 0 | 1 |
subtype6 | 3 | 1 | 0 | 0 |
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Cluster data file = KICH-TP.mergedcluster.txt
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Clinical data file = KICH-TP.clin.merged.picked.txt
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Number of patients = 25
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Number of clustering approaches = 8
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Number of selected clinical features = 7
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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, 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.