This pipeline uses various statistical tests to identify selected clinical features related to mutation rate.
Testing the association between 2 variables and 11 clinical features across 154 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 4 clinical features related to at least one variables.
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2 variables correlated to 'AGE'.
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MUTATIONRATE_NONSYNONYMOUS , MUTATIONRATE_SILENT
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1 variable correlated to 'NEOPLASM.DISEASESTAGE'.
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MUTATIONRATE_NONSYNONYMOUS
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2 variables correlated to 'GENDER'.
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MUTATIONRATE_NONSYNONYMOUS , MUTATIONRATE_SILENT
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2 variables correlated to 'HISTOLOGICAL.TYPE'.
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MUTATIONRATE_SILENT , MUTATIONRATE_NONSYNONYMOUS
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No variables correlated to 'Time to Death', 'AGE_mutation.rate', 'PATHOLOGY.T.STAGE', 'PATHOLOGY.N.STAGE', 'PATHOLOGY.M.STAGE', 'COMPLETENESS.OF.RESECTION', and 'NUMBER.OF.LYMPH.NODES'.
Complete statistical result table is provided in Supplement Table 1
Table 1. Get Full Table This table shows the clinical features, statistical methods used, and the number of variables that are significantly associated with each clinical feature at P value < 0.05 and Q value < 0.3.
| Clinical feature | Statistical test | Significant variables | Associated with | Associated with | ||
|---|---|---|---|---|---|---|
| Time to Death | Cox regression test | N=0 | ||||
| AGE | Spearman correlation test | N=2 | older | N=2 | younger | N=0 |
| AGE | Linear Regression Analysis | N=0 | ||||
| NEOPLASM DISEASESTAGE | Kruskal-Wallis test | N=1 | ||||
| PATHOLOGY T STAGE | Spearman correlation test | N=0 | ||||
| PATHOLOGY N STAGE | Spearman correlation test | N=0 | ||||
| PATHOLOGY M STAGE | Kruskal-Wallis test | N=0 | ||||
| GENDER | Wilcoxon test | N=2 | male | N=2 | female | N=0 |
| HISTOLOGICAL TYPE | Wilcoxon test | N=2 | colon mucinous adenocarcinoma | N=2 | colon adenocarcinoma | N=0 |
| COMPLETENESS OF RESECTION | Kruskal-Wallis test | N=0 | ||||
| NUMBER OF LYMPH NODES | Spearman correlation test | N=0 |
Table S1. Basic characteristics of clinical feature: 'Time to Death'
| Time to Death | Duration (Months) | 0.9-54 (median=23.4) |
| censored | N = 115 | |
| death | N = 26 | |
| Significant variables | N = 0 |
Table S2. Basic characteristics of clinical feature: 'AGE'
| AGE | Mean (SD) | 70.48 (12) |
| Significant variables | N = 2 | |
| pos. correlated | 2 | |
| neg. correlated | 0 |
Table S3. Get Full Table List of 2 variables significantly correlated to 'AGE' by Spearman correlation test
| SpearmanCorr | corrP | Q | |
|---|---|---|---|
| MUTATIONRATE_NONSYNONYMOUS | 0.2197 | 0.006195 | 0.0124 |
| MUTATIONRATE_SILENT | 0.1636 | 0.04264 | 0.0426 |
Table S4. Basic characteristics of clinical feature: 'AGE'
| AGE | Mean (SD) | 70.48 (12) |
| Significant variables | N = 0 |
Table S5. Basic characteristics of clinical feature: 'NEOPLASM.DISEASESTAGE'
| NEOPLASM.DISEASESTAGE | Labels | N |
| STAGE I | 31 | |
| STAGE II | 14 | |
| STAGE IIA | 38 | |
| STAGE IIB | 4 | |
| STAGE III | 14 | |
| STAGE IIIA | 2 | |
| STAGE IIIB | 12 | |
| STAGE IIIC | 16 | |
| STAGE IV | 21 | |
| STAGE IVA | 1 | |
| Significant variables | N = 1 |
Table S6. Get Full Table List of one variable differentially expressed by 'NEOPLASM.DISEASESTAGE'
| ANOVA_P | Q | |
|---|---|---|
| MUTATIONRATE_NONSYNONYMOUS | 0.03493 | 0.0699 |
Table S7. Basic characteristics of clinical feature: 'PATHOLOGY.T.STAGE'
| PATHOLOGY.T.STAGE | Mean (SD) | 2.83 (0.62) |
| N | ||
| 1 | 4 | |
| 2 | 33 | |
| 3 | 102 | |
| 4 | 15 | |
| Significant variables | N = 0 |
Table S8. Basic characteristics of clinical feature: 'PATHOLOGY.N.STAGE'
| PATHOLOGY.N.STAGE | Mean (SD) | 0.64 (0.82) |
| N | ||
| 0 | 90 | |
| 1 | 30 | |
| 2 | 34 | |
| Significant variables | N = 0 |
Table S9. Basic characteristics of clinical feature: 'PATHOLOGY.M.STAGE'
| PATHOLOGY.M.STAGE | Labels | N |
| M0 | 130 | |
| M1 | 21 | |
| M1A | 1 | |
| Significant variables | N = 0 |
Table S10. Basic characteristics of clinical feature: 'GENDER'
| GENDER | Labels | N |
| FEMALE | 77 | |
| MALE | 77 | |
| Significant variables | N = 2 | |
| Higher in MALE | 2 | |
| Higher in FEMALE | 0 |
Table S11. Get Full Table List of 2 variables differentially expressed by 'GENDER'. 0 significant gene(s) located in sex chromosomes is(are) filtered out.
| W(pos if higher in 'MALE') | wilcoxontestP | Q | AUC | |
|---|---|---|---|---|
| MUTATIONRATE_NONSYNONYMOUS | 2338 | 0.02369 | 0.0474 | 0.6057 |
| MUTATIONRATE_SILENT | 2417.5 | 0.04826 | 0.0483 | 0.5923 |
Table S12. Basic characteristics of clinical feature: 'HISTOLOGICAL.TYPE'
| HISTOLOGICAL.TYPE | Labels | N |
| COLON ADENOCARCINOMA | 130 | |
| COLON MUCINOUS ADENOCARCINOMA | 22 | |
| Significant variables | N = 2 | |
| Higher in COLON MUCINOUS ADENOCARCINOMA | 2 | |
| Higher in COLON ADENOCARCINOMA | 0 |
Table S13. Get Full Table List of 2 variables differentially expressed by 'HISTOLOGICAL.TYPE'
| W(pos if higher in 'COLON MUCINOUS ADENOCARCINOMA') | wilcoxontestP | Q | AUC | |
|---|---|---|---|---|
| MUTATIONRATE_SILENT | 2105.5 | 0.0004073 | 0.000815 | 0.7362 |
| MUTATIONRATE_NONSYNONYMOUS | 2095 | 0.0005015 | 0.000815 | 0.7325 |
No variable related to 'COMPLETENESS.OF.RESECTION'.
Table S14. Basic characteristics of clinical feature: 'COMPLETENESS.OF.RESECTION'
| COMPLETENESS.OF.RESECTION | Labels | N |
| R0 | 128 | |
| R1 | 1 | |
| R2 | 19 | |
| RX | 1 | |
| Significant variables | N = 0 |
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Expresson data file = COAD-TP.patients.counts_and_rates.txt
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Clinical data file = COAD-TP.merged_data.txt
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Number of patients = 154
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Number of variables = 2
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Number of clinical features = 11
For survival clinical features, Wald's test in univariate Cox regression analysis with proportional hazards model (Andersen and Gill 1982) was used to estimate the P values using the 'coxph' function in R. Kaplan-Meier survival curves were plot using the four quartile subgroups of patients based on expression levels
For continuous numerical clinical features, Spearman's rank correlation coefficients (Spearman 1904) and two-tailed P values were estimated using 'cor.test' function in R
For multi-class clinical features (ordinal or nominal), one-way analysis of variance (Howell 2002) was applied to compare the log2-expression levels between different clinical classes using 'anova' function in R
For two-class clinical features, two-tailed Student's t test with unequal variance (Lehmann and Romano 2005) was applied to compare the log2-expression levels between the two clinical classes using 't.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.