This pipeline uses various statistical tests to identify selected clinical features related to mutation rate.
Testing the association between 2 variables and 15 clinical features across 268 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 3 clinical features related to at least one variables.
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1 variable correlated to 'MELANOMA.ULCERATION'.
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MUTATIONRATE_SILENT
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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 'RACE'.
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MUTATIONRATE_NONSYNONYMOUS , MUTATIONRATE_SILENT
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No variables correlated to 'Time from Specimen Diagnosis to Death', 'Time to Death', 'AGE', 'AGE_mutation.rate', 'PRIMARY.SITE.OF.DISEASE', 'NEOPLASM.DISEASESTAGE', 'PATHOLOGY.T.STAGE', 'PATHOLOGY.N.STAGE', 'PATHOLOGY.M.STAGE', 'MELANOMA.PRIMARY.KNOWN', 'BRESLOW.THICKNESS', and 'ETHNICITY'.
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 | ||
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Time from Specimen Diagnosis to Death | Cox regression test | N=0 | ||||
Time to Death | Cox regression test | N=0 | ||||
AGE | Spearman correlation test | N=0 | ||||
AGE | Linear Regression Analysis | N=0 | ||||
PRIMARY SITE OF DISEASE | Kruskal-Wallis test | N=0 | ||||
NEOPLASM DISEASESTAGE | Kruskal-Wallis test | N=0 | ||||
PATHOLOGY T STAGE | Spearman correlation test | N=0 | ||||
PATHOLOGY N STAGE | Spearman correlation test | N=0 | ||||
PATHOLOGY M STAGE | Kruskal-Wallis test | N=0 | ||||
MELANOMA ULCERATION | Wilcoxon test | N=1 | yes | N=1 | no | N=0 |
MELANOMA PRIMARY KNOWN | Wilcoxon test | N=0 | ||||
BRESLOW THICKNESS | Spearman correlation test | N=0 | ||||
GENDER | Wilcoxon test | N=2 | male | N=2 | female | N=0 |
RACE | Kruskal-Wallis test | N=2 | ||||
ETHNICITY | Wilcoxon test | N=0 |
No variable related to 'Time from Specimen Diagnosis to Death'.
Table S1. Basic characteristics of clinical feature: 'Time from Specimen Diagnosis to Death'
Time from Specimen Diagnosis to Death | Duration (Months) | 0-124.3 (median=14.8) |
censored | N = 128 | |
death | N = 130 | |
Significant variables | N = 0 |
Table S2. Basic characteristics of clinical feature: 'Time to Death'
Time to Death | Duration (Months) | 0.2-357.4 (median=48.6) |
censored | N = 132 | |
death | N = 131 | |
Significant variables | N = 0 |
Table S3. Basic characteristics of clinical feature: 'AGE'
AGE | Mean (SD) | 55.72 (16) |
Significant variables | N = 0 |
Table S4. Basic characteristics of clinical feature: 'AGE'
AGE | Mean (SD) | 55.72 (16) |
Significant variables | N = 0 |
Table S5. Basic characteristics of clinical feature: 'PRIMARY.SITE.OF.DISEASE'
PRIMARY.SITE.OF.DISEASE | Labels | N |
DISTANT METASTASIS | 35 | |
PRIMARY TUMOR | 4 | |
REGIONAL CUTANEOUS OR SUBCUTANEOUS TISSUE | 58 | |
REGIONAL LYMPH NODE | 170 | |
Significant variables | N = 0 |
Table S6. Basic characteristics of clinical feature: 'NEOPLASM.DISEASESTAGE'
NEOPLASM.DISEASESTAGE | Labels | N |
I OR II NOS | 10 | |
STAGE 0 | 6 | |
STAGE I | 22 | |
STAGE IA | 10 | |
STAGE IB | 24 | |
STAGE II | 17 | |
STAGE IIA | 10 | |
STAGE IIB | 14 | |
STAGE IIC | 9 | |
STAGE III | 31 | |
STAGE IIIA | 13 | |
STAGE IIIB | 22 | |
STAGE IIIC | 44 | |
STAGE IV | 12 | |
Significant variables | N = 0 |
Table S7. Basic characteristics of clinical feature: 'PATHOLOGY.T.STAGE'
PATHOLOGY.T.STAGE | Mean (SD) | 2.42 (1.3) |
N | ||
0 | 21 | |
1 | 30 | |
2 | 58 | |
3 | 53 | |
4 | 55 | |
Significant variables | N = 0 |
Table S8. Basic characteristics of clinical feature: 'PATHOLOGY.N.STAGE'
PATHOLOGY.N.STAGE | Mean (SD) | 0.84 (1.1) |
N | ||
0 | 138 | |
1 | 48 | |
2 | 32 | |
3 | 33 | |
Significant variables | N = 0 |
Table S9. Basic characteristics of clinical feature: 'PATHOLOGY.M.STAGE'
PATHOLOGY.M.STAGE | Labels | N |
M0 | 240 | |
M1 | 4 | |
M1A | 2 | |
M1B | 2 | |
M1C | 5 | |
Significant variables | N = 0 |
Table S10. Basic characteristics of clinical feature: 'MELANOMA.ULCERATION'
MELANOMA.ULCERATION | Labels | N |
NO | 102 | |
YES | 67 | |
Significant variables | N = 1 | |
Higher in YES | 1 | |
Higher in NO | 0 |
Table S11. Get Full Table List of one variable differentially expressed by 'MELANOMA.ULCERATION'
W(pos if higher in 'YES') | wilcoxontestP | Q | AUC | |
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MUTATIONRATE_SILENT | 2784 | 0.04208 | 0.0842 | 0.5926 |
Table S12. Basic characteristics of clinical feature: 'MELANOMA.PRIMARY.KNOWN'
MELANOMA.PRIMARY.KNOWN | Labels | N |
NO | 33 | |
YES | 235 | |
Significant variables | N = 0 |
Table S13. Basic characteristics of clinical feature: 'BRESLOW.THICKNESS'
BRESLOW.THICKNESS | Mean (SD) | 3.56 (5) |
Significant variables | N = 0 |
Table S14. Basic characteristics of clinical feature: 'GENDER'
GENDER | Labels | N |
FEMALE | 103 | |
MALE | 165 | |
Significant variables | N = 2 | |
Higher in MALE | 2 | |
Higher in FEMALE | 0 |
Table S15. 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 | |
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MUTATIONRATE_NONSYNONYMOUS | 10114 | 0.008841 | 0.0177 | 0.5951 |
MUTATIONRATE_SILENT | 10110 | 0.00901 | 0.0177 | 0.5949 |
Table S16. Basic characteristics of clinical feature: 'RACE'
RACE | Labels | N |
ASIAN | 3 | |
BLACK OR AFRICAN AMERICAN | 1 | |
WHITE | 264 | |
Significant variables | N = 2 |
Table S17. Get Full Table List of 2 variables differentially expressed by 'RACE'
ANOVA_P | Q | |
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MUTATIONRATE_NONSYNONYMOUS | 0.0318 | 0.055 |
MUTATIONRATE_SILENT | 0.02749 | 0.055 |
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Expresson data file = SKCM-TM.patients.counts_and_rates.txt
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Clinical data file = SKCM-TM.merged_data.txt
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Number of patients = 268
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Number of variables = 2
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Number of clinical features = 15
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.