(Regional_LN cohort)
This pipeline uses various statistical tests to identify RPPAs whose expression levels correlated to selected clinical features.
Testing the association between 175 genes and 6 clinical features across 80 samples, statistically thresholded by Q value < 0.05, no clinical feature related to at least one genes.
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No genes correlated to 'Time to Death', 'AGE', 'GENDER', 'DISTANT.METASTASIS', 'LYMPH.NODE.METASTASIS', and 'NEOPLASM.DISEASESTAGE'.
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 genes that are significantly associated with each clinical feature at Q value < 0.05.
| Clinical feature | Statistical test | Significant genes | Associated with | Associated with | ||
|---|---|---|---|---|---|---|
| Time to Death | Cox regression test | N=0 | ||||
| AGE | Spearman correlation test | N=0 | ||||
| GENDER | t test | N=0 | ||||
| DISTANT METASTASIS | ANOVA test | N=0 | ||||
| LYMPH NODE METASTASIS | ANOVA test | N=0 | ||||
| NEOPLASM DISEASESTAGE | ANOVA test | N=0 |
Table S1. Basic characteristics of clinical feature: 'Time to Death'
| Time to Death | Duration (Months) | 1.1-98.8 (median=13.5) |
| censored | N = 18 | |
| death | N = 22 | |
| Significant markers | N = 0 |
Table S2. Basic characteristics of clinical feature: 'AGE'
| AGE | Mean (SD) | 56.52 (16) |
| Significant markers | N = 0 |
Table S3. Basic characteristics of clinical feature: 'GENDER'
| GENDER | Labels | N |
| FEMALE | 29 | |
| MALE | 51 | |
| Significant markers | N = 0 |
Table S4. Basic characteristics of clinical feature: 'DISTANT.METASTASIS'
| DISTANT.METASTASIS | Labels | N |
| M0 | 66 | |
| M1 | 1 | |
| M1B | 2 | |
| M1C | 1 | |
| Significant markers | N = 0 |
Table S5. Basic characteristics of clinical feature: 'LYMPH.NODE.METASTASIS'
| LYMPH.NODE.METASTASIS | Labels | N |
| N0 | 45 | |
| N1 | 1 | |
| N1A | 1 | |
| N1B | 7 | |
| N2A | 2 | |
| N2B | 4 | |
| N2C | 1 | |
| N3 | 8 | |
| NX | 2 | |
| Significant markers | N = 0 |
Table S6. Basic characteristics of clinical feature: 'NEOPLASM.DISEASESTAGE'
| NEOPLASM.DISEASESTAGE | Labels | N |
| I OR II NOS | 1 | |
| STAGE I | 11 | |
| STAGE IA | 6 | |
| STAGE IB | 6 | |
| STAGE II | 8 | |
| STAGE IIA | 5 | |
| STAGE IIB | 4 | |
| STAGE IIC | 2 | |
| STAGE III | 2 | |
| STAGE IIIA | 1 | |
| STAGE IIIB | 6 | |
| STAGE IIIC | 10 | |
| STAGE IV | 3 | |
| Significant markers | N = 0 |
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Expresson data file = SKCM-Regional_LN.rppa.txt
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Clinical data file = SKCM-Regional_LN.clin.merged.picked.txt
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Number of patients = 80
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Number of genes = 175
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Number of clinical features = 6
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 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 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 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.