This pipeline uses various statistical tests to identify genes whose promoter methylation levels correlated to selected clinical features.
Testing the association between 12215 genes and 5 clinical features across 296 samples, statistically thresholded by Q value < 0.05, 2 clinical features related to at least one genes.
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1 gene correlated to 'Time to Death'.
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NOL3
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12 genes correlated to 'AGE'.
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SDR16C5 , KCNIP1 , PDZK1 , ATP2B2 , ITGBL1 , ...
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No genes correlated to 'KARNOFSKY.PERFORMANCE.SCORE', 'TUMOR.STAGE', and 'NEOADJUVANT.THERAPY'.
Complete statistical result table is provided in Supplement Table 1
Clinical feature | Statistical test | Significant genes | Associated with | Associated with | ||
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Time to Death | Cox regression test | N=1 | shorter survival | N=0 | longer survival | N=1 |
AGE | Spearman correlation test | N=12 | older | N=1 | younger | N=11 |
KARNOFSKY PERFORMANCE SCORE | Spearman correlation test | N=0 | ||||
TUMOR STAGE | Spearman correlation test | N=0 | ||||
NEOADJUVANT THERAPY | t test | N=0 |
Time to Death | Duration (Months) | 0.3-180.2 (median=28.3) |
censored | N = 125 | |
death | N = 169 | |
Significant markers | N = 1 | |
associated with shorter survival | 0 | |
associated with longer survival | 1 |
HazardRatio | Wald_P | Q | C_index | |
---|---|---|---|---|
NOL3 | 0.02 | 3.794e-06 | 0.046 | 0.412 |
AGE | Mean (SD) | 59.17 (11) |
Significant markers | N = 12 | |
pos. correlated | 1 | |
neg. correlated | 11 |
SpearmanCorr | corrP | Q | |
---|---|---|---|
SDR16C5 | -0.323 | 2.035e-08 | 0.000249 |
KCNIP1 | -0.3053 | 1.259e-07 | 0.00154 |
PDZK1 | -0.2867 | 7.455e-07 | 0.00911 |
ATP2B2 | -0.2838 | 9.742e-07 | 0.0119 |
ITGBL1 | -0.2833 | 1.021e-06 | 0.0125 |
NRM | -0.2821 | 1.137e-06 | 0.0139 |
GRM2 | -0.2816 | 1.194e-06 | 0.0146 |
IL12RB2 | -0.2783 | 1.603e-06 | 0.0196 |
PCDHGB7 | 0.2773 | 1.753e-06 | 0.0214 |
PDE4A | -0.2726 | 2.655e-06 | 0.0324 |
No gene related to 'KARNOFSKY.PERFORMANCE.SCORE'.
KARNOFSKY.PERFORMANCE.SCORE | Mean (SD) | 76 (14) |
Score | N | |
60 | 5 | |
80 | 8 | |
100 | 2 | |
Significant markers | N = 0 |
TUMOR.STAGE | Mean (SD) | 3.06 (0.42) |
N | ||
Stage 2 | 18 | |
Stage 3 | 240 | |
Stage 4 | 36 | |
Significant markers | N = 0 |
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Expresson data file = OV.meth.for_correlation.filtered_data.txt
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Clinical data file = OV.clin.merged.picked.txt
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Number of patients = 296
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Number of genes = 12215
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Number of clinical features = 5
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 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.