This pipeline uses various statistical tests to identify genes whose promoter methylation levels correlated to selected clinical features.
Testing the association between 20239 genes and 3 clinical features across 192 samples, statistically thresholded by Q value < 0.05, 2 clinical features related to at least one genes.
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35 genes correlated to 'AGE'.
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ETV1 , KIAA1377 , ANGPTL5 , AASS , TMEM20 , ...
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7 genes correlated to 'GENDER'.
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AP2B1 , KIF4B , DKFZP434L187 , MYO5A , DACH1 , ...
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No genes correlated to 'Time to Death'
Complete statistical result table is provided in Supplement Table 1
Clinical feature | Statistical test | Significant genes | Associated with | Associated with | ||
---|---|---|---|---|---|---|
Time to Death | Cox regression test | N=0 | ||||
AGE | Spearman correlation test | N=35 | older | N=3 | younger | N=32 |
GENDER | t test | N=7 | male | N=3 | female | N=4 |
Time to Death | Duration (Months) | 0.9-94.1 (median=12) |
censored | N = 63 | |
death | N = 103 | |
Significant markers | N = 0 |
AGE | Mean (SD) | 55.13 (16) |
Significant markers | N = 35 | |
pos. correlated | 3 | |
neg. correlated | 32 |
SpearmanCorr | corrP | Q | |
---|---|---|---|
ETV1 | -0.4366 | 2.447e-10 | 4.95e-06 |
KIAA1377 | -0.4313 | 4.213e-10 | 8.53e-06 |
ANGPTL5 | -0.4298 | 4.946e-10 | 1e-05 |
AASS | -0.4264 | 6.957e-10 | 1.41e-05 |
TMEM20 | -0.4239 | 8.951e-10 | 1.81e-05 |
MYEF2 | -0.3908 | 2.089e-08 | 0.000423 |
HCG4 | -0.3887 | 2.528e-08 | 0.000511 |
HOOK1 | -0.3841 | 3.794e-08 | 0.000768 |
TBC1D12 | -0.3797 | 5.58e-08 | 0.00113 |
ENPP5 | -0.3673 | 1.598e-07 | 0.00323 |
GENDER | Labels | N |
FEMALE | 89 | |
MALE | 103 | |
Significant markers | N = 7 | |
Higher in MALE | 3 | |
Higher in FEMALE | 4 |
T(pos if higher in 'MALE') | ttestP | Q | AUC | |
---|---|---|---|---|
AP2B1 | -11.96 | 9.237e-24 | 1.87e-19 | 0.9023 |
KIF4B | -10.61 | 5.859e-21 | 1.19e-16 | 0.8587 |
DKFZP434L187 | 9.15 | 1.114e-16 | 2.25e-12 | 0.86 |
MYO5A | -6.88 | 1.117e-10 | 2.26e-06 | 0.8276 |
DACH1 | 5.78 | 3.086e-08 | 0.000624 | 0.734 |
RNASEH2C | 5.66 | 7.663e-08 | 0.00155 | 0.8014 |
LOC100240735 | -5.17 | 5.978e-07 | 0.0121 | 0.7071 |
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Expresson data file = LAML.meth.for_correlation.filtered_data.txt
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Clinical data file = LAML.clin.merged.picked.txt
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Number of patients = 192
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Number of genes = 20239
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Number of clinical features = 3
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.