This pipeline uses various statistical tests to identify genes whose promoter methylation levels correlated to selected clinical features.
Testing the association between 20386 genes and 7 clinical features across 380 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 4 clinical features related to at least one genes.
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513 genes correlated to 'AGE'.
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ANGPT4 , ALS2CL , GPR158 , ITPK1 , NCRNA00203 , ...
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3991 genes correlated to 'HISTOLOGICAL.TYPE'.
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APBB1IP , SSTR1 , RASGRF1 , ADAMTS16 , ITPK1 , ...
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66 genes correlated to 'RADIATIONS.RADIATION.REGIMENINDICATION'.
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RMND5B , FIZ1 , ZNF524 , ZNF831 , MAP2K2 , ...
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30 genes correlated to 'RACE'.
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C18ORF54 , LOC253039 , PSMD5 , ZNF525 , NCRNA00174 , ...
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No genes correlated to 'Time to Death', 'COMPLETENESS.OF.RESECTION', and 'ETHNICITY'.
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=513 | older | N=167 | younger | N=346 |
HISTOLOGICAL TYPE | Kruskal-Wallis test | N=3991 | ||||
RADIATIONS RADIATION REGIMENINDICATION | Wilcoxon test | N=66 | yes | N=66 | no | N=0 |
COMPLETENESS OF RESECTION | Kruskal-Wallis test | N=0 | ||||
RACE | Kruskal-Wallis test | N=30 | ||||
ETHNICITY | Wilcoxon test | N=0 |
Time to Death | Duration (Months) | 0-191.8 (median=18) |
censored | N = 333 | |
death | N = 45 | |
Significant markers | N = 0 |
AGE | Mean (SD) | 63.85 (11) |
Significant markers | N = 513 | |
pos. correlated | 167 | |
neg. correlated | 346 |
SpearmanCorr | corrP | Q | |
---|---|---|---|
ANGPT4 | 0.352 | 1.712e-12 | 3.49e-08 |
ALS2CL | -0.3468 | 3.785e-12 | 7.72e-08 |
GPR158 | -0.3449 | 4.99e-12 | 1.02e-07 |
ITPK1 | -0.3291 | 5.021e-11 | 1.02e-06 |
NCRNA00203 | -0.3291 | 5.021e-11 | 1.02e-06 |
HDAC11 | -0.3281 | 5.787e-11 | 1.18e-06 |
SLFN14 | 0.328 | 5.862e-11 | 1.19e-06 |
ADAMTS15 | -0.3273 | 6.492e-11 | 1.32e-06 |
PLA2G15 | -0.3226 | 1.257e-10 | 2.56e-06 |
EPB41L1 | -0.3196 | 1.908e-10 | 3.89e-06 |
HISTOLOGICAL.TYPE | Labels | N |
ENDOMETRIOID ENDOMETRIAL ADENOCARCINOMA | 278 | |
MIXED SEROUS AND ENDOMETRIOID | 19 | |
SEROUS ENDOMETRIAL ADENOCARCINOMA | 83 | |
Significant markers | N = 3991 |
66 genes related to 'RADIATIONS.RADIATION.REGIMENINDICATION'.
RADIATIONS.RADIATION.REGIMENINDICATION | Labels | N |
NO | 87 | |
YES | 293 | |
Significant markers | N = 66 | |
Higher in YES | 66 | |
Higher in NO | 0 |
W(pos if higher in 'YES') | wilcoxontestP | Q | AUC | |
---|---|---|---|---|
RMND5B | 17999 | 5.25e-09 | 0.000107 | 0.7061 |
FIZ1 | 17946 | 7.464e-09 | 0.000152 | 0.704 |
ZNF524 | 17946 | 7.464e-09 | 0.000152 | 0.704 |
ZNF831 | 17853 | 1.373e-08 | 0.00028 | 0.7004 |
MAP2K2 | 17695 | 3.774e-08 | 0.000769 | 0.6942 |
C14ORF93 | 17678 | 4.2e-08 | 0.000856 | 0.6935 |
GIPR | 17649 | 5.037e-08 | 0.00103 | 0.6924 |
SAP130 | 17624 | 5.887e-08 | 0.0012 | 0.6914 |
GOLGA3 | 17606 | 6.583e-08 | 0.00134 | 0.6907 |
TMEM125 | 17574 | 8.022e-08 | 0.00163 | 0.6894 |
COMPLETENESS.OF.RESECTION | Labels | N |
R0 | 253 | |
R1 | 18 | |
R2 | 13 | |
RX | 28 | |
Significant markers | N = 0 |
RACE | Labels | N |
AMERICAN INDIAN OR ALASKA NATIVE | 2 | |
ASIAN | 7 | |
BLACK OR AFRICAN AMERICAN | 68 | |
NATIVE HAWAIIAN OR OTHER PACIFIC ISLANDER | 7 | |
WHITE | 275 | |
Significant markers | N = 30 |
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Expresson data file = UCEC-TP.meth.by_min_clin_corr.data.txt
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Clinical data file = UCEC-TP.merged_data.txt
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Number of patients = 380
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Number of genes = 20386
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Number of clinical features = 7
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.