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 5 clinical features across 366 samples, statistically thresholded by Q value < 0.05, 4 clinical features related to at least one genes.
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226 genes correlated to 'AGE'.
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ANGPT4 , GPR158 , ALS2CL , ADAMTS15 , PLA2G15 , ...
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2989 genes correlated to 'HISTOLOGICAL.TYPE'.
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APBB1IP , ITPK1 , NCRNA00203 , SSTR1 , CARD11 , ...
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17 genes correlated to 'RADIATIONS.RADIATION.REGIMENINDICATION'.
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MAP2K2 , FIZ1 , ZNF524 , C17ORF28 , C14ORF93 , ...
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20 genes correlated to 'COMPLETENESS.OF.RESECTION'.
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TNFRSF19 , MYRIP , POLR1A__1 , EWSR1 , RHBDD3 , ...
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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=226 | older | N=65 | younger | N=161 |
HISTOLOGICAL TYPE | ANOVA test | N=2989 | ||||
RADIATIONS RADIATION REGIMENINDICATION | t test | N=17 | yes | N=16 | no | N=1 |
COMPLETENESS OF RESECTION | ANOVA test | N=20 |
Time to Death | Duration (Months) | 0-191.8 (median=17.6) |
censored | N = 320 | |
death | N = 44 | |
Significant markers | N = 0 |
AGE | Mean (SD) | 63.92 (11) |
Significant markers | N = 226 | |
pos. correlated | 65 | |
neg. correlated | 161 |
SpearmanCorr | corrP | Q | |
---|---|---|---|
ANGPT4 | 0.3472 | 8.919e-12 | 1.82e-07 |
GPR158 | -0.3402 | 2.416e-11 | 4.93e-07 |
ALS2CL | -0.3401 | 2.472e-11 | 5.04e-07 |
ADAMTS15 | -0.3316 | 8.102e-11 | 1.65e-06 |
PLA2G15 | -0.3297 | 1.056e-10 | 2.15e-06 |
HDAC11 | -0.3272 | 1.488e-10 | 3.03e-06 |
ITPK1 | -0.3248 | 2.062e-10 | 4.2e-06 |
NCRNA00203 | -0.3248 | 2.062e-10 | 4.2e-06 |
C2ORF34 | -0.317 | 5.757e-10 | 1.17e-05 |
SLFN14 | 0.3153 | 7.259e-10 | 1.48e-05 |
HISTOLOGICAL.TYPE | Labels | N |
ENDOMETRIOID ENDOMETRIAL ADENOCARCINOMA | 270 | |
MIXED SEROUS AND ENDOMETRIOID | 18 | |
SEROUS ENDOMETRIAL ADENOCARCINOMA | 78 | |
Significant markers | N = 2989 |
ANOVA_P | Q | |
---|---|---|
APBB1IP | 5.398e-49 | 1.1e-44 |
ITPK1 | 2.271e-46 | 4.63e-42 |
NCRNA00203 | 2.271e-46 | 4.63e-42 |
SSTR1 | 2.212e-44 | 4.51e-40 |
CARD11 | 3.882e-44 | 7.91e-40 |
PPIH | 1.404e-43 | 2.86e-39 |
CRYAB__1 | 3.47e-41 | 7.07e-37 |
HSPB2__1 | 3.47e-41 | 7.07e-37 |
ADAMTS16 | 5.629e-41 | 1.15e-36 |
CRYAB | 2.375e-40 | 4.84e-36 |
17 genes related to 'RADIATIONS.RADIATION.REGIMENINDICATION'.
RADIATIONS.RADIATION.REGIMENINDICATION | Labels | N |
NO | 84 | |
YES | 282 | |
Significant markers | N = 17 | |
Higher in YES | 16 | |
Higher in NO | 1 |
T(pos if higher in 'YES') | ttestP | Q | AUC | |
---|---|---|---|---|
MAP2K2 | 5.94 | 2.027e-08 | 0.000413 | 0.7024 |
FIZ1 | 5.82 | 3.991e-08 | 0.000814 | 0.6999 |
ZNF524 | 5.82 | 3.991e-08 | 0.000814 | 0.6999 |
C17ORF28 | 5.44 | 1.94e-07 | 0.00395 | 0.6865 |
C14ORF93 | 5.38 | 2.651e-07 | 0.0054 | 0.6969 |
GIPR | 5.32 | 4.627e-07 | 0.00943 | 0.6875 |
PEF1 | 5.14 | 6.067e-07 | 0.0124 | 0.659 |
RGPD4 | 5.26 | 6.269e-07 | 0.0128 | 0.6749 |
MST1 | 5.05 | 1.007e-06 | 0.0205 | 0.6513 |
RNF123__1 | 5.05 | 1.007e-06 | 0.0205 | 0.6513 |
COMPLETENESS.OF.RESECTION | Labels | N |
R0 | 243 | |
R1 | 18 | |
R2 | 12 | |
RX | 26 | |
Significant markers | N = 20 |
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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 = 366
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Number of genes = 20386
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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 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.