This pipeline uses various statistical tests to identify genes whose promoter methylation levels correlated to selected clinical features.
Testing the association between 20141 genes and 9 clinical features across 84 samples, statistically thresholded by Q value < 0.05, 3 clinical features related to at least one genes.
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105 genes correlated to 'PATHOLOGY.M.STAGE'.
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DUOX2 , DUOXA2 , CHERP , CHRNA7 , DPF3 , ...
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1057 genes correlated to 'HISTOLOGICAL.TYPE'.
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MAP4K4 , ANO6 , PLEKHA9 , DGCR5 , CIDEA , ...
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10 genes correlated to 'RADIATIONS.RADIATION.REGIMENINDICATION'.
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CTF1 , NKX3-2 , MAP6 , ZNF221 , HOOK3 , ...
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No genes correlated to 'Time to Death', 'AGE', 'PATHOLOGY.T.STAGE', 'PATHOLOGY.N.STAGE', 'NUMBERPACKYEARSSMOKED', and 'NUMBER.OF.LYMPH.NODES'.
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=0 | ||||
PATHOLOGY T STAGE | Spearman correlation test | N=0 | ||||
PATHOLOGY N STAGE | t test | N=0 | ||||
PATHOLOGY M STAGE | ANOVA test | N=105 | ||||
HISTOLOGICAL TYPE | ANOVA test | N=1057 | ||||
RADIATIONS RADIATION REGIMENINDICATION | t test | N=10 | yes | N=7 | no | N=3 |
NUMBERPACKYEARSSMOKED | Spearman correlation test | N=0 | ||||
NUMBER OF LYMPH NODES | Spearman correlation test | N=0 |
Time to Death | Duration (Months) | 0-177 (median=6.9) |
censored | N = 68 | |
death | N = 14 | |
Significant markers | N = 0 |
AGE | Mean (SD) | 48.2 (13) |
Significant markers | N = 0 |
PATHOLOGY.T.STAGE | Mean (SD) | 1.38 (0.65) |
N | ||
1 | 53 | |
2 | 22 | |
3 | 1 | |
4 | 2 | |
Significant markers | N = 0 |
PATHOLOGY.N.STAGE | Labels | N |
class0 | 52 | |
class1 | 24 | |
Significant markers | N = 0 |
PATHOLOGY.M.STAGE | Labels | N |
M0 | 51 | |
M1 | 2 | |
MX | 26 | |
Significant markers | N = 105 |
ANOVA_P | Q | |
---|---|---|
DUOX2 | 1.627e-20 | 3.28e-16 |
DUOXA2 | 1.627e-20 | 3.28e-16 |
CHERP | 5.527e-15 | 1.11e-10 |
CHRNA7 | 2.745e-14 | 5.53e-10 |
DPF3 | 3.064e-13 | 6.17e-09 |
MTUS2 | 4.214e-12 | 8.49e-08 |
PFKM__1 | 1.12e-11 | 2.26e-07 |
SOCS2 | 6.78e-11 | 1.37e-06 |
ATOH8 | 8.247e-11 | 1.66e-06 |
ADAMTS13__1 | 1.045e-10 | 2.1e-06 |
HISTOLOGICAL.TYPE | Labels | N |
CERVICAL SQUAMOUS CELL CARCINOMA | 72 | |
ENDOCERVICAL ADENOCARCINOMA OF THE USUAL TYPE | 1 | |
ENDOCERVICAL TYPE OF ADENOCARCINOMA | 8 | |
ENDOMETRIOID ADENOCARCINOMA OF ENDOCERVIX | 1 | |
MUCINOUS ADENOCARCINOMA OF ENDOCERVICAL TYPE | 2 | |
Significant markers | N = 1057 |
ANOVA_P | Q | |
---|---|---|
MAP4K4 | 2.347e-60 | 4.73e-56 |
ANO6 | 2.889e-55 | 5.82e-51 |
PLEKHA9 | 2.889e-55 | 5.82e-51 |
DGCR5 | 1.668e-53 | 3.36e-49 |
CIDEA | 1.644e-51 | 3.31e-47 |
OSCAR | 6.57e-51 | 1.32e-46 |
C17ORF86__1 | 8.266e-45 | 1.66e-40 |
SCARNA16__1 | 8.266e-45 | 1.66e-40 |
ABTB2 | 1.161e-44 | 2.34e-40 |
PTGIR | 1.132e-42 | 2.28e-38 |
10 genes related to 'RADIATIONS.RADIATION.REGIMENINDICATION'.
RADIATIONS.RADIATION.REGIMENINDICATION | Labels | N |
NO | 17 | |
YES | 67 | |
Significant markers | N = 10 | |
Higher in YES | 7 | |
Higher in NO | 3 |
T(pos if higher in 'YES') | ttestP | Q | AUC | |
---|---|---|---|---|
CTF1 | 6.85 | 1.749e-09 | 3.52e-05 | 0.8068 |
NKX3-2 | 6.46 | 9.059e-09 | 0.000182 | 0.7331 |
MAP6 | 5.42 | 8.299e-07 | 0.0167 | 0.6295 |
ZNF221 | 5.41 | 8.719e-07 | 0.0176 | 0.8078 |
HOOK3 | -5.65 | 1.085e-06 | 0.0218 | 0.849 |
RNF170 | -5.65 | 1.085e-06 | 0.0218 | 0.849 |
CDH16 | -5.19 | 1.656e-06 | 0.0333 | 0.8174 |
TMEM160 | 5.21 | 1.672e-06 | 0.0337 | 0.7612 |
ANKRD5 | 5.08 | 2.338e-06 | 0.0471 | 0.8165 |
GJB2 | 5.08 | 2.406e-06 | 0.0484 | 0.6874 |
NUMBERPACKYEARSSMOKED | Mean (SD) | 18 (13) |
Significant markers | N = 0 |
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Expresson data file = CESC-TP.meth.by_min_clin_corr.data.txt
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Clinical data file = CESC-TP.merged_data.txt
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Number of patients = 84
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Number of genes = 20141
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Number of clinical features = 9
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.
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.