This pipeline uses various statistical tests to identify mRNAs whose expression levels correlated to selected clinical features.
Testing the association between 18202 genes and 9 clinical features across 76 samples, statistically thresholded by Q value < 0.05, 3 clinical features related to at least one genes.
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13 genes correlated to 'PATHOLOGY.M.STAGE'.
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HOXA4|3201 , ARF1|375 , HOXA10|3206 , TRMT12|55039 , PRNP|5621 , ...
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440 genes correlated to 'HISTOLOGICAL.TYPE'.
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TP63|8626 , PKP1|5317 , HNF1A|6927 , LOC642587|642587 , SLC3A1|6519 , ...
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2 genes correlated to 'RADIATIONS.RADIATION.REGIMENINDICATION'.
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ARMC3|219681 , APOBEC4|403314
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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
Table 1. Get Full Table This table shows the clinical features, statistical methods used, and the number of genes that are significantly associated with each clinical feature at Q value < 0.05.
Clinical feature | Statistical test | Significant genes | Associated with | Associated with | ||
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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=13 | ||||
HISTOLOGICAL TYPE | ANOVA test | N=440 | ||||
RADIATIONS RADIATION REGIMENINDICATION | t test | N=2 | yes | N=2 | no | N=0 |
NUMBERPACKYEARSSMOKED | Spearman correlation test | N=0 | ||||
NUMBER OF LYMPH NODES | Spearman correlation test | N=0 |
Table S1. Basic characteristics of clinical feature: 'Time to Death'
Time to Death | Duration (Months) | 0.1-177 (median=9.7) |
censored | N = 62 | |
death | N = 12 | |
Significant markers | N = 0 |
Table S2. Basic characteristics of clinical feature: 'AGE'
AGE | Mean (SD) | 47.35 (13) |
Significant markers | N = 0 |
Table S3. Basic characteristics of clinical feature: 'PATHOLOGY.T.STAGE'
PATHOLOGY.T.STAGE | Mean (SD) | 1.38 (0.59) |
N | ||
1 | 48 | |
2 | 22 | |
3 | 1 | |
4 | 1 | |
Significant markers | N = 0 |
Table S4. Basic characteristics of clinical feature: 'PATHOLOGY.N.STAGE'
PATHOLOGY.N.STAGE | Labels | N |
class0 | 48 | |
class1 | 23 | |
Significant markers | N = 0 |
Table S5. Basic characteristics of clinical feature: 'PATHOLOGY.M.STAGE'
PATHOLOGY.M.STAGE | Labels | N |
M0 | 46 | |
M1 | 2 | |
MX | 23 | |
Significant markers | N = 13 |
Table S6. Get Full Table List of top 10 genes differentially expressed by 'PATHOLOGY.M.STAGE'
ANOVA_P | Q | |
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HOXA4|3201 | 1.888e-10 | 3.44e-06 |
ARF1|375 | 3.241e-10 | 5.9e-06 |
HOXA10|3206 | 8.771e-09 | 0.00016 |
TRMT12|55039 | 1.401e-08 | 0.000255 |
PRNP|5621 | 1.087e-07 | 0.00198 |
FAM135A|57579 | 1.329e-07 | 0.00242 |
CD40|958 | 4.148e-07 | 0.00755 |
SYVN1|84447 | 9.003e-07 | 0.0164 |
FERMT1|55612 | 1.206e-06 | 0.0219 |
AMOTL1|154810 | 1.671e-06 | 0.0304 |
Figure S1. Get High-res Image As an example, this figure shows the association of HOXA4|3201 to 'PATHOLOGY.M.STAGE'. P value = 1.89e-10 with ANOVA analysis.

Table S7. Basic characteristics of clinical feature: 'HISTOLOGICAL.TYPE'
HISTOLOGICAL.TYPE | Labels | N |
CERVICAL SQUAMOUS CELL CARCINOMA | 65 | |
ENDOCERVICAL ADENOCARCINOMA OF THE USUAL TYPE | 1 | |
ENDOCERVICAL TYPE OF ADENOCARCINOMA | 8 | |
ENDOMETRIOID ADENOCARCINOMA OF ENDOCERVIX | 1 | |
MUCINOUS ADENOCARCINOMA OF ENDOCERVICAL TYPE | 1 | |
Significant markers | N = 440 |
Table S8. Get Full Table List of top 10 genes differentially expressed by 'HISTOLOGICAL.TYPE'
ANOVA_P | Q | |
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TP63|8626 | 6.719e-21 | 1.22e-16 |
PKP1|5317 | 1.509e-18 | 2.74e-14 |
HNF1A|6927 | 7.931e-18 | 1.44e-13 |
LOC642587|642587 | 6.054e-17 | 1.1e-12 |
SLC3A1|6519 | 1.264e-15 | 2.3e-11 |
KRT6A|3853 | 1.452e-15 | 2.64e-11 |
CALML3|810 | 3.883e-15 | 7.06e-11 |
GPR87|53836 | 4.791e-15 | 8.71e-11 |
SLC30A2|7780 | 5.469e-15 | 9.94e-11 |
DNALI1|7802 | 2.013e-14 | 3.66e-10 |
Figure S2. Get High-res Image As an example, this figure shows the association of TP63|8626 to 'HISTOLOGICAL.TYPE'. P value = 6.72e-21 with ANOVA analysis.

2 genes related to 'RADIATIONS.RADIATION.REGIMENINDICATION'.
Table S9. Basic characteristics of clinical feature: 'RADIATIONS.RADIATION.REGIMENINDICATION'
RADIATIONS.RADIATION.REGIMENINDICATION | Labels | N |
NO | 16 | |
YES | 60 | |
Significant markers | N = 2 | |
Higher in YES | 2 | |
Higher in NO | 0 |
Table S10. Get Full Table List of 2 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'
T(pos if higher in 'YES') | ttestP | Q | AUC | |
---|---|---|---|---|
ARMC3|219681 | 6.22 | 2.301e-07 | 0.00418 | 0.8706 |
APOBEC4|403314 | 5.96 | 1.593e-06 | 0.029 | 0.9655 |
Figure S3. Get High-res Image As an example, this figure shows the association of ARMC3|219681 to 'RADIATIONS.RADIATION.REGIMENINDICATION'. P value = 2.3e-07 with T-test analysis.

Table S11. Basic characteristics of clinical feature: 'NUMBERPACKYEARSSMOKED'
NUMBERPACKYEARSSMOKED | Mean (SD) | 19.24 (13) |
Significant markers | N = 0 |
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Expresson data file = CESC-TP.uncv2.mRNAseq_RSEM_normalized_log2.txt
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Clinical data file = CESC-TP.merged_data.txt
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Number of patients = 76
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Number of genes = 18202
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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.