This pipeline uses various statistical tests to identify miRs whose expression levels correlated to selected clinical features.
Testing the association between 540 genes and 9 clinical features across 65 samples, statistically thresholded by Q value < 0.05, 4 clinical features related to at least one genes.
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2 genes correlated to 'AGE'.
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HSA-MIR-424 , HSA-MIR-450A-2
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2 genes correlated to 'PATHOLOGY.M.STAGE'.
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HSA-MIR-202 , HSA-MIR-449A
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10 genes correlated to 'HISTOLOGICAL.TYPE'.
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HSA-MIR-194-2 , HSA-MIR-192 , HSA-MIR-194-1 , HSA-MIR-205 , HSA-MIR-944 , ...
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2 genes correlated to 'RADIATIONS.RADIATION.REGIMENINDICATION'.
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HSA-MIR-532 , HSA-MIR-660
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No genes correlated to 'Time to Death', '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=2 | older | N=0 | younger | N=2 |
PATHOLOGY T STAGE | Spearman correlation test | N=0 | ||||
PATHOLOGY N STAGE | t test | N=0 | ||||
PATHOLOGY M STAGE | ANOVA test | N=2 | ||||
HISTOLOGICAL TYPE | ANOVA test | N=10 | ||||
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 |
Time to Death | Duration (Months) | 0.1-177 (median=11.4) |
censored | N = 50 | |
death | N = 13 | |
Significant markers | N = 0 |
AGE | Mean (SD) | 48.23 (13) |
Significant markers | N = 2 | |
pos. correlated | 0 | |
neg. correlated | 2 |
SpearmanCorr | corrP | Q | |
---|---|---|---|
HSA-MIR-424 | -0.536 | 4.996e-06 | 0.0027 |
HSA-MIR-450A-2 | -0.4927 | 3.531e-05 | 0.019 |
PATHOLOGY.T.STAGE | Mean (SD) | 1.38 (0.61) |
N | ||
1 | 41 | |
2 | 18 | |
3 | 1 | |
4 | 1 | |
Significant markers | N = 0 |
PATHOLOGY.N.STAGE | Labels | N |
class0 | 39 | |
class1 | 21 | |
Significant markers | N = 0 |
PATHOLOGY.M.STAGE | Labels | N |
M0 | 42 | |
M1 | 2 | |
MX | 16 | |
Significant markers | N = 2 |
ANOVA_P | Q | |
---|---|---|
HSA-MIR-202 | 1.912e-06 | 0.00103 |
HSA-MIR-449A | 5.742e-06 | 0.0031 |
HISTOLOGICAL.TYPE | Labels | N |
CERVICAL SQUAMOUS CELL CARCINOMA | 57 | |
ENDOCERVICAL ADENOCARCINOMA OF THE USUAL TYPE | 1 | |
ENDOCERVICAL TYPE OF ADENOCARCINOMA | 6 | |
ENDOMETRIOID ADENOCARCINOMA OF ENDOCERVIX | 1 | |
Significant markers | N = 10 |
ANOVA_P | Q | |
---|---|---|
HSA-MIR-194-2 | 2.041e-16 | 1.09e-13 |
HSA-MIR-192 | 9.095e-16 | 4.87e-13 |
HSA-MIR-194-1 | 1.07e-15 | 5.72e-13 |
HSA-MIR-205 | 1.169e-15 | 6.23e-13 |
HSA-MIR-944 | 2.743e-09 | 1.46e-06 |
HSA-MIR-215 | 3.517e-09 | 1.87e-06 |
HSA-MIR-375 | 2.465e-06 | 0.00131 |
HSA-MIR-3682 | 1.287e-05 | 0.00681 |
HSA-MIR-1287 | 5.926e-05 | 0.0313 |
HSA-MIR-152 | 6.118e-05 | 0.0322 |
2 genes related to 'RADIATIONS.RADIATION.REGIMENINDICATION'.
RADIATIONS.RADIATION.REGIMENINDICATION | Labels | N |
NO | 18 | |
YES | 47 | |
Significant markers | N = 2 | |
Higher in YES | 2 | |
Higher in NO | 0 |
T(pos if higher in 'YES') | ttestP | Q | AUC | |
---|---|---|---|---|
HSA-MIR-532 | 5.02 | 1.246e-05 | 0.0067 | 0.8239 |
HSA-MIR-660 | 4.52 | 8.541e-05 | 0.0459 | 0.8156 |
NUMBERPACKYEARSSMOKED | Mean (SD) | 18.85 (13) |
Significant markers | N = 0 |
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Expresson data file = CESC-TP.miRseq_RPKM_log2.txt
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Clinical data file = CESC-TP.clin.merged.picked.txt
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Number of patients = 65
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Number of genes = 540
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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.