This pipeline uses various statistical tests to identify miRs whose expression levels correlated to selected clinical features.
Testing the association between 539 miRs and 9 clinical features across 78 samples, statistically thresholded by Q value < 0.05, 4 clinical features related to at least one miRs.
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1 miR correlated to 'AGE'.
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HSA-MIR-424
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6 miRs correlated to 'PATHOLOGY.M.STAGE'.
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HSA-MIR-202 , HSA-MIR-514-1 , HSA-MIR-514-3 , HSA-MIR-514-2 , HSA-MIR-509-3 , ...
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11 miRs correlated to 'HISTOLOGICAL.TYPE'.
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HSA-MIR-205 , HSA-MIR-944 , HSA-MIR-194-2 , HSA-MIR-192 , HSA-MIR-194-1 , ...
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4 miRs correlated to 'RADIATIONS.RADIATION.REGIMENINDICATION'.
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HSA-MIR-338 , HSA-MIR-660 , HSA-MIR-532 , HSA-MIR-362
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No miRs 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 miRs | Associated with | Associated with | ||
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Time to Death | Cox regression test | N=0 | ||||
AGE | Spearman correlation test | N=1 | older | N=0 | younger | N=1 |
PATHOLOGY T STAGE | Spearman correlation test | N=0 | ||||
PATHOLOGY N STAGE | t test | N=0 | ||||
PATHOLOGY M STAGE | ANOVA test | N=6 | ||||
HISTOLOGICAL TYPE | ANOVA test | N=11 | ||||
RADIATIONS RADIATION REGIMENINDICATION | t test | N=4 | yes | N=4 | 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=10.1) |
censored | N = 62 | |
death | N = 14 | |
Significant markers | N = 0 |
AGE | Mean (SD) | 48.09 (13) |
Significant markers | N = 1 | |
pos. correlated | 0 | |
neg. correlated | 1 |
SpearmanCorr | corrP | Q | |
---|---|---|---|
HSA-MIR-424 | -0.4656 | 1.984e-05 | 0.0107 |
PATHOLOGY.T.STAGE | Mean (SD) | 1.41 (0.66) |
N | ||
1 | 49 | |
2 | 22 | |
3 | 1 | |
4 | 2 | |
Significant markers | N = 0 |
PATHOLOGY.N.STAGE | Labels | N |
class0 | 49 | |
class1 | 24 | |
Significant markers | N = 0 |
PATHOLOGY.M.STAGE | Labels | N |
M0 | 48 | |
M1 | 2 | |
MX | 23 | |
Significant markers | N = 6 |
ANOVA_P | Q | |
---|---|---|
HSA-MIR-202 | 5.325e-07 | 0.000287 |
HSA-MIR-514-1 | 2.612e-05 | 0.0141 |
HSA-MIR-514-3 | 5.878e-05 | 0.0316 |
HSA-MIR-514-2 | 6.079e-05 | 0.0326 |
HSA-MIR-509-3 | 6.346e-05 | 0.034 |
HSA-MIR-452 | 8.615e-05 | 0.046 |
HISTOLOGICAL.TYPE | Labels | N |
CERVICAL SQUAMOUS CELL CARCINOMA | 67 | |
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 = 11 |
ANOVA_P | Q | |
---|---|---|
HSA-MIR-205 | 2.464e-19 | 1.32e-16 |
HSA-MIR-944 | 3.302e-15 | 1.77e-12 |
HSA-MIR-194-2 | 9.301e-15 | 4.98e-12 |
HSA-MIR-192 | 1.71e-14 | 9.13e-12 |
HSA-MIR-194-1 | 2.291e-13 | 1.22e-10 |
HSA-MIR-375 | 3.566e-07 | 0.00019 |
HSA-MIR-10A | 2.367e-06 | 0.00126 |
HSA-MIR-215 | 5.668e-06 | 0.003 |
HSA-MIR-449A | 2.611e-05 | 0.0138 |
HSA-MIR-155 | 2.892e-05 | 0.0153 |
4 miRs related to 'RADIATIONS.RADIATION.REGIMENINDICATION'.
RADIATIONS.RADIATION.REGIMENINDICATION | Labels | N |
NO | 17 | |
YES | 61 | |
Significant markers | N = 4 | |
Higher in YES | 4 | |
Higher in NO | 0 |
T(pos if higher in 'YES') | ttestP | Q | AUC | |
---|---|---|---|---|
HSA-MIR-338 | 5.09 | 1.263e-05 | 0.00678 | 0.8245 |
HSA-MIR-660 | 5.21 | 2.116e-05 | 0.0113 | 0.8467 |
HSA-MIR-532 | 4.79 | 4.653e-05 | 0.0249 | 0.811 |
HSA-MIR-362 | 4.47 | 9.061e-05 | 0.0484 | 0.8014 |
NUMBERPACKYEARSSMOKED | Mean (SD) | 19.24 (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.merged_data.txt
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Number of patients = 78
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Number of miRs = 539
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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.