This pipeline uses various statistical tests to identify miRs whose expression levels correlated to selected clinical features.
Testing the association between 556 genes and 5 clinical features across 453 samples, statistically thresholded by Q value < 0.05, 4 clinical features related to at least one genes.
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4 genes correlated to 'Time to Death'.
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HSA-LET-7G , HSA-MIR-576 , HSA-MIR-628 , HSA-MIR-30E
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52 genes correlated to 'AGE'.
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HSA-MIR-424 , HSA-MIR-1247 , HSA-MIR-337 , HSA-MIR-214 , HSA-MIR-199A-1 , ...
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92 genes correlated to 'HISTOLOGICAL.TYPE'.
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HSA-MIR-9-3 , HSA-MIR-9-2 , HSA-MIR-9-1 , HSA-MIR-934 , HSA-MIR-34A , ...
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7 genes correlated to 'RADIATIONS.RADIATION.REGIMENINDICATION'.
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HSA-MIR-3613 , HSA-MIR-128-1 , HSA-MIR-628 , HSA-MIR-128-2 , HSA-MIR-107 , ...
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No genes correlated to 'COMPLETENESS.OF.RESECTION'
Complete statistical result table is provided in Supplement Table 1
Clinical feature | Statistical test | Significant genes | Associated with | Associated with | ||
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Time to Death | Cox regression test | N=4 | shorter survival | N=0 | longer survival | N=4 |
AGE | Spearman correlation test | N=52 | older | N=5 | younger | N=47 |
HISTOLOGICAL TYPE | ANOVA test | N=92 | ||||
RADIATIONS RADIATION REGIMENINDICATION | t test | N=7 | yes | N=5 | no | N=2 |
COMPLETENESS OF RESECTION | ANOVA test | N=0 |
Time to Death | Duration (Months) | 0-187.1 (median=15.3) |
censored | N = 408 | |
death | N = 41 | |
Significant markers | N = 4 | |
associated with shorter survival | 0 | |
associated with longer survival | 4 |
HazardRatio | Wald_P | Q | C_index | |
---|---|---|---|---|
HSA-LET-7G | 0.46 | 1.176e-05 | 0.0065 | 0.298 |
HSA-MIR-576 | 0.53 | 1.264e-05 | 0.007 | 0.317 |
HSA-MIR-628 | 0.64 | 2.025e-05 | 0.011 | 0.296 |
HSA-MIR-30E | 0.34 | 4.345e-05 | 0.024 | 0.314 |
AGE | Mean (SD) | 63.53 (11) |
Significant markers | N = 52 | |
pos. correlated | 5 | |
neg. correlated | 47 |
SpearmanCorr | corrP | Q | |
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HSA-MIR-424 | -0.3183 | 4.202e-12 | 2.34e-09 |
HSA-MIR-1247 | -0.2805 | 1.523e-09 | 8.45e-07 |
HSA-MIR-337 | -0.2665 | 8.642e-09 | 4.79e-06 |
HSA-MIR-214 | -0.2618 | 1.676e-08 | 9.27e-06 |
HSA-MIR-199A-1 | -0.2608 | 1.837e-08 | 1.01e-05 |
HSA-MIR-199A-2 | -0.254 | 4.351e-08 | 2.4e-05 |
HSA-MIR-409 | -0.2525 | 5.25e-08 | 2.89e-05 |
HSA-MIR-34A | -0.2523 | 5.389e-08 | 2.96e-05 |
HSA-MIR-134 | -0.2491 | 8.018e-08 | 4.39e-05 |
HSA-MIR-199B | -0.2475 | 9.736e-08 | 5.33e-05 |
HISTOLOGICAL.TYPE | Labels | N |
ENDOMETRIOID ENDOMETRIAL ADENOCARCINOMA | 354 | |
MIXED SEROUS AND ENDOMETRIOID | 18 | |
SEROUS ENDOMETRIAL ADENOCARCINOMA | 81 | |
Significant markers | N = 92 |
ANOVA_P | Q | |
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HSA-MIR-9-3 | 7.413e-32 | 4.12e-29 |
HSA-MIR-9-2 | 2.39e-28 | 1.33e-25 |
HSA-MIR-9-1 | 2.754e-28 | 1.53e-25 |
HSA-MIR-934 | 1.226e-23 | 6.78e-21 |
HSA-MIR-34A | 2.866e-23 | 1.58e-20 |
HSA-MIR-375 | 5.156e-20 | 2.84e-17 |
HSA-MIR-195 | 2.24e-18 | 1.23e-15 |
HSA-MIR-190B | 3.621e-18 | 1.99e-15 |
HSA-MIR-497 | 1.715e-17 | 9.4e-15 |
HSA-MIR-548V | 1.186e-16 | 6.49e-14 |
7 genes related to 'RADIATIONS.RADIATION.REGIMENINDICATION'.
RADIATIONS.RADIATION.REGIMENINDICATION | Labels | N |
NO | 130 | |
YES | 323 | |
Significant markers | N = 7 | |
Higher in YES | 5 | |
Higher in NO | 2 |
T(pos if higher in 'YES') | ttestP | Q | AUC | |
---|---|---|---|---|
HSA-MIR-3613 | -5.31 | 2.194e-07 | 0.000122 | 0.6571 |
HSA-MIR-128-1 | 4.7 | 3.906e-06 | 0.00217 | 0.6376 |
HSA-MIR-628 | -4.64 | 5.384e-06 | 0.00298 | 0.6252 |
HSA-MIR-128-2 | 4.57 | 7.231e-06 | 0.004 | 0.6312 |
HSA-MIR-107 | 4.17 | 4.079e-05 | 0.0225 | 0.61 |
HSA-MIR-361 | 4.16 | 4.363e-05 | 0.024 | 0.6125 |
HSA-MIR-181D | 4.08 | 5.882e-05 | 0.0323 | 0.6199 |
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Expresson data file = UCEC-TP.miRseq_RPKM_log2.txt
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Clinical data file = UCEC-TP.clin.merged.picked.txt
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Number of patients = 453
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Number of genes = 556
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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.
This is an experimental feature. The full results of the analysis summarized in this report can be downloaded from the TCGA Data Coordination Center.