This pipeline uses various statistical tests to identify miRs whose expression levels correlated to selected clinical features.
Testing the association between 484 genes and 3 clinical features across 125 samples, statistically thresholded by Q value < 0.05, 1 clinical feature related to at least one genes.
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3 genes correlated to 'NEOADJUVANT.THERAPY'.
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HSA-MIR-200B , HSA-MIR-200C , HSA-MIR-3605
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No genes correlated to 'AGE', and 'RADIATIONS.RADIATION.REGIMENINDICATION'.
Complete statistical result table is provided in Supplement Table 1
Clinical feature | Statistical test | Significant genes | Associated with | Associated with | ||
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AGE | Spearman correlation test | N=0 | ||||
RADIATIONS RADIATION REGIMENINDICATION | t test | N=0 | ||||
NEOADJUVANT THERAPY | t test | N=3 | yes | N=1 | no | N=2 |
AGE | Mean (SD) | 61.02 (6.6) |
Significant markers | N = 0 |
No gene related to 'RADIATIONS.RADIATION.REGIMENINDICATION'.
RADIATIONS.RADIATION.REGIMENINDICATION | Labels | N |
NO | 5 | |
YES | 120 | |
Significant markers | N = 0 |
NEOADJUVANT.THERAPY | Labels | N |
NO | 3 | |
YES | 122 | |
Significant markers | N = 3 | |
Higher in YES | 1 | |
Higher in NO | 2 |
T(pos if higher in 'YES') | ttestP | Q | AUC | |
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HSA-MIR-200B | -7.24 | 1.144e-08 | 3.85e-06 | 0.8115 |
HSA-MIR-200C | -10.93 | 4.108e-08 | 1.38e-05 | 0.9071 |
HSA-MIR-3605 | 10.66 | 6.553e-05 | 0.0219 | 0.9256 |
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Expresson data file = PRAD.miRseq_RPKM_log2.txt
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Clinical data file = PRAD.clin.merged.picked.txt
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Number of patients = 125
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Number of genes = 484
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Number of clinical features = 3
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 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.