This pipeline uses various statistical tests to identify miRs whose expression levels correlated to selected clinical features.
Testing the association between 470 genes and 5 clinical features across 164 samples, statistically thresholded by Q value < 0.05, 2 clinical features related to at least one genes.
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5 genes correlated to 'PATHOLOGY.T.STAGE'.
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HSA-MIR-30A , HSA-MIR-3676 , HSA-MIR-190 , HSA-MIR-598 , HSA-MIR-486
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1 gene correlated to 'NUMBER.OF.LYMPH.NODES'.
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HSA-MIR-378
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No genes correlated to 'AGE', 'PATHOLOGY.N.STAGE', and '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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AGE | Spearman correlation test | N=0 | ||||
PATHOLOGY T STAGE | Spearman correlation test | N=5 | higher stage | N=0 | lower stage | N=5 |
PATHOLOGY N STAGE | t test | N=0 | ||||
COMPLETENESS OF RESECTION | ANOVA test | N=0 | ||||
NUMBER OF LYMPH NODES | Spearman correlation test | N=1 | higher number.of.lymph.nodes | N=0 | lower number.of.lymph.nodes | N=1 |
AGE | Mean (SD) | 60.17 (6.9) |
Significant markers | N = 0 |
PATHOLOGY.T.STAGE | Mean (SD) | 2.6 (0.54) |
N | ||
2 | 70 | |
3 | 89 | |
4 | 4 | |
Significant markers | N = 5 | |
pos. correlated | 0 | |
neg. correlated | 5 |
SpearmanCorr | corrP | Q | |
---|---|---|---|
HSA-MIR-30A | -0.3348 | 1.251e-05 | 0.00588 |
HSA-MIR-3676 | -0.3217 | 2.983e-05 | 0.014 |
HSA-MIR-190 | -0.3094 | 6.162e-05 | 0.0288 |
HSA-MIR-598 | -0.3042 | 7.901e-05 | 0.0369 |
HSA-MIR-486 | -0.3002 | 9.878e-05 | 0.046 |
PATHOLOGY.N.STAGE | Labels | N |
class0 | 130 | |
class1 | 14 | |
Significant markers | N = 0 |
COMPLETENESS.OF.RESECTION | Labels | N |
R0 | 122 | |
R1 | 30 | |
RX | 3 | |
Significant markers | N = 0 |
NUMBER.OF.LYMPH.NODES | Mean (SD) | 0.19 (0.72) |
Significant markers | N = 1 | |
pos. correlated | 0 | |
neg. correlated | 1 |
SpearmanCorr | corrP | Q | |
---|---|---|---|
HSA-MIR-378 | -0.3274 | 6.19e-05 | 0.0291 |
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Expresson data file = PRAD-TP.miRseq_RPKM_log2.txt
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Clinical data file = PRAD-TP.clin.merged.picked.txt
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Number of patients = 164
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Number of genes = 470
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Number of clinical features = 5
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.