This pipeline uses various statistical tests to identify miRs whose expression levels correlated to selected clinical features.
Testing the association between 457 miRs and 9 clinical features across 486 samples, statistically thresholded by Q value < 0.05, 6 clinical features related to at least one miRs.
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62 miRs correlated to 'Time to Death'.
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HSA-MIR-223 , HSA-MIR-130B , HSA-MIR-34C , HSA-MIR-21 , HSA-MIR-365-2 , ...
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1 miR correlated to 'AGE'.
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HSA-MIR-590
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37 miRs correlated to 'NEOPLASM.DISEASESTAGE'.
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HSA-MIR-139 , HSA-MIR-625 , HSA-MIR-21 , HSA-MIR-486 , HSA-MIR-28 , ...
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33 miRs correlated to 'PATHOLOGY.T.STAGE'.
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HSA-MIR-139 , HSA-MIR-486 , HSA-MIR-21 , HSA-MIR-625 , HSA-MIR-155 , ...
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22 miRs correlated to 'PATHOLOGY.M.STAGE'.
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HSA-MIR-26A-1 , HSA-MIR-144 , HSA-MIR-625 , HSA-MIR-1277 , HSA-MIR-1269 , ...
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9 miRs correlated to 'GENDER'.
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HSA-MIR-100 , HSA-MIR-708 , HSA-MIR-599 , HSA-MIR-455 , HSA-MIR-30A , ...
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No miRs correlated to 'PATHOLOGY.N.STAGE', 'KARNOFSKY.PERFORMANCE.SCORE', and 'NUMBERPACKYEARSSMOKED'.
Complete statistical result table is provided in Supplement Table 1
Clinical feature | Statistical test | Significant miRs | Associated with | Associated with | ||
---|---|---|---|---|---|---|
Time to Death | Cox regression test | N=62 | shorter survival | N=54 | longer survival | N=8 |
AGE | Spearman correlation test | N=1 | older | N=1 | younger | N=0 |
NEOPLASM DISEASESTAGE | ANOVA test | N=37 | ||||
PATHOLOGY T STAGE | Spearman correlation test | N=33 | higher stage | N=23 | lower stage | N=10 |
PATHOLOGY N STAGE | t test | N=0 | ||||
PATHOLOGY M STAGE | ANOVA test | N=22 | ||||
GENDER | t test | N=9 | male | N=3 | female | N=6 |
KARNOFSKY PERFORMANCE SCORE | Spearman correlation test | N=0 | ||||
NUMBERPACKYEARSSMOKED | Spearman correlation test | N=0 |
Time to Death | Duration (Months) | 0.1-120.6 (median=37.1) |
censored | N = 322 | |
death | N = 164 | |
Significant markers | N = 62 | |
associated with shorter survival | 54 | |
associated with longer survival | 8 |
HazardRatio | Wald_P | Q | C_index | |
---|---|---|---|---|
HSA-MIR-223 | 1.62 | 4.97e-13 | 2.3e-10 | 0.646 |
HSA-MIR-130B | 2 | 6.237e-12 | 2.8e-09 | 0.645 |
HSA-MIR-34C | 1.28 | 3.2e-10 | 1.5e-07 | 0.634 |
HSA-MIR-21 | 2 | 7.889e-10 | 3.6e-07 | 0.659 |
HSA-MIR-365-2 | 1.68 | 1.44e-08 | 6.5e-06 | 0.621 |
HSA-MIR-10B | 0.57 | 1.838e-08 | 8.3e-06 | 0.369 |
HSA-MIR-18A | 1.55 | 2.374e-08 | 1.1e-05 | 0.619 |
HSA-MIR-365-1 | 1.64 | 3.232e-08 | 1.5e-05 | 0.617 |
HSA-MIR-34B | 1.31 | 3.437e-08 | 1.5e-05 | 0.624 |
HSA-MIR-1248 | 1.39 | 4.979e-08 | 2.2e-05 | 0.61 |
AGE | Mean (SD) | 60.57 (12) |
Significant markers | N = 1 | |
pos. correlated | 1 | |
neg. correlated | 0 |
SpearmanCorr | corrP | Q | |
---|---|---|---|
HSA-MIR-590 | 0.1806 | 6.232e-05 | 0.0285 |
NEOPLASM.DISEASESTAGE | Labels | N |
STAGE I | 230 | |
STAGE II | 53 | |
STAGE III | 124 | |
STAGE IV | 79 | |
Significant markers | N = 37 |
ANOVA_P | Q | |
---|---|---|
HSA-MIR-139 | 3.323e-12 | 1.52e-09 |
HSA-MIR-625 | 1.196e-10 | 5.45e-08 |
HSA-MIR-21 | 6.829e-09 | 3.11e-06 |
HSA-MIR-486 | 1.233e-08 | 5.6e-06 |
HSA-MIR-28 | 1.557e-08 | 7.06e-06 |
HSA-MIR-155 | 2.759e-08 | 1.25e-05 |
HSA-LET-7I | 3.102e-08 | 1.4e-05 |
HSA-MIR-130B | 3.929e-08 | 1.77e-05 |
HSA-MIR-144 | 6.786e-08 | 3.05e-05 |
HSA-MIR-10B | 2.015e-07 | 9.03e-05 |
PATHOLOGY.T.STAGE | Mean (SD) | 1.92 (0.97) |
N | ||
1 | 236 | |
2 | 64 | |
3 | 175 | |
4 | 11 | |
Significant markers | N = 33 | |
pos. correlated | 23 | |
neg. correlated | 10 |
SpearmanCorr | corrP | Q | |
---|---|---|---|
HSA-MIR-139 | -0.3315 | 6.28e-14 | 2.87e-11 |
HSA-MIR-486 | -0.2693 | 1.615e-09 | 7.36e-07 |
HSA-MIR-21 | 0.2688 | 1.73e-09 | 7.87e-07 |
HSA-MIR-625 | 0.2677 | 2.03e-09 | 9.22e-07 |
HSA-MIR-155 | 0.2482 | 2.943e-08 | 1.33e-05 |
HSA-MIR-144 | -0.2408 | 7.72e-08 | 3.49e-05 |
HSA-MIR-9-1 | 0.2341 | 1.793e-07 | 8.09e-05 |
HSA-MIR-130B | 0.233 | 2.041e-07 | 9.19e-05 |
HSA-MIR-451 | -0.2302 | 2.896e-07 | 0.00013 |
HSA-MIR-9-2 | 0.2248 | 5.527e-07 | 0.000248 |
PATHOLOGY.N.STAGE | Labels | N |
class0 | 223 | |
class1 | 18 | |
Significant markers | N = 0 |
PATHOLOGY.M.STAGE | Labels | N |
M0 | 405 | |
M1 | 78 | |
MX | 3 | |
Significant markers | N = 22 |
ANOVA_P | Q | |
---|---|---|
HSA-MIR-26A-1 | 8.162e-08 | 3.73e-05 |
HSA-MIR-144 | 3.859e-07 | 0.000176 |
HSA-MIR-625 | 3.963e-07 | 0.00018 |
HSA-MIR-1277 | 4.171e-07 | 0.000189 |
HSA-MIR-1269 | 9.483e-07 | 0.00043 |
HSA-MIR-155 | 4.507e-06 | 0.00204 |
HSA-MIR-191 | 5.737e-06 | 0.00259 |
HSA-MIR-28 | 1.025e-05 | 0.00461 |
HSA-LET-7I | 1.45e-05 | 0.00651 |
HSA-MIR-628 | 1.87e-05 | 0.00838 |
GENDER | Labels | N |
FEMALE | 165 | |
MALE | 321 | |
Significant markers | N = 9 | |
Higher in MALE | 3 | |
Higher in FEMALE | 6 |
T(pos if higher in 'MALE') | ttestP | Q | AUC | |
---|---|---|---|---|
HSA-MIR-100 | 8.24 | 4.513e-15 | 2.06e-12 | 0.7302 |
HSA-MIR-708 | 5.57 | 5.528e-08 | 2.52e-05 | 0.6608 |
HSA-MIR-599 | -5.47 | 1.06e-07 | 4.82e-05 | 0.6852 |
HSA-MIR-455 | -5.37 | 1.381e-07 | 6.27e-05 | 0.6581 |
HSA-MIR-30A | -4.45 | 1.117e-05 | 0.00506 | 0.6165 |
HSA-MIR-31 | 4.4 | 1.517e-05 | 0.00686 | 0.63 |
HSA-MIR-30C-2 | -4.19 | 3.637e-05 | 0.0164 | 0.6092 |
HSA-MIR-204 | -4.02 | 7.114e-05 | 0.032 | 0.6369 |
HSA-MIR-500B | -3.99 | 8.172e-05 | 0.0367 | 0.6076 |
No miR related to 'KARNOFSKY.PERFORMANCE.SCORE'.
KARNOFSKY.PERFORMANCE.SCORE | Mean (SD) | 88.33 (23) |
Score | N | |
0 | 2 | |
70 | 1 | |
80 | 3 | |
90 | 13 | |
100 | 17 | |
Significant markers | N = 0 |
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Expresson data file = KIRC-TP.miRseq_RPKM_log2.txt
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Clinical data file = KIRC-TP.merged_data.txt
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Number of patients = 486
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Number of miRs = 457
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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 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.
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.