This pipeline uses various statistical tests to identify miRs whose log2 expression levels correlated to selected clinical features.
Testing the association between 817 miRs and 8 clinical features across 560 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 3 clinical features related to at least one miRs.
-
2 miRs correlated to 'Time to Death'.
-
HSA-MIR-551B* , HSA-MIR-198
-
13 miRs correlated to 'AGE'.
-
HSA-MIR-30B* , HSA-MIR-30D* , HSA-MIR-30B , HUR_4 , HSA-MIR-30D , ...
-
1 miR correlated to 'RACE'.
-
HSA-MIR-145
-
No miRs correlated to 'PRIMARY.SITE.OF.DISEASE', 'KARNOFSKY.PERFORMANCE.SCORE', 'RADIATIONS.RADIATION.REGIMENINDICATION', 'COMPLETENESS.OF.RESECTION', and 'ETHNICITY'.
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=2 | shorter survival | N=2 | longer survival | N=0 |
AGE | Spearman correlation test | N=13 | older | N=5 | younger | N=8 |
PRIMARY SITE OF DISEASE | Kruskal-Wallis test | N=0 | ||||
KARNOFSKY PERFORMANCE SCORE | Spearman correlation test | N=0 | ||||
RADIATIONS RADIATION REGIMENINDICATION | Wilcoxon test | N=0 | ||||
COMPLETENESS OF RESECTION | Kruskal-Wallis test | N=0 | ||||
RACE | Kruskal-Wallis test | N=1 | ||||
ETHNICITY | Wilcoxon test | N=0 |
Time to Death | Duration (Months) | 0.3-180.2 (median=28.5) |
censored | N = 262 | |
death | N = 293 | |
Significant markers | N = 2 | |
associated with shorter survival | 2 | |
associated with longer survival | 0 |
HazardRatio | Wald_P | Q | C_index | |
---|---|---|---|---|
HSA-MIR-551B* | 9.4 | 0.0001322 | 0.11 | 0.577 |
HSA-MIR-198 | 1.87 | 0.0002327 | 0.19 | 0.568 |
AGE | Mean (SD) | 59.71 (12) |
Significant markers | N = 13 | |
pos. correlated | 5 | |
neg. correlated | 8 |
SpearmanCorr | corrP | Q | |
---|---|---|---|
HSA-MIR-30B* | -0.2239 | 1.155e-07 | 9.43e-05 |
HSA-MIR-30D* | -0.2226 | 1.37e-07 | 0.000112 |
HSA-MIR-30B | -0.2043 | 1.388e-06 | 0.00113 |
HUR_4 | 0.1979 | 2.974e-06 | 0.00242 |
HSA-MIR-30D | -0.1974 | 3.166e-06 | 0.00257 |
HSA-LET-7A* | -0.1633 | 0.0001216 | 0.0987 |
HSA-MIR-331-3P | 0.1621 | 0.000136 | 0.11 |
HSA-MIR-338-3P | 0.1591 | 0.0001811 | 0.147 |
HSA-MIR-449A | -0.1579 | 0.0002033 | 0.164 |
HSA-MIR-9* | 0.1564 | 0.0002349 | 0.19 |
PRIMARY.SITE.OF.DISEASE | Labels | N |
OMENTUM | 2 | |
OVARY | 556 | |
PERITONEUM OVARY | 2 | |
Significant markers | N = 0 |
No miR related to 'KARNOFSKY.PERFORMANCE.SCORE'.
KARNOFSKY.PERFORMANCE.SCORE | Mean (SD) | 75.64 (13) |
Score | N | |
40 | 2 | |
60 | 20 | |
80 | 49 | |
100 | 7 | |
Significant markers | N = 0 |
No miR related to 'RADIATIONS.RADIATION.REGIMENINDICATION'.
RADIATIONS.RADIATION.REGIMENINDICATION | Labels | N |
NO | 3 | |
YES | 557 | |
Significant markers | N = 0 |
COMPLETENESS.OF.RESECTION | Labels | N |
R0 | 14 | |
R1 | 27 | |
R2 | 1 | |
Significant markers | N = 0 |
RACE | Labels | N |
AMERICAN INDIAN OR ALASKA NATIVE | 2 | |
ASIAN | 19 | |
BLACK OR AFRICAN AMERICAN | 23 | |
NATIVE HAWAIIAN OR OTHER PACIFIC ISLANDER | 1 | |
WHITE | 484 | |
Significant markers | N = 1 |
ANOVA_P | Q | |
---|---|---|
HSA-MIR-145 | 0.0003585 | 0.293 |
-
Expresson data file = OV-TP.mirna__h_mirna_8x15kv2__unc_edu__Level_3__unc_DWD_Batch_adjusted__data.data.txt
-
Clinical data file = OV-TP.merged_data.txt
-
Number of patients = 560
-
Number of miRs = 817
-
Number of clinical features = 8
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.