This pipeline uses various statistical tests to identify mRNAs whose log2 expression levels correlated to selected clinical features.
Testing the association between 18632 genes and 8 clinical features across 562 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 3 clinical features related to at least one genes.
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5 genes correlated to 'Time to Death'.
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ZFHX4 , PPM2C , TLL1 , LUZP1 , EXOC6B
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329 genes correlated to 'AGE'.
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STS , GREB1 , DEPDC6 , GNPNAT1 , SLCO1A2 , ...
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2 genes correlated to 'KARNOFSKY.PERFORMANCE.SCORE'.
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WDR60 , NDUFA13
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No genes correlated to 'PRIMARY.SITE.OF.DISEASE', 'RADIATIONS.RADIATION.REGIMENINDICATION', 'COMPLETENESS.OF.RESECTION', 'RACE', and 'ETHNICITY'.
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=5 | shorter survival | N=5 | longer survival | N=0 |
AGE | Spearman correlation test | N=329 | older | N=129 | younger | N=200 |
PRIMARY SITE OF DISEASE | Kruskal-Wallis test | N=0 | ||||
KARNOFSKY PERFORMANCE SCORE | Spearman correlation test | N=2 | higher score | N=1 | lower score | N=1 |
RADIATIONS RADIATION REGIMENINDICATION | Wilcoxon test | N=0 | ||||
COMPLETENESS OF RESECTION | Kruskal-Wallis test | N=0 | ||||
RACE | Kruskal-Wallis test | N=0 | ||||
ETHNICITY | Wilcoxon test | N=0 |
Time to Death | Duration (Months) | 0.3-180.2 (median=28.6) |
censored | N = 264 | |
death | N = 293 | |
Significant markers | N = 5 | |
associated with shorter survival | 5 | |
associated with longer survival | 0 |
AGE | Mean (SD) | 59.72 (12) |
Significant markers | N = 329 | |
pos. correlated | 129 | |
neg. correlated | 200 |
SpearmanCorr | corrP | Q | |
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STS | -0.307 | 1.713e-13 | 3.19e-09 |
GREB1 | -0.3024 | 4.058e-13 | 7.56e-09 |
DEPDC6 | -0.301 | 5.286e-13 | 9.85e-09 |
GNPNAT1 | -0.2963 | 1.261e-12 | 2.35e-08 |
SLCO1A2 | 0.2853 | 8.849e-12 | 1.65e-07 |
EIF4E3 | -0.2847 | 9.779e-12 | 1.82e-07 |
NPAL2 | -0.2761 | 4.258e-11 | 7.93e-07 |
BRCC3 | -0.275 | 5.105e-11 | 9.51e-07 |
NLK | 0.2749 | 5.176e-11 | 9.64e-07 |
APPL2 | 0.2747 | 5.406e-11 | 1.01e-06 |
PRIMARY.SITE.OF.DISEASE | Labels | N |
OMENTUM | 2 | |
OVARY | 558 | |
PERITONEUM OVARY | 2 | |
Significant markers | N = 0 |
2 genes 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 = 2 | |
pos. correlated | 1 | |
neg. correlated | 1 |
No gene related to 'RADIATIONS.RADIATION.REGIMENINDICATION'.
RADIATIONS.RADIATION.REGIMENINDICATION | Labels | N |
NO | 3 | |
YES | 559 | |
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 | 24 | |
NATIVE HAWAIIAN OR OTHER PACIFIC ISLANDER | 1 | |
WHITE | 485 | |
Significant markers | N = 0 |
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Expresson data file = OV-TP.medianexp.txt
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Clinical data file = OV-TP.merged_data.txt
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Number of patients = 562
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Number of genes = 18632
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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.