This pipeline uses various statistical tests to identify RPPAs whose expression levels correlated to selected clinical features.
Testing the association between 165 genes and 7 clinical features across 407 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 2 clinical features related to at least one genes.
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3 genes correlated to 'Time to Death'.
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MAPK1 MAPK3|MAPK_PT202_Y204-R-V , MAP2K1|MEK1_PS217_S221-R-V , YBX1|YB-1_PS102-R-V
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10 genes correlated to 'AGE'.
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PGR|PR-R-V , ESR1|ER-ALPHA-R-V , ERBB2|HER2-M-V , ERBB2|HER2_PY1248-R-V , IGFBP2|IGFBP2-R-V , ...
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No genes correlated to 'PRIMARY.SITE.OF.DISEASE', 'KARNOFSKY.PERFORMANCE.SCORE', '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=3 | shorter survival | N=3 | longer survival | N=0 |
AGE | Spearman correlation test | N=10 | older | N=5 | younger | N=5 |
PRIMARY SITE OF DISEASE | Kruskal-Wallis test | N=0 | ||||
KARNOFSKY PERFORMANCE SCORE | Spearman correlation 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=28.7) |
censored | N = 188 | |
death | N = 213 | |
Significant markers | N = 3 | |
associated with shorter survival | 3 | |
associated with longer survival | 0 |
HazardRatio | Wald_P | Q | C_index | |
---|---|---|---|---|
MAPK1 MAPK3|MAPK_PT202_Y204-R-V | 1.28 | 9.224e-05 | 0.015 | 0.575 |
MAP2K1|MEK1_PS217_S221-R-V | 1.91 | 0.0001133 | 0.019 | 0.582 |
YBX1|YB-1_PS102-R-V | 1.83 | 0.0009269 | 0.15 | 0.55 |
AGE | Mean (SD) | 59.67 (12) |
Significant markers | N = 10 | |
pos. correlated | 5 | |
neg. correlated | 5 |
SpearmanCorr | corrP | Q | |
---|---|---|---|
PGR|PR-R-V | -0.1951 | 8.575e-05 | 0.0141 |
ESR1|ER-ALPHA-R-V | 0.1899 | 0.0001324 | 0.0217 |
ERBB2|HER2-M-V | 0.1873 | 0.0001642 | 0.0268 |
ERBB2|HER2_PY1248-R-V | 0.1815 | 0.0002642 | 0.0428 |
IGFBP2|IGFBP2-R-V | 0.1743 | 0.0004636 | 0.0746 |
EIF4EBP1|4E-BP1-R-V | -0.1673 | 0.0007839 | 0.125 |
EEF2K|EEF2K-R-V | -0.1653 | 0.0009083 | 0.144 |
CDH1|E-CADHERIN-R-V | -0.1592 | 0.001403 | 0.222 |
BIRC2 |CIAP-R-V | -0.1569 | 0.00165 | 0.259 |
COL6A1|COLLAGEN_VI-R-V | 0.1547 | 0.001921 | 0.3 |
PRIMARY.SITE.OF.DISEASE | Labels | N |
OMENTUM | 2 | |
OVARY | 403 | |
PERITONEUM OVARY | 2 | |
Significant markers | N = 0 |
No gene related to 'KARNOFSKY.PERFORMANCE.SCORE'.
KARNOFSKY.PERFORMANCE.SCORE | Mean (SD) | 74.9 (12) |
Score | N | |
40 | 1 | |
60 | 14 | |
80 | 33 | |
100 | 3 | |
Significant markers | N = 0 |
COMPLETENESS.OF.RESECTION | Labels | N |
R0 | 13 | |
R1 | 28 | |
R2 | 2 | |
Significant markers | N = 0 |
RACE | Labels | N |
AMERICAN INDIAN OR ALASKA NATIVE | 3 | |
ASIAN | 16 | |
BLACK OR AFRICAN AMERICAN | 19 | |
WHITE | 342 | |
Significant markers | N = 0 |
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Expresson data file = OV-TP.rppa.txt
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Clinical data file = OV-TP.merged_data.txt
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Number of patients = 407
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Number of genes = 165
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Number of clinical features = 7
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.