This pipeline uses various statistical tests to identify RPPAs whose expression levels correlated to selected clinical features.
Testing the association between 189 genes and 6 clinical features across 239 samples, statistically thresholded by Q value < 0.05, 4 clinical features related to at least one genes.
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11 genes correlated to 'Time to Death'.
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ANXA1|ANNEXIN-1-M-E , MAPK14|P38_MAPK-R-V , SERPINE1|PAI-1-M-E , PGR|PR-R-V , CHEK2|CHK2_PT68-R-E , ...
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4 genes correlated to 'AGE'.
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IGFBP2|IGFBP2-R-V , PEA15|PEA15-R-V , SERPINE1|PAI-1-M-E , EGFR|EGFR-R-V
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1 gene correlated to 'GENDER'.
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RAB11A RAB11B|RAB11-R-E
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20 genes correlated to 'HISTOLOGICAL.TYPE'.
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SYK|SYK-M-V , ANXA1|ANNEXIN-1-M-E , MAPK14|P38_MAPK-R-V , BAX|BAX-R-V , PTEN|PTEN-R-V , ...
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No genes correlated to 'KARNOFSKY.PERFORMANCE.SCORE', and 'RADIATIONS.RADIATION.REGIMENINDICATION'.
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=11 | shorter survival | N=7 | longer survival | N=4 |
AGE | Spearman correlation test | N=4 | older | N=3 | younger | N=1 |
GENDER | t test | N=1 | male | N=1 | female | N=0 |
KARNOFSKY PERFORMANCE SCORE | Spearman correlation test | N=0 | ||||
HISTOLOGICAL TYPE | ANOVA test | N=20 | ||||
RADIATIONS RADIATION REGIMENINDICATION | t test | N=0 |
Time to Death | Duration (Months) | 0-211.2 (median=16.2) |
censored | N = 184 | |
death | N = 55 | |
Significant markers | N = 11 | |
associated with shorter survival | 7 | |
associated with longer survival | 4 |
HazardRatio | Wald_P | Q | C_index | |
---|---|---|---|---|
ANXA1|ANNEXIN-1-M-E | 2.1 | 1.78e-07 | 3.4e-05 | 0.722 |
MAPK14|P38_MAPK-R-V | 3.6 | 1.916e-05 | 0.0036 | 0.688 |
SERPINE1|PAI-1-M-E | 2.3 | 2.069e-05 | 0.0039 | 0.679 |
PGR|PR-R-V | 0 | 5.07e-05 | 0.0094 | 0.3 |
CHEK2|CHK2_PT68-R-E | 0.03 | 0.0001133 | 0.021 | 0.318 |
SMAD1|SMAD1-R-V | 5.2 | 0.0001197 | 0.022 | 0.645 |
INPP4B|INPP4B-G-E | 0.14 | 0.0001347 | 0.025 | 0.358 |
BAX|BAX-R-V | 5.2 | 0.0001352 | 0.025 | 0.673 |
IGFBP2|IGFBP2-R-V | 2.1 | 0.000179 | 0.032 | 0.734 |
RAB11A RAB11B|RAB11-R-E | 0.04 | 0.0002261 | 0.041 | 0.308 |
AGE | Mean (SD) | 42.72 (13) |
Significant markers | N = 4 | |
pos. correlated | 3 | |
neg. correlated | 1 |
SpearmanCorr | corrP | Q | |
---|---|---|---|
IGFBP2|IGFBP2-R-V | 0.3273 | 2.267e-07 | 4.29e-05 |
PEA15|PEA15-R-V | -0.2964 | 3.102e-06 | 0.000583 |
SERPINE1|PAI-1-M-E | 0.266 | 3.109e-05 | 0.00581 |
EGFR|EGFR-R-V | 0.2412 | 0.0001664 | 0.0309 |
GENDER | Labels | N |
FEMALE | 106 | |
MALE | 133 | |
Significant markers | N = 1 | |
Higher in MALE | 1 | |
Higher in FEMALE | 0 |
T(pos if higher in 'MALE') | ttestP | Q | AUC | |
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RAB11A RAB11B|RAB11-R-E | 3.92 | 0.0001166 | 0.022 | 0.6437 |
No gene related to 'KARNOFSKY.PERFORMANCE.SCORE'.
KARNOFSKY.PERFORMANCE.SCORE | Mean (SD) | 87.57 (11) |
Significant markers | N = 0 |
HISTOLOGICAL.TYPE | Labels | N |
ASTROCYTOMA | 73 | |
OLIGOASTROCYTOMA | 69 | |
OLIGODENDROGLIOMA | 97 | |
Significant markers | N = 20 |
ANOVA_P | Q | |
---|---|---|
SYK|SYK-M-V | 6.074e-13 | 1.15e-10 |
ANXA1|ANNEXIN-1-M-E | 2.886e-08 | 5.43e-06 |
MAPK14|P38_MAPK-R-V | 3.308e-07 | 6.19e-05 |
BAX|BAX-R-V | 4.389e-07 | 8.16e-05 |
PTEN|PTEN-R-V | 7.701e-07 | 0.000142 |
YAP1|YAP_PS127-R-E | 1.116e-06 | 0.000205 |
AR|AR-R-V | 2.358e-06 | 0.000431 |
KIT|C-KIT-R-V | 1.733e-05 | 0.00315 |
ERBB3|HER3_PY1289-R-C | 1.816e-05 | 0.00329 |
BECN1|BECLIN-G-C | 2.531e-05 | 0.00455 |
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Expresson data file = LGG-TP.rppa.txt
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Clinical data file = LGG-TP.merged_data.txt
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Number of patients = 239
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Number of genes = 189
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Number of clinical features = 6
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 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.