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 248 samples, statistically thresholded by Q value < 0.05, 5 clinical features related to at least one genes.
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12 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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3 genes correlated to 'AGE'.
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IGFBP2|IGFBP2-R-V , PEA15|PEA15-R-V , SERPINE1|PAI-1-M-E
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1 gene correlated to 'GENDER'.
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RAB11A RAB11B|RAB11-R-E
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1 gene correlated to 'KARNOFSKY.PERFORMANCE.SCORE'.
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IGFBP2|IGFBP2-R-V
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27 genes correlated to 'HISTOLOGICAL.TYPE'.
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SYK|SYK-M-V , ANXA1|ANNEXIN-1-M-E , BAX|BAX-R-V , AR|AR-R-V , PTEN|PTEN-R-V , ...
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No genes correlated to '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=12 | shorter survival | N=7 | longer survival | N=5 |
AGE | Spearman correlation test | N=3 | older | N=2 | younger | N=1 |
GENDER | t test | N=1 | male | N=1 | female | N=0 |
KARNOFSKY PERFORMANCE SCORE | Spearman correlation test | N=1 | higher score | N=0 | lower score | N=1 |
HISTOLOGICAL TYPE | ANOVA test | N=27 | ||||
RADIATIONS RADIATION REGIMENINDICATION | t test | N=0 |
Time to Death | Duration (Months) | 0-211.2 (median=16.4) |
censored | N = 193 | |
death | N = 55 | |
Significant markers | N = 12 | |
associated with shorter survival | 7 | |
associated with longer survival | 5 |
HazardRatio | Wald_P | Q | C_index | |
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ANXA1|ANNEXIN-1-M-E | 2.1 | 2.03e-07 | 3.8e-05 | 0.721 |
MAPK14|P38_MAPK-R-V | 3.7 | 1.378e-05 | 0.0026 | 0.691 |
SERPINE1|PAI-1-M-E | 2.3 | 1.509e-05 | 0.0028 | 0.68 |
PGR|PR-R-V | 0 | 4.747e-05 | 0.0088 | 0.3 |
CHEK2|CHK2_PT68-R-E | 0.03 | 0.0001022 | 0.019 | 0.317 |
SMAD1|SMAD1-R-V | 5.3 | 0.0001085 | 0.02 | 0.645 |
INPP4B|INPP4B-G-E | 0.13 | 0.0001132 | 0.021 | 0.358 |
BAX|BAX-R-V | 5.1 | 0.0001653 | 0.03 | 0.669 |
IGFBP2|IGFBP2-R-V | 2.1 | 0.0001816 | 0.033 | 0.735 |
RAB11A RAB11B|RAB11-R-E | 0.04 | 0.0002358 | 0.042 | 0.309 |
AGE | Mean (SD) | 42.79 (13) |
Significant markers | N = 3 | |
pos. correlated | 2 | |
neg. correlated | 1 |
SpearmanCorr | corrP | Q | |
---|---|---|---|
IGFBP2|IGFBP2-R-V | 0.3275 | 1.303e-07 | 2.46e-05 |
PEA15|PEA15-R-V | -0.2942 | 2.421e-06 | 0.000455 |
SERPINE1|PAI-1-M-E | 0.2843 | 5.417e-06 | 0.00101 |
GENDER | Labels | N |
FEMALE | 107 | |
MALE | 141 | |
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 | 3.96 | 0.0001003 | 0.019 | 0.642 |
One gene related to 'KARNOFSKY.PERFORMANCE.SCORE'.
KARNOFSKY.PERFORMANCE.SCORE | Mean (SD) | 87.43 (11) |
Significant markers | N = 1 | |
pos. correlated | 0 | |
neg. correlated | 1 |
SpearmanCorr | corrP | Q | |
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IGFBP2|IGFBP2-R-V | -0.3524 | 0.0001709 | 0.0323 |
HISTOLOGICAL.TYPE | Labels | N |
ASTROCYTOMA | 79 | |
OLIGOASTROCYTOMA | 70 | |
OLIGODENDROGLIOMA | 99 | |
Significant markers | N = 27 |
ANOVA_P | Q | |
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SYK|SYK-M-V | 6.511e-15 | 1.23e-12 |
ANXA1|ANNEXIN-1-M-E | 2.047e-09 | 3.85e-07 |
BAX|BAX-R-V | 4.87e-08 | 9.11e-06 |
AR|AR-R-V | 1.041e-07 | 1.94e-05 |
PTEN|PTEN-R-V | 1.955e-07 | 3.62e-05 |
MAPK14|P38_MAPK-R-V | 2.036e-07 | 3.75e-05 |
YAP1|YAP_PS127-R-E | 2.194e-07 | 4.02e-05 |
ERBB3|HER3_PY1289-R-C | 2.118e-06 | 0.000385 |
ACACA|ACC1-R-E | 4.219e-06 | 0.000764 |
KIT|C-KIT-R-V | 5.348e-06 | 0.000963 |
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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 = 248
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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.