This pipeline uses various statistical tests to identify genes whose promoter methylation levels correlated to selected clinical features.
Testing the association between 20110 genes and 8 clinical features across 398 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 6 clinical features related to at least one genes.
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1351 genes correlated to 'AGE'.
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TCHH , TRIM58 , SHISA2 , LOC150786 , ADAMTSL3 , ...
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24 genes correlated to 'GENDER'.
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ALG11__2 , UTP14C , POLDIP3 , RNU12 , KIF4B , ...
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137 genes correlated to 'KARNOFSKY.PERFORMANCE.SCORE'.
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PREP , ALDH1A1 , RCAN1 , TMEM165 , HS6ST1 , ...
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3831 genes correlated to 'HISTOLOGICAL.TYPE'.
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REST , MAPKAP1 , GLIS3 , SLC2A4RG , C2ORF67 , ...
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1356 genes correlated to 'RADIATIONS.RADIATION.REGIMENINDICATION'.
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PPP1R8 , HSPA13 , BIRC6 , AMY2B , RNPC3 , ...
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3 genes correlated to 'RACE'.
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C6ORF52__1 , PAK1IP1__1 , RNF135
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No genes correlated to 'Time to Death', and 'ETHNICITY'.
Complete statistical result table is provided in Supplement Table 1
Clinical feature | Statistical test | Significant genes | Associated with | Associated with | ||
---|---|---|---|---|---|---|
Time to Death | Cox regression test | N=0 | ||||
AGE | Spearman correlation test | N=1351 | older | N=440 | younger | N=911 |
GENDER | Wilcoxon test | N=24 | male | N=24 | female | N=0 |
KARNOFSKY PERFORMANCE SCORE | Spearman correlation test | N=137 | higher score | N=137 | lower score | N=0 |
HISTOLOGICAL TYPE | Kruskal-Wallis test | N=3831 | ||||
RADIATIONS RADIATION REGIMENINDICATION | Wilcoxon test | N=1356 | yes | N=1356 | no | N=0 |
RACE | Kruskal-Wallis test | N=3 | ||||
ETHNICITY | Wilcoxon test | N=0 |
Time to Death | Duration (Months) | 0-211.2 (median=14.9) |
censored | N = 326 | |
death | N = 67 | |
Significant markers | N = 0 |
AGE | Mean (SD) | 43.12 (13) |
Significant markers | N = 1351 | |
pos. correlated | 440 | |
neg. correlated | 911 |
SpearmanCorr | corrP | Q | |
---|---|---|---|
TCHH | 0.5457 | 2.941e-32 | 5.91e-28 |
TRIM58 | 0.5398 | 1.751e-31 | 3.52e-27 |
SHISA2 | 0.5224 | 3.044e-29 | 6.12e-25 |
LOC150786 | 0.5105 | 8.588e-28 | 1.73e-23 |
ADAMTSL3 | 0.5006 | 1.234e-26 | 2.48e-22 |
FOXE3 | 0.497 | 4.331e-26 | 8.71e-22 |
RELN | 0.4922 | 1.134e-25 | 2.28e-21 |
GALNT14 | 0.4901 | 1.934e-25 | 3.89e-21 |
TFAP2B | 0.4876 | 3.651e-25 | 7.34e-21 |
SLC22A16 | 0.4817 | 1.643e-24 | 3.3e-20 |
GENDER | Labels | N |
FEMALE | 178 | |
MALE | 220 | |
Significant markers | N = 24 | |
Higher in MALE | 24 | |
Higher in FEMALE | 0 |
W(pos if higher in 'MALE') | wilcoxontestP | Q | AUC | |
---|---|---|---|---|
ALG11__2 | 38337 | 1.032e-60 | 2.07e-56 | 0.979 |
UTP14C | 38337 | 1.032e-60 | 2.07e-56 | 0.979 |
POLDIP3 | 2857 | 1.253e-48 | 2.52e-44 | 0.927 |
RNU12 | 2857 | 1.253e-48 | 2.52e-44 | 0.927 |
KIF4B | 8574 | 5.172e-22 | 1.04e-17 | 0.7811 |
WBP11P1 | 29643 | 1.161e-18 | 2.33e-14 | 0.757 |
LOC389791__1 | 28766 | 8.292e-16 | 1.67e-11 | 0.7346 |
PTGES2__1 | 28766 | 8.292e-16 | 1.67e-11 | 0.7346 |
TLE1 | 10511 | 1.907e-15 | 3.83e-11 | 0.7316 |
ZNF839 | 11834 | 1.138e-11 | 2.29e-07 | 0.6978 |
137 genes related to 'KARNOFSKY.PERFORMANCE.SCORE'.
KARNOFSKY.PERFORMANCE.SCORE | Mean (SD) | 87.91 (12) |
Significant markers | N = 137 | |
pos. correlated | 137 | |
neg. correlated | 0 |
SpearmanCorr | corrP | Q | |
---|---|---|---|
PREP | 0.3506 | 3.575e-08 | 0.000719 |
ALDH1A1 | 0.3332 | 1.789e-07 | 0.0036 |
RCAN1 | 0.3325 | 1.903e-07 | 0.00383 |
TMEM165 | 0.3308 | 2.216e-07 | 0.00446 |
HS6ST1 | 0.3274 | 3e-07 | 0.00603 |
UBC | 0.3266 | 3.221e-07 | 0.00648 |
DEGS1 | 0.3266 | 3.233e-07 | 0.0065 |
BTN2A3 | 0.3245 | 3.871e-07 | 0.00778 |
KCNN4 | 0.3226 | 4.579e-07 | 0.00921 |
IGF1 | 0.3213 | 5.091e-07 | 0.0102 |
HISTOLOGICAL.TYPE | Labels | N |
ASTROCYTOMA | 142 | |
OLIGOASTROCYTOMA | 103 | |
OLIGODENDROGLIOMA | 153 | |
Significant markers | N = 3831 |
1356 genes related to 'RADIATIONS.RADIATION.REGIMENINDICATION'.
RADIATIONS.RADIATION.REGIMENINDICATION | Labels | N |
NO | 85 | |
YES | 313 | |
Significant markers | N = 1356 | |
Higher in YES | 1356 | |
Higher in NO | 0 |
W(pos if higher in 'YES') | wilcoxontestP | Q | AUC | |
---|---|---|---|---|
PPP1R8 | 21655 | 6.686e-19 | 1.34e-14 | 0.8139 |
HSPA13 | 21593 | 1.207e-18 | 2.43e-14 | 0.8116 |
BIRC6 | 21156 | 6.858e-17 | 1.38e-12 | 0.7952 |
AMY2B | 5561 | 1.866e-16 | 3.75e-12 | 0.791 |
RNPC3 | 5561 | 1.866e-16 | 3.75e-12 | 0.791 |
MTX2 | 5581 | 2.228e-16 | 4.48e-12 | 0.7902 |
DAZL | 20494 | 5.762e-16 | 1.16e-11 | 0.7889 |
TMEM135 | 19920 | 7.418e-16 | 1.49e-11 | 0.7908 |
BMP5 | 20630 | 1.112e-15 | 2.23e-11 | 0.7846 |
ASPM | 20802 | 1.548e-15 | 3.11e-11 | 0.7819 |
RACE | Labels | N |
AMERICAN INDIAN OR ALASKA NATIVE | 1 | |
ASIAN | 2 | |
BLACK OR AFRICAN AMERICAN | 13 | |
WHITE | 375 | |
Significant markers | N = 3 |
ANOVA_P | Q | |
---|---|---|
C6ORF52__1 | 2.903e-06 | 0.0584 |
PAK1IP1__1 | 2.903e-06 | 0.0584 |
RNF135 | 9.499e-06 | 0.191 |
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Expresson data file = LGG-TP.meth.by_min_clin_corr.data.txt
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Clinical data file = LGG-TP.merged_data.txt
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Number of patients = 398
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Number of genes = 20110
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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 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.