This pipeline uses various statistical tests to identify genes whose promoter methylation levels correlated to selected clinical features.
Testing the association between 20126 genes and 8 clinical features across 433 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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1320 genes correlated to 'AGE'.
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TCHH , TRIM58 , SHISA2 , CACNA1B , ADAMTSL3 , ...
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24 genes correlated to 'GENDER'.
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ALG11__1 , UTP14C , POLDIP3 , RNU12 , KIF4B , ...
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270 genes correlated to 'KARNOFSKY.PERFORMANCE.SCORE'.
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PREP , RCAN1 , FAM131A , HS6ST1 , KCNN4 , ...
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4198 genes correlated to 'HISTOLOGICAL.TYPE'.
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REST , MAPKAP1 , SLC2A4RG , BVES , GLIS3 , ...
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1559 genes correlated to 'RADIATIONS.RADIATION.REGIMENINDICATION'.
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PPP1R8 , HSPA13 , BIRC6 , DAZL , MTX2 , ...
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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=1320 | older | N=446 | younger | N=874 |
GENDER | Wilcoxon test | N=24 | male | N=24 | female | N=0 |
KARNOFSKY PERFORMANCE SCORE | Spearman correlation test | N=270 | higher score | N=269 | lower score | N=1 |
HISTOLOGICAL TYPE | Kruskal-Wallis test | N=4198 | ||||
RADIATIONS RADIATION REGIMENINDICATION | Wilcoxon test | N=1559 | yes | N=1559 | no | N=0 |
RACE | Kruskal-Wallis test | N=3 | ||||
ETHNICITY | Wilcoxon test | N=0 |
Time to Death | Duration (Months) | 0-211.2 (median=15.8) |
censored | N = 355 | |
death | N = 75 | |
Significant markers | N = 0 |
AGE | Mean (SD) | 42.91 (13) |
Significant markers | N = 1320 | |
pos. correlated | 446 | |
neg. correlated | 874 |
SpearmanCorr | corrP | Q | |
---|---|---|---|
TCHH | 0.5501 | 1.538e-35 | 3.09e-31 |
TRIM58 | 0.5441 | 1.163e-34 | 2.34e-30 |
SHISA2 | 0.5224 | 1.295e-31 | 2.61e-27 |
CACNA1B | 0.5163 | 8.238e-31 | 1.66e-26 |
ADAMTSL3 | 0.5055 | 2.096e-29 | 4.22e-25 |
LOC150786 | 0.5039 | 3.354e-29 | 6.75e-25 |
FOXE3 | 0.4986 | 2.091e-28 | 4.21e-24 |
RELN | 0.4929 | 7.958e-28 | 1.6e-23 |
TFAP2B | 0.4874 | 3.724e-27 | 7.49e-23 |
KLRG2 | 0.4814 | 1.903e-26 | 3.83e-22 |
GENDER | Labels | N |
FEMALE | 192 | |
MALE | 241 | |
Significant markers | N = 24 | |
Higher in MALE | 24 | |
Higher in FEMALE | 0 |
W(pos if higher in 'MALE') | wilcoxontestP | Q | AUC | |
---|---|---|---|---|
ALG11__1 | 45372 | 3.248e-66 | 6.54e-62 | 0.9805 |
UTP14C | 45372 | 3.248e-66 | 6.54e-62 | 0.9805 |
POLDIP3 | 3589 | 1.398e-51 | 2.81e-47 | 0.9224 |
RNU12 | 3589 | 1.398e-51 | 2.81e-47 | 0.9224 |
KIF4B | 10464 | 1.18e-22 | 2.37e-18 | 0.7739 |
WBP11P1 | 34853 | 1.341e-19 | 2.7e-15 | 0.7532 |
TLE1 | 12386 | 9.611e-17 | 1.93e-12 | 0.7323 |
LOC389791__1 | 33727 | 2.687e-16 | 5.41e-12 | 0.7289 |
PTGES2__1 | 33727 | 2.687e-16 | 5.41e-12 | 0.7289 |
ZC3H14 | 13763 | 4.322e-13 | 8.7e-09 | 0.7026 |
270 genes related to 'KARNOFSKY.PERFORMANCE.SCORE'.
KARNOFSKY.PERFORMANCE.SCORE | Mean (SD) | 87.72 (12) |
Significant markers | N = 270 | |
pos. correlated | 269 | |
neg. correlated | 1 |
SpearmanCorr | corrP | Q | |
---|---|---|---|
PREP | 0.3377 | 4.402e-08 | 0.000886 |
RCAN1 | 0.3303 | 8.975e-08 | 0.00181 |
FAM131A | 0.3291 | 9.982e-08 | 0.00201 |
HS6ST1 | 0.3288 | 1.028e-07 | 0.00207 |
KCNN4 | 0.3288 | 1.03e-07 | 0.00207 |
LMO4 | 0.3287 | 1.037e-07 | 0.00209 |
IQCK | 0.3256 | 1.393e-07 | 0.0028 |
METTL8__1 | 0.3253 | 1.431e-07 | 0.00288 |
TMEM165 | 0.3229 | 1.787e-07 | 0.00359 |
BTN2A3 | 0.3228 | 1.807e-07 | 0.00364 |
HISTOLOGICAL.TYPE | Labels | N |
ASTROCYTOMA | 159 | |
OLIGOASTROCYTOMA | 108 | |
OLIGODENDROGLIOMA | 166 | |
Significant markers | N = 4198 |
1559 genes related to 'RADIATIONS.RADIATION.REGIMENINDICATION'.
RADIATIONS.RADIATION.REGIMENINDICATION | Labels | N |
NO | 89 | |
YES | 344 | |
Significant markers | N = 1559 | |
Higher in YES | 1559 | |
Higher in NO | 0 |
W(pos if higher in 'YES') | wilcoxontestP | Q | AUC | |
---|---|---|---|---|
PPP1R8 | 25352 | 1.367e-21 | 2.75e-17 | 0.8281 |
HSPA13 | 25275 | 2.761e-21 | 5.56e-17 | 0.8255 |
BIRC6 | 24691 | 4.816e-19 | 9.69e-15 | 0.8065 |
DAZL | 24003 | 3.099e-18 | 6.24e-14 | 0.802 |
MTX2 | 6243 | 7.043e-18 | 1.42e-13 | 0.7961 |
BMP5 | 24109 | 9.085e-18 | 1.83e-13 | 0.7964 |
AMY2B | 6279 | 9.488e-18 | 1.91e-13 | 0.7949 |
RNPC3 | 6279 | 9.488e-18 | 1.91e-13 | 0.7949 |
TMEM135 | 23232 | 1.335e-17 | 2.69e-13 | 0.7992 |
ZFP91 | 6335 | 1.505e-17 | 3.03e-13 | 0.7931 |
RACE | Labels | N |
AMERICAN INDIAN OR ALASKA NATIVE | 1 | |
ASIAN | 6 | |
BLACK OR AFRICAN AMERICAN | 14 | |
WHITE | 403 | |
Significant markers | N = 3 |
ANOVA_P | Q | |
---|---|---|
C6ORF52__1 | 6.086e-07 | 0.0122 |
PAK1IP1__1 | 6.086e-07 | 0.0122 |
RNF135 | 6.863e-06 | 0.138 |
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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 = 433
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Number of genes = 20126
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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.