This pipeline uses various statistical tests to identify genes whose promoter methylation levels correlated to selected clinical features.
Testing the association between 17247 genes and 8 clinical features across 58 samples, statistically thresholded by Q value < 0.05, 5 clinical features related to at least one genes.
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1 gene correlated to 'AGE'.
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IGF2BP2
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3 genes correlated to 'GENDER'.
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NARFL , ATAD5 , CCNYL1
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51 genes correlated to 'PATHOLOGY.T'.
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DLX6AS , GNASAS , GP2 , GPR150 , PCDHB19P , ...
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22 genes correlated to 'PATHOLOGICSPREAD(M)'.
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RFX7 , GDPD4 , ERCC2 , DHDH , UNC93A , ...
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33 genes correlated to 'TUMOR.STAGE'.
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INSM1 , ZNF177 , DLX6AS , CNIH3 , MATK , ...
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No genes correlated to 'Time to Death', 'KARNOFSKY.PERFORMANCE.SCORE', and 'PATHOLOGY.N'.
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=1 | older | N=1 | younger | N=0 |
GENDER | t test | N=3 | male | N=1 | female | N=2 |
KARNOFSKY PERFORMANCE SCORE | t test | N=0 | ||||
PATHOLOGY T | Spearman correlation test | N=51 | higher pT | N=40 | lower pT | N=11 |
PATHOLOGY N | Spearman correlation test | N=0 | ||||
PATHOLOGICSPREAD(M) | ANOVA test | N=22 | ||||
TUMOR STAGE | Spearman correlation test | N=33 | higher stage | N=29 | lower stage | N=4 |
Time to Death | Duration (Months) | 1-182.7 (median=21.6) |
censored | N = 44 | |
death | N = 11 | |
Significant markers | N = 0 |
AGE | Mean (SD) | 60.27 (14) |
Significant markers | N = 1 | |
pos. correlated | 1 | |
neg. correlated | 0 |
SpearmanCorr | corrP | Q | |
---|---|---|---|
IGF2BP2 | 0.619 | 4.721e-07 | 0.00814 |
GENDER | Labels | N |
FEMALE | 18 | |
MALE | 40 | |
Significant markers | N = 3 | |
Higher in MALE | 1 | |
Higher in FEMALE | 2 |
T(pos if higher in 'MALE') | ttestP | Q | AUC | |
---|---|---|---|---|
NARFL | -7.15 | 1.997e-09 | 3.44e-05 | 0.8875 |
ATAD5 | 6.47 | 6.841e-07 | 0.0118 | 0.8889 |
CCNYL1 | -6.09 | 2.276e-06 | 0.0392 | 0.8847 |
No gene related to 'KARNOFSKY.PERFORMANCE.SCORE'.
KARNOFSKY.PERFORMANCE.SCORE | Labels | N |
class100 | 5 | |
class90 | 5 | |
Significant markers | N = 0 |
PATHOLOGY.T | Mean (SD) | 1.91 (1) |
N | ||
T1 | 31 | |
T2 | 2 | |
T3 | 24 | |
T4 | 1 | |
Significant markers | N = 51 | |
pos. correlated | 40 | |
neg. correlated | 11 |
SpearmanCorr | corrP | Q | |
---|---|---|---|
DLX6AS | 0.6973 | 1.19e-09 | 2.05e-05 |
GNASAS | -0.6915 | 1.858e-09 | 3.2e-05 |
GP2 | -0.6477 | 3.9e-08 | 0.000673 |
GPR150 | 0.64 | 6.328e-08 | 0.00109 |
PCDHB19P | 0.6368 | 7.7e-08 | 0.00133 |
HBA1 | 0.6368 | 7.716e-08 | 0.00133 |
SLC2A14 | 0.6329 | 9.774e-08 | 0.00169 |
DLEU2 | -0.6307 | 1.118e-07 | 0.00193 |
MATK | 0.6246 | 1.605e-07 | 0.00277 |
NECAB1 | 0.624 | 1.665e-07 | 0.00287 |
PATHOLOGY.N | Mean (SD) | 0.56 (0.7) |
N | ||
N0 | 15 | |
N1 | 9 | |
N2 | 3 | |
Significant markers | N = 0 |
PATHOLOGICSPREAD(M) | Labels | N |
M0 | 37 | |
M1 | 4 | |
MX | 16 | |
Significant markers | N = 22 |
ANOVA_P | Q | |
---|---|---|
RFX7 | 2.125e-11 | 3.67e-07 |
GDPD4 | 7.075e-09 | 0.000122 |
ERCC2 | 4.114e-08 | 0.000709 |
DHDH | 1.266e-07 | 0.00218 |
UNC93A | 1.497e-07 | 0.00258 |
NFE2L1 | 1.929e-07 | 0.00333 |
ZPBP | 2.418e-07 | 0.00417 |
OR10AD1 | 3.672e-07 | 0.00633 |
PCDHA5 | 3.774e-07 | 0.00651 |
TRMT6 | 4.743e-07 | 0.00818 |
TUMOR.STAGE | Mean (SD) | 2.05 (1.2) |
N | ||
Stage 1 | 30 | |
Stage 2 | 1 | |
Stage 3 | 19 | |
Stage 4 | 7 | |
Significant markers | N = 33 | |
pos. correlated | 29 | |
neg. correlated | 4 |
SpearmanCorr | corrP | Q | |
---|---|---|---|
INSM1 | 0.7163 | 3.74e-10 | 6.45e-06 |
ZNF177 | 0.6711 | 1.111e-08 | 0.000192 |
DLX6AS | 0.6708 | 1.133e-08 | 0.000195 |
CNIH3 | 0.6526 | 3.775e-08 | 0.000651 |
MATK | 0.65 | 4.45e-08 | 0.000767 |
NSD1 | 0.6407 | 7.973e-08 | 0.00137 |
TMEM132B | -0.6389 | 8.876e-08 | 0.00153 |
WDR16 | 0.6318 | 1.363e-07 | 0.00235 |
HBA1 | 0.6317 | 1.372e-07 | 0.00236 |
DIO3 | 0.6263 | 1.878e-07 | 0.00324 |
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Expresson data file = KIRP-TP.meth.for_correlation.filtered_data.txt
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Clinical data file = KIRP-TP.clin.merged.picked.txt
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Number of patients = 58
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Number of genes = 17247
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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.
This is an experimental feature. The full results of the analysis summarized in this report can be downloaded from the TCGA Data Coordination Center.