This pipeline uses various statistical tests to identify genes whose promoter methylation levels correlated to selected clinical features.
Testing the association between 19877 genes and 9 clinical features across 127 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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167 genes correlated to 'AGE'.
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KRBA2 , NKX6-1 , BEND6 , DST , SHOX2 , ...
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1 gene correlated to 'NEOPLASM.DISEASESTAGE'.
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ARL4C
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5 genes correlated to 'PATHOLOGY.T.STAGE'.
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CYB561 , C20ORF118 , VEGFA , CCDC90A , RNF125
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3 genes correlated to 'GENDER'.
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ALG11__1 , UTP14C , KIF4B
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2 genes correlated to 'NUMBERPACKYEARSSMOKED'.
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GNA11 , ZFAND1
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1643 genes correlated to 'RACE'.
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LASP1 , TPCN1__1 , CTBP2 , YEATS2 , HOXD11 , ...
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No genes correlated to 'Time to Death', 'PATHOLOGY.N.STAGE', and 'PATHOLOGY.M.STAGE'.
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=167 | older | N=96 | younger | N=71 |
NEOPLASM DISEASESTAGE | Kruskal-Wallis test | N=1 | ||||
PATHOLOGY T STAGE | Spearman correlation test | N=5 | higher stage | N=5 | lower stage | N=0 |
PATHOLOGY N STAGE | Spearman correlation test | N=0 | ||||
PATHOLOGY M STAGE | Kruskal-Wallis test | N=0 | ||||
GENDER | Wilcoxon test | N=3 | male | N=3 | female | N=0 |
NUMBERPACKYEARSSMOKED | Spearman correlation test | N=2 | higher numberpackyearssmoked | N=1 | lower numberpackyearssmoked | N=1 |
RACE | Kruskal-Wallis test | N=1643 |
Time to Death | Duration (Months) | 0-122.1 (median=5.4) |
censored | N = 81 | |
death | N = 38 | |
Significant markers | N = 0 |
AGE | Mean (SD) | 63.64 (13) |
Significant markers | N = 167 | |
pos. correlated | 96 | |
neg. correlated | 71 |
SpearmanCorr | corrP | Q | |
---|---|---|---|
KRBA2 | 0.4938 | 3.644e-09 | 7.24e-05 |
NKX6-1 | 0.4902 | 4.93e-09 | 9.8e-05 |
BEND6 | 0.4629 | 4.247e-08 | 0.000844 |
DST | 0.4629 | 4.247e-08 | 0.000844 |
SHOX2 | 0.4559 | 7.223e-08 | 0.00144 |
WNT2B | 0.4488 | 1.206e-07 | 0.0024 |
NAV1 | 0.4473 | 1.352e-07 | 0.00269 |
ELOVL2 | 0.437 | 2.794e-07 | 0.00555 |
C14ORF132 | 0.4336 | 3.533e-07 | 0.00702 |
GPRC5A | -0.4317 | 4.034e-07 | 0.00801 |
NEOPLASM.DISEASESTAGE | Labels | N |
STAGE I | 7 | |
STAGE IA | 4 | |
STAGE IB | 5 | |
STAGE II | 1 | |
STAGE IIA | 34 | |
STAGE IIB | 22 | |
STAGE III | 16 | |
STAGE IIIA | 8 | |
STAGE IIIB | 6 | |
STAGE IIIC | 4 | |
STAGE IV | 2 | |
STAGE IVA | 1 | |
Significant markers | N = 1 |
PATHOLOGY.T.STAGE | Mean (SD) | 2.39 (0.84) |
N | ||
0 | 1 | |
1 | 20 | |
2 | 30 | |
3 | 60 | |
4 | 3 | |
Significant markers | N = 5 | |
pos. correlated | 5 | |
neg. correlated | 0 |
PATHOLOGY.N.STAGE | Mean (SD) | 0.62 (0.77) |
N | ||
0 | 59 | |
1 | 41 | |
2 | 8 | |
3 | 4 | |
Significant markers | N = 0 |
PATHOLOGY.M.STAGE | Labels | N |
M0 | 90 | |
M1 | 1 | |
M1A | 2 | |
MX | 17 | |
Significant markers | N = 0 |
GENDER | Labels | N |
FEMALE | 18 | |
MALE | 109 | |
Significant markers | N = 3 | |
Higher in MALE | 3 | |
Higher in FEMALE | 0 |
NUMBERPACKYEARSSMOKED | Mean (SD) | 36.68 (21) |
Significant markers | N = 2 | |
pos. correlated | 1 | |
neg. correlated | 1 |
RACE | Labels | N |
ASIAN | 36 | |
BLACK OR AFRICAN AMERICAN | 2 | |
WHITE | 84 | |
Significant markers | N = 1643 |
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Expresson data file = ESCA-TP.meth.by_min_clin_corr.data.txt
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Clinical data file = ESCA-TP.merged_data.txt
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Number of patients = 127
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Number of genes = 19877
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Number of clinical features = 9
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 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 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 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.