This pipeline uses various statistical tests to identify genes whose promoter methylation levels correlated to selected clinical features.
Testing the association between 19682 genes and 9 clinical features across 151 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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67 genes correlated to 'AGE'.
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NKX6-1 , BEND6 , DST , KRBA2 , SYT8 , ...
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2 genes correlated to 'NEOPLASM.DISEASESTAGE'.
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TUSC3 , CLDN18
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1 gene correlated to 'PATHOLOGY.T.STAGE'.
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RNF125
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1 gene correlated to 'GENDER'.
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KIF4B
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4 genes correlated to 'NUMBERPACKYEARSSMOKED'.
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KLK10 , TENC1 , MAP3K14 , LEKR1
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1438 genes correlated to 'RACE'.
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SCAMP5 , YEATS2 , LASP1 , KCNK13 , CTBP2 , ...
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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 | ||
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Time to Death | Cox regression test | N=0 | ||||
AGE | Spearman correlation test | N=67 | older | N=41 | younger | N=26 |
NEOPLASM DISEASESTAGE | Kruskal-Wallis test | N=2 | ||||
PATHOLOGY T STAGE | Spearman correlation test | N=1 | higher stage | N=1 | lower stage | N=0 |
PATHOLOGY N STAGE | Spearman correlation test | N=0 | ||||
PATHOLOGY M STAGE | Kruskal-Wallis test | N=0 | ||||
GENDER | Wilcoxon test | N=1 | male | N=1 | female | N=0 |
NUMBERPACKYEARSSMOKED | Spearman correlation test | N=4 | higher numberpackyearssmoked | N=2 | lower numberpackyearssmoked | N=2 |
RACE | Kruskal-Wallis test | N=1438 |
Time to Death | Duration (Months) | 0-122.1 (median=7.6) |
censored | N = 88 | |
death | N = 55 | |
Significant markers | N = 0 |
AGE | Mean (SD) | 63.26 (12) |
Significant markers | N = 67 | |
pos. correlated | 41 | |
neg. correlated | 26 |
SpearmanCorr | corrP | Q | |
---|---|---|---|
NKX6-1 | 0.4365 | 2.109e-08 | 0.000415 |
BEND6 | 0.417 | 1.001e-07 | 0.00197 |
DST | 0.417 | 1.001e-07 | 0.00197 |
KRBA2 | 0.4121 | 1.461e-07 | 0.00287 |
SYT8 | -0.402 | 3.114e-07 | 0.00613 |
YEATS2 | 0.3876 | 8.816e-07 | 0.0173 |
GALNTL4 | 0.3874 | 8.936e-07 | 0.0176 |
PTPLB | 0.3866 | 9.429e-07 | 0.0186 |
SYT14 | 0.3855 | 1.016e-06 | 0.02 |
CIZ1__1 | 0.3826 | 1.243e-06 | 0.0245 |
NEOPLASM.DISEASESTAGE | Labels | N |
STAGE I | 8 | |
STAGE IA | 4 | |
STAGE IB | 6 | |
STAGE II | 1 | |
STAGE IIA | 35 | |
STAGE IIB | 26 | |
STAGE III | 24 | |
STAGE IIIA | 11 | |
STAGE IIIB | 8 | |
STAGE IIIC | 6 | |
STAGE IV | 3 | |
STAGE IVA | 2 | |
Significant markers | N = 2 |
PATHOLOGY.T.STAGE | Mean (SD) | 2.41 (0.84) |
N | ||
0 | 1 | |
1 | 25 | |
2 | 33 | |
3 | 75 | |
4 | 4 | |
Significant markers | N = 1 | |
pos. correlated | 1 | |
neg. correlated | 0 |
PATHOLOGY.N.STAGE | Mean (SD) | 0.7 (0.8) |
N | ||
0 | 64 | |
1 | 55 | |
2 | 11 | |
3 | 6 | |
Significant markers | N = 0 |
PATHOLOGY.M.STAGE | Labels | N |
M0 | 112 | |
M1 | 2 | |
M1A | 3 | |
MX | 17 | |
Significant markers | N = 0 |
GENDER | Labels | N |
FEMALE | 21 | |
MALE | 130 | |
Significant markers | N = 1 | |
Higher in MALE | 1 | |
Higher in FEMALE | 0 |
NUMBERPACKYEARSSMOKED | Mean (SD) | 35.24 (21) |
Significant markers | N = 4 | |
pos. correlated | 2 | |
neg. correlated | 2 |
RACE | Labels | N |
ASIAN | 38 | |
BLACK OR AFRICAN AMERICAN | 2 | |
WHITE | 93 | |
Significant markers | N = 1438 |
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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 = 151
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Number of genes = 19682
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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.