This pipeline uses various statistical tests to identify genes whose promoter methylation levels correlated to selected clinical features.
Testing the association between 16969 genes and 9 clinical features across 35 samples, statistically thresholded by Q value < 0.05, 3 clinical features related to at least one genes.
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131 genes correlated to 'PRIMARY.SITE.OF.DISEASE'.
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HAGH , PCNP , RBPJ , LOC641367 , HIST1H4K , ...
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341 genes correlated to 'HISTOLOGICAL.TYPE'.
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C4ORF38 , PEBP1 , SCNN1G , C4ORF48 , ARPM1 , ...
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36 genes correlated to 'PATHOLOGICSPREAD(M)'.
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THAP11 , LRRC14 , UBL5 , N4BP3 , MAP6D1 , ...
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No genes correlated to 'Time to Death', 'AGE', 'GENDER', 'PATHOLOGY.T', 'PATHOLOGY.N', and 'TUMOR.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=0 | ||||
PRIMARY SITE OF DISEASE | t test | N=131 | rectum | N=51 | colon | N=80 |
GENDER | t test | N=0 | ||||
HISTOLOGICAL TYPE | ANOVA test | N=341 | ||||
PATHOLOGY T | Spearman correlation test | N=0 | ||||
PATHOLOGY N | Spearman correlation test | N=0 | ||||
PATHOLOGICSPREAD(M) | ANOVA test | N=36 | ||||
TUMOR STAGE | Spearman correlation test | N=0 |
Time to Death | Duration (Months) | 1-72.1 (median=15.2) |
censored | N = 27 | |
death | N = 4 | |
Significant markers | N = 0 |
AGE | Mean (SD) | 64.03 (13) |
Significant markers | N = 0 |
PRIMARY.SITE.OF.DISEASE | Labels | N |
COLON | 29 | |
RECTUM | 6 | |
Significant markers | N = 131 | |
Higher in RECTUM | 51 | |
Higher in COLON | 80 |
T(pos if higher in 'RECTUM') | ttestP | Q | AUC | |
---|---|---|---|---|
HAGH | 14.2 | 1.366e-15 | 2.32e-11 | 1 |
PCNP | -20.02 | 8.35e-15 | 1.42e-10 | 1 |
RBPJ | -12.24 | 8.283e-14 | 1.41e-09 | 1 |
LOC641367 | -12.15 | 1.994e-13 | 3.38e-09 | 1 |
HIST1H4K | 16.15 | 8.622e-13 | 1.46e-08 | 1 |
KIAA0430 | -11.17 | 1.306e-12 | 2.22e-08 | 1 |
CENPM | 12.91 | 5.447e-12 | 9.24e-08 | 1 |
LOC644936 | -11.16 | 5.965e-12 | 1.01e-07 | 1 |
PPPDE1 | -18.54 | 6.465e-12 | 1.1e-07 | 1 |
PRKAB1 | -9.92 | 1.994e-11 | 3.38e-07 | 1 |
GENDER | Labels | N |
FEMALE | 19 | |
MALE | 16 | |
Significant markers | N = 0 |
HISTOLOGICAL.TYPE | Labels | N |
COLON ADENOCARCINOMA | 28 | |
COLON MUCINOUS ADENOCARCINOMA | 1 | |
RECTAL ADENOCARCINOMA | 5 | |
RECTAL MUCINOUS ADENOCARCINOMA | 1 | |
Significant markers | N = 341 |
ANOVA_P | Q | |
---|---|---|
C4ORF38 | 2.252e-51 | 3.82e-47 |
PEBP1 | 3.432e-47 | 5.82e-43 |
SCNN1G | 4.429e-46 | 7.52e-42 |
C4ORF48 | 1.095e-43 | 1.86e-39 |
ARPM1 | 1.336e-42 | 2.27e-38 |
CCDC146 | 2.784e-39 | 4.72e-35 |
ACAT2 | 1.773e-32 | 3.01e-28 |
KIAA0141 | 4.199e-31 | 7.12e-27 |
FAM185A | 1.21e-30 | 2.05e-26 |
EXD1 | 1.656e-29 | 2.81e-25 |
PATHOLOGY.T | Mean (SD) | 2.86 (0.73) |
N | ||
T1 | 2 | |
T2 | 6 | |
T3 | 22 | |
T4 | 5 | |
Significant markers | N = 0 |
PATHOLOGY.N | Mean (SD) | 0.46 (0.66) |
N | ||
N0 | 22 | |
N1 | 10 | |
N2 | 3 | |
Significant markers | N = 0 |
PATHOLOGICSPREAD(M) | Labels | N |
M0 | 28 | |
M1 | 5 | |
M1A | 1 | |
Significant markers | N = 36 |
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Expresson data file = COADREAD-TP.meth.for_correlation.filtered_data.txt
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Clinical data file = COADREAD-TP.clin.merged.picked.txt
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Number of patients = 35
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Number of genes = 16969
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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 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.