(primary solid tumor cohort)
This pipeline uses various statistical tests to identify genes whose promoter methylation levels correlated to selected clinical features.
Testing the association between 17179 genes and 8 clinical features across 48 samples, statistically thresholded by Q value < 0.05, 3 clinical features related to at least one genes.
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2 genes correlated to 'PATHOLOGY.N'.
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GTF2H1 , ELAVL1
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28 genes correlated to 'PATHOLOGICSPREAD(M)'.
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C17ORF101 , ATXN7 , PRNP , SIX4 , KCNJ3 , ...
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11 genes correlated to 'COMPLETENESS.OF.RESECTION'.
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C1ORF59 , TNFRSF11B , CHID1 , TUBGCP5 , ALG12 , ...
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No genes correlated to 'AGE', 'GENDER', 'PATHOLOGY.T', 'TUMOR.STAGE', and 'NUMBER.OF.LYMPH.NODES'.
Complete statistical result table is provided in Supplement Table 1
Clinical feature | Statistical test | Significant genes | Associated with | Associated with | ||
---|---|---|---|---|---|---|
AGE | Spearman correlation test | N=0 | ||||
GENDER | t test | N=0 | ||||
PATHOLOGY T | Spearman correlation test | N=0 | ||||
PATHOLOGY N | Spearman correlation test | N=2 | higher pN | N=2 | lower pN | N=0 |
PATHOLOGICSPREAD(M) | ANOVA test | N=28 | ||||
TUMOR STAGE | Spearman correlation test | N=0 | ||||
COMPLETENESS OF RESECTION | ANOVA test | N=11 | ||||
NUMBER OF LYMPH NODES | Spearman correlation test | N=0 |
AGE | Mean (SD) | 63 (12) |
Significant markers | N = 0 |
GENDER | Labels | N |
FEMALE | 21 | |
MALE | 27 | |
Significant markers | N = 0 |
PATHOLOGY.T | Mean (SD) | 2.83 (0.75) |
N | ||
T1 | 3 | |
T2 | 9 | |
T3 | 29 | |
T4 | 7 | |
Significant markers | N = 0 |
PATHOLOGY.N | Mean (SD) | 0.7 (0.84) |
N | ||
N0 | 25 | |
N1 | 10 | |
N2 | 11 | |
Significant markers | N = 2 | |
pos. correlated | 2 | |
neg. correlated | 0 |
PATHOLOGICSPREAD(M) | Labels | N |
M0 | 34 | |
M1 | 4 | |
M1A | 1 | |
MX | 9 | |
Significant markers | N = 28 |
ANOVA_P | Q | |
---|---|---|
C17ORF101 | 6.707e-25 | 1.15e-20 |
ATXN7 | 9.753e-23 | 1.68e-18 |
PRNP | 4.572e-19 | 7.85e-15 |
SIX4 | 8.941e-13 | 1.54e-08 |
KCNJ3 | 3.005e-12 | 5.16e-08 |
NUDT19 | 1.008e-11 | 1.73e-07 |
DEAF1 | 1.409e-11 | 2.42e-07 |
KLRC2 | 1.99e-11 | 3.42e-07 |
ZNF501 | 2.916e-11 | 5.01e-07 |
SLC25A22 | 1.816e-10 | 3.12e-06 |
TUMOR.STAGE | Mean (SD) | 2.41 (1) |
N | ||
Stage 1 | 10 | |
Stage 2 | 14 | |
Stage 3 | 15 | |
Stage 4 | 7 | |
Significant markers | N = 0 |
COMPLETENESS.OF.RESECTION | Labels | N |
R0 | 32 | |
R1 | 1 | |
RX | 3 | |
Significant markers | N = 11 |
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Expresson data file = READ-TP.meth.for_correlation.filtered_data.txt
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Clinical data file = READ-TP.clin.merged.picked.txt
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Number of patients = 48
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Number of genes = 17179
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Number of clinical features = 8
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.