(NF1_Any_Mutants cohort)
This pipeline uses various statistical tests to identify genes whose promoter methylation levels correlated to selected clinical features.
Testing the association between 17038 genes and 6 clinical features across 22 samples, statistically thresholded by Q value < 0.05, 2 clinical features related to at least one genes.
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288 genes correlated to 'LYMPH.NODE.METASTASIS'.
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PALM3 , CYP4V2 , INPP5B , ZNF467 , DACT1 , ...
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101 genes correlated to 'NEOPLASM.DISEASESTAGE'.
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TCTEX1D4 , GZF1 , ZIK1 , AKAP13 , MTG1 , ...
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No genes correlated to 'Time to Death', 'AGE', 'PRIMARY.SITE.OF.DISEASE', and 'GENDER'.
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=0 | ||||
PRIMARY SITE OF DISEASE | ANOVA test | N=0 | ||||
GENDER | t test | N=0 | ||||
LYMPH NODE METASTASIS | ANOVA test | N=288 | ||||
NEOPLASM DISEASESTAGE | ANOVA test | N=101 |
Time to Death | Duration (Months) | 0.2-204.6 (median=26.9) |
censored | N = 8 | |
death | N = 14 | |
Significant markers | N = 0 |
AGE | Mean (SD) | 65.41 (15) |
Significant markers | N = 0 |
PRIMARY.SITE.OF.DISEASE | Labels | N |
DISTANT METASTASIS | 6 | |
REGIONAL CUTANEOUS OR SUBCUTANEOUS TISSUE (INCLUDES SATELLITE AND IN-TRANSIT METASTASIS) | 3 | |
REGIONAL LYMPH NODE | 13 | |
Significant markers | N = 0 |
GENDER | Labels | N |
FEMALE | 8 | |
MALE | 14 | |
Significant markers | N = 0 |
LYMPH.NODE.METASTASIS | Labels | N |
N0 | 15 | |
N1B | 3 | |
N2C | 1 | |
N3 | 1 | |
Significant markers | N = 288 |
ANOVA_P | Q | |
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PALM3 | 1.937e-30 | 3.3e-26 |
CYP4V2 | 7.353e-27 | 1.25e-22 |
INPP5B | 7.719e-27 | 1.31e-22 |
ZNF467 | 1.666e-26 | 2.84e-22 |
DACT1 | 2.583e-26 | 4.4e-22 |
TBKBP1 | 2.837e-26 | 4.83e-22 |
ADRB2 | 5.849e-26 | 9.96e-22 |
GAMT | 4.366e-25 | 7.44e-21 |
MYCBPAP | 9.062e-25 | 1.54e-20 |
MTL5 | 9.246e-25 | 1.57e-20 |
NEOPLASM.DISEASESTAGE | Labels | N |
STAGE IA | 2 | |
STAGE IB | 1 | |
STAGE II | 6 | |
STAGE IIB | 3 | |
STAGE IIIB | 2 | |
STAGE IIIC | 3 | |
STAGE IV | 1 | |
Significant markers | N = 101 |
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Expresson data file = SKCM-NF1_Any_Mutants.meth.for_correlation.filtered_data.txt
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Clinical data file = SKCM-NF1_Any_Mutants.clin.merged.picked.txt
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Number of patients = 22
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Number of genes = 17038
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Number of clinical features = 6
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.
This is an experimental feature. The full results of the analysis summarized in this report can be downloaded from the TCGA Data Coordination Center.