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Table 1 GAW20 quality control and statistical models, data sets, and software used by this group

From: Epigenetics, heritability and longitudinal analysis

Contribution Phenotype Normalization h2 Covariates CpG probes Model(s) Software
Almeida et al. [22] HDL Inverse Pre and post fenofibrate HDL and CpG sites 20 PCs Epigenome-wide VC-LME SOLAR
Canty and Paterson [20] TG, QC Probe type strata 4 PCs
Difference in TGs
Epigenome-wide Standard linear model (t-test)  
Fernandez-Rhodes et al. [25] Metabolic syndrome Type II probes Metabolic syndrome, 4 CpG sites age, sex, SNPs, center, smoking, PCs 4 CpG sites VC-LME SOLAR
LeBlanc et al. [21] QC only BMIQ Used breeding values from a heritability model Age, sex, SNPs Epigenome-wide Bayesian LME R-INLA
Lim et al. [23] TG BMIQ   Age, sex, study, center, smoking, 10 PCs 14,850 CpG sites showing LME WGCNA, missmethyl
Nustad et al. [24] TG, HDL BMIQ P-to-e and post fenofibrate, TG HDL and CpG sites Age, sex Epigenome-wide Bayesian LME R-package INLA
Yu et al. [26] TG   Age, sex, study center, smoking status, HDL 349,755 CpG sites GEE R 3.2
  1. All contributions in this group used the GAW20 real data set
  2. BMIQ beta-mixture quantile normalization method for correcting probe design bias, GEE generalized estimating equation, HDL high-density lipoprotein, h2 denotes heritability and indicates if the paper has estimated this quantity, INLA integrated nested Laplace approximation, PC DNA methylation-derived principal component and indicates this study employed PCs as covariates in their analysis, QC quality control, SOLAR sequential oligogenic linkage analysis routines, SNP single-nucleotide polymorphism, TG triglyceride, VC-LME variance component linear mixed effect, WGCNA weighted gene coexpression network analysis
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