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ewas-design

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Designs and defends an epigenome-wide association study (EWAS) on 450K/EPIC array or bisulfite methylation - the layer deciding whether a hit is credible. Covers the confounding hierarchy (cell composition covariates as the dominant confounder, batch/Sentrix chip/array position, age/sex, smoking AHRR cg05575921, ancestry/mQTL, reverse causation), chip randomization (no-rescue theorem), surrogate variable analysis sva/SmartSVA, ComBat, RUVm, over-correction, genomic inflation lambda vs GWAS genomic control, BACON bias/inflation, genome-wide significance threshold 450K/EPIC, FWER vs FDR, pwrEWAS power, meta-analysis, EWAS Catalog/Atlas, methylation risk scores. Use when designing an EWAS, choosing a covariate set, randomizing a plate layout, interpreting lambda, applying BACON, setting a threshold, powering a study, or using an MRS. For the per-site test see differential-cpg-testing; for cell fractions see cell-type-deconvolution; for causal mQTL orientation see causal-genomics/mendelia…

When to use

• designing an EWAS
• choosing a covariate set
• randomizing a plate layout
• interpreting lambda
• applying BACON
• setting a threshold
• powering a study
• using an MRS

When not to use

• per-site test
• differential-cpg-testing
• cell fractions
• cell-type-deconvolution
• causal mQTL orientation
• causal-genomics/mendelian-randomization
• normalization internals
• array-preprocessing

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