Mathematics, Statistics, and Computer Science
GAW20, DNA methylation, single nucleotide polymorphism, multimarker tests, ascertainment, epigenetics, family data
Background: The rise in popularity and accessibility of DNA methylation data to evaluate epigenetic associations with disease has led to numerous methodological questions. As part of GAW20, our working group of 8 research groups focused on gene searching methods.
Results: Although the methods were varied, we identified 3 main themes within our group. First, many groups tackled the question of how best to use pedigree information in downstream analyses, finding that (a) the use of kinship matrices is common practice, (b) ascertainment corrections may be necessary, and (c) pedigree information may be useful for identifying parent-of-origin effects. Second, many groups also considered multimarker versus single-marker tests. Multimarker tests had modestly improved power versus single-marker methods on simulated data, and on real data identified additional associations that were not identified with single-marker methods, including identification of a gene with a strong biological interpretation. Finally, some of the groups explored methods to combine single-nucleotide polymorphism (SNP) and DNA methylation into a single association analysis.
Conclusions: A causal inference method showed promise at discovering new mechanisms of SNP activity; gene-based methods of summarizing SNP and DNA methylation data also showed promise. Even though numerous questions still remain in the analysis of DNA methylation data, our discussions at GAW20 suggest some emerging best practices.
Source Publication Title
Fuady, Angga M.; Lent, Samantha; Sarnowski, Chloé; and Tintle, Nathan L., "Application of Novel and Existing Methods to Identify Genes with Evidence of Epigenetic Association: Results from GAW20" (2018). Faculty Work Comprehensive List. 1024.