Correcting for Sample Heterogeneity in Methylome-Wide Association Studies.
Methods in molecular biology, August 2015
Zou, James Y, James Y. Zou
Epigenome-wide association studies (EWAS) face many of the same challenges as genome-wide association studies (GWAS), but have an added challenge in that the epigenome can vary dramatically across cell types. When cell-type composition differs between cases and controls, this leads to spurious associations that may obscure true associations. We have developed a computational method, FaST-LMM-EWASher, which automatically corrects for cell-type composition without needing explicit knowledge of it. In this chapter, we provide a tutorial on using FaST-LMM-EWASher for DNA methylation data and discuss data analysis strategies.
|Readers by professional status||Count||As %|
|Student > Ph. D. Student||2||25%|
|Readers by discipline||Count||As %|
|Agricultural and Biological Sciences||2||25%|
|Biochemistry, Genetics and Molecular Biology||1||13%|
|Medicine and Dentistry||1||13%|