title: Gene, Environment and Methylation (GEM): a tool suite to efficiently navigate large scale epigenome wide association studies and integrate genotype and interaction between genotype and environment.
abstract: BACKGROUND
  The interplay among genetic, environment and epigenetic variation is not fully understood. Advances in high-throughput genotyping methods, high-density DNA methylation detection and well-characterized sample collections, enable epigenetic association studies at the genomic and population levels (EWAS). The field has extended to interrogate the interaction of environmental and genetic (GxE) influences on epigenetic variation. Also, the detection of methylation quantitative trait loci (methQTLs) and their association with health status has enhanced our knowledge of epigenetic mechanisms in disease trajectory. However analysis of this type of data brings computational challenges and there are few practical solutions to enable large scale studies in standard computational environments.
  
  
  RESULTS
  GEM is a highly efficient R tool suite for performing epigenome wide association studies (EWAS). GEM provides three major functions named GEM_Emodel, GEM_Gmodel and GEM_GxEmodel to study the interplay of Gene, Environment and Methylation (GEM). Within GEM, the pre-existing "Matrix eQTL" package is utilized and extended to study methylation quantitative trait loci (methQTL) and the interaction of genotype and environment (GxE) to determine DNA methylation variation, using matrix based iterative correlation and memory-efficient data analysis. Benchmarking presented here on a publicly available dataset, demonstrated that GEM can facilitate reliable genome-wide methQTL and GxE analysis on a standard laptop computer within minutes.
  
  
  CONCLUSIONS
  The GEM package facilitates efficient EWAS study in large cohorts. It is written in R code and can be freely downloaded from Bioconductor at https://www.bioconductor.org/packages/GEM/ .
authors.affiliation: Singapore Institute for Clinical Sciences (SICS), Agency for Science Technology and Research (A*STAR), Singapore, 117609, Singapore.|School of Computer Science and Engineering, Nanyang Technological University (NTU), Singapore, 639798, Singapore.
authors.forename: Hong
authors.initials: H
authors.lastname: Pan
authors.affiliation: Singapore Institute for Clinical Sciences (SICS), Agency for Science Technology and Research (A*STAR), Singapore, 117609, Singapore.
authors.forename: Joanna D
authors.initials: JD
authors.lastname: Holbrook
authors.affiliation: Singapore Institute for Clinical Sciences (SICS), Agency for Science Technology and Research (A*STAR), Singapore, 117609, Singapore.|Yong Loo Lin School of Medicine, National University of Singapore (NUS), Singapore, 119228, Singapore.
authors.forename: Neerja
authors.initials: N
authors.lastname: Karnani
authors.affiliation: School of Computer Science and Engineering, Nanyang Technological University (NTU), Singapore, 639798, Singapore. ASCKKWOH@ntu.edu.sg.
authors.forename: Chee Keong
authors.initials: CK
authors.lastname: Kwoh
mesh_terms: D000465:Algorithms; D019175:DNA Methylation; D057890:Epigenomics; D056726:Genetic Association Studies; D023281:Genomics; D005838:Genotype; D020407:Internet; D040641:Quantitative Trait Loci; D014584:User-Computer Interface
keywords: EWAS; GxE; Matrix operation; methQTL