  Statistical methods for genomewide association studies (GWAS) continue to
improve. However, the increasing volume and variety of genetic and genomic data
make computational speed and ease of data manipulation mandatory in future
software. In our view, a collaborative effort of statistical geneticists is
required to develop open source software targeted to genetic epidemiology. Our
attempt to meet this need is called the OPENMENDELproject
(https://openmendel.github.io). It aims to (1) enable interactive and
reproducible analyses with informative intermediate results, (2) scale to big
data analytics, (3) embrace parallel and distributed computing, (4) adapt to
rapid hardware evolution, (5) allow cloud computing, (6) allow integration of
varied genetic data types, and (7) foster easy communication between
clinicians, geneticists, statisticians, and computer scientists. This article
reviews and makes recommendations to the genetic epidemiology community in the
context of the OPENMENDEL project.
