This paper provides details on the necessary steps to assess and control data in genome wide association studies (GWAS) using genotype information on a large number of genetic markers for large number of individuals. Due to varied study designs and genotyping platforms between multiple sites/projects as well as potential genotyping errors, it is important to ensure high quality data. Scripts and directions are provided to facilitate others in this process.
Digital Object Identifier (DOI)
This work was supported by the National Institutes of Health (NIH) National Center for Advancing Translational Science grant KL2TR000116 and the University of Kentucky Center for Computational Sciences.
Zenodo: GWAS: Automated GWAS QC, doi: 10.5281/zenodo.58228.
Ellingson, Sally R. and Fardo, David W., "Automated Quality Control for Genome Wide Association Studies" (2016). Institute for Biomedical Informatics Faculty Publications. 3.