Dr. O'Connell was trained in mathematics and computer science before transitioning to genetics and computational biology in 1993. His primary research area has been in human genetics, but expanded to animal genetic since 2007 with a part-time appointment at USDA Animal Improvement Laboratory (AIPL). Primary research focus is developing, implementing and applying methods to analyze genomic data in large pedigree and population data. He works extensively on the analysis of large pedigree data such as the Old Order Amish and Holstein using mixed model methods developed and implemented into MMAP (Mixed Models for Analysis of Pedigree/Populations). MMAP implements a broad selection of analysis options for genome-wide association (GWA) analysis, variance components estimation, linkage analysis, genotype imputation, genomic prediction, haplotyping and mega analysis.