Lummei Analytics LLC was founded in 2016 by two academic researchers, Dan Garrigan and Sarah Kingan. Our goal is to increase the productivity of your research program with large-scale genomic analysis and custom resource development. In an era characterized by abundant data but dwindling funding we can help you accomplish tasks at a fraction of the time and cost it would normally take a postdoc or graduate student.


Daniel Garrigan

Dan Garrigan

Dan Garrigan is an Assistant Professor of Biology at the University of Rochester and the co-founder of Lummei Analytics. He holds a Ph.D. from Arizona State University (advisor, Philip Hedrick) and B.S. from the University of Washington  (advisor, Scott Edwards). Dan did postdoctoral training with Michael Hammer at the University of Arizona and John Wakeley and Richard Lewontin at Harvard University. Dan has worked on many genomic systems, from Drosophila speciation, to human population genetics, to MHC evolution in vertebrates, often developing innovative computational methods to address complex biological questions. At Lummei Analytics, Dan serves as the head programmer, database developer, and computer systems administrator. He automates large-scale NGS analysis, performs simulations, and conducts statistical analyses.


Sarah Kingan

Sarah Kingan

Sarah Kingan is a Research Associate in the Biology Department at University of Rochester and co-founder of Lummei Analytics. She holds a Ph.D. from Harvard University (advisor, Dan Hartl) and B.S. in Biology from Brown University (advisors, David Rand and Marc Tatar). She did postdoctoral training with Daven Presgraves at the University of Rochester. Sarah got her start working on classical and population genetics of Drosophila, humans, and primates and in her postdoctoral work has focused on computational approaches to comparative and population genomic questions. As Lummei’s head bioinformatician, Sarah handles expression analysis, genome annotation, comparative and population genomic analyses, statistical analysis, and data visualization.