Abstract: Modern life science research rarely fits the stereotype of ?one hypothesis, one test,? with definitive testing of simple hypotheses. Data analysis applied to the life sciences often requires the distillation of complex and potentially contradictory data. In this talk, I explore the challenges in making simple and actionable conclusions from research data. I argue that the concept of storytelling in communication of research is a natural extension of the well-established practice of data distillation, a practice that has historically been largely self-taught. I will give examples from my own research and offer thoughts on the future of research communication.

Short Bio: Fred Wright is Goodnight Innovation Distinguished Professor in the Departments of Statistics and Biological Sciences North Carolina State University and Director of the NCSU Bioinformatics Research Center. His interests include expression quantitative trait locus (eQTL) analysis, gene mapping, methodology development in the statistical analysis of expression microarrays, somatic genomics of cancer, and genome-wide association studies. At UNC, he was the Director of the Environmental Bioinformatics Research Center, a $4.5 STAR Center awarded in 2005, that was followed by an unprecedented two additional STAR Centers awarded to his institution. In recent years Dr. Wright has worked to develop methods for pathway analysis, QSAR-based prediction, and investigation of genetic susceptibility. He has actively expanded his interests to now include sequence-based approaches, including analysis of exome sequencing analysis and whole genome sequencing. He is a lead statistician in the International Cystic Fibrosis Gene Modifier Consortium, and PI of an analysis R01 for the GTEx Genotype-Tissue Expression Consortium and of a new NIEHS-funded R01 of the effects of butadiene on Collaborative Cross mice. Dr. Wright is co-investigator and local PI on several additional grants related to computational toxicology, from NIEHS and U.S. EPA.