Dr. Daryl Gohl on Improving the Accuracy and Reproducibility of Genomics Measurements

Dr. Daryl Gohl, from the UMGC’s Innovation Lab, will be a speaker at the “Questions About Reproducibility in an Age of Big Data'' virtual conference, where he will discuss efforts at the UMGC to detect and dissect biases in the process of generating next-generation sequencing data and to improve the accuracy and reproducibility of genomics measurements.

Abstract
With the advent of next-generation DNA sequencing technologies, the generation of genomic data continues to grow exponentially. The use of genomic data spans every field in biology, informing research in biomedicine, agriculture, evolution and ecology, neuroscience, and many other disciplines. Genomics measurements are susceptible to error and bias at essentially every step of the data generation and analysis workflows. Given these challenges, accurate and reproducible data generation requires optimized wet lab and analysis methods and appropriate controls to monitor and report on errors and bias. I will describe efforts in the University of Minnesota Genomics Center to detect and dissect biases in the process of generating next-generation sequencing data and to improve the accuracy and reproducibility of genomics measurements. 

Dr. Gohl’s talk will be Friday, May 7th at 11:00 AM (CT).

This 3-day event is hosted by the University of Minnesota's Institute for Research in Statistics and its Applications and the Minnesota Center for Philosophy of Science. Please see the conference's website for the full agenda and to register. Registration has been extended to May 5th.