Experimental evolution is a powerful way to probe the genetic basis of rapid adaptation. However, finding and implementing a computational pipeline for processing and analyzing sequencing data can be difficult for newcomers. We will explore the key concepts of these high-powered experiments, and then together, we will analyze real experimental evolution data generated from our studies of yeast and fruit flies. Students will learn to process raw sequencing data, fit the appropriate statistical models to the data, and visualize the results. Prerequisite: some experience/background in molecular biology, some experience with programming (R or Python)
2 units · Medical Satisfactory/No Credit
Experimental evolution is a powerful way to probe the genetic basis of rapid adaptation. However, finding and implementing a computational pipeline for processing and analyzing sequencing data can be difficult for newcomers. We will explore the key concepts of these high-powered experiments, and then together, we will analyze real experimental evolution data generated from our studies of yeast and fruit flies. Students will learn to process raw sequencing data, fit the appropriate statistical models to the data, and visualize the results. Prerequisite: some experience/background in molecular biology, some experience with programming (R or Python)
Offered in Winter 2027 at Stanford University.