The subject of my talk will be using R and Bioconductor to analyze and visualize RNA-seq data. RNA-seq is a method of measuring expression of all of an organism's genes simultaneously. Bioconductor is a community project to develop and maintain a large set of R packages for the analysis of biological data. I will demonstrate how these packages are used to find differentially expressed genes when comparing bacterial cultures grown on different media. Bioconductor is also used to aid scientific interpretation of the results by finding sets of functionally related genes that are disproportionately affected by different growth conditions and by visualizing differential gene expression on specialized maps that illustrate biological processes.
Yury Bukhman is a scientist in the Computational Biology Core group at the Great Lakes Bioenergy Research Center (GLBRC), University of Wisconsin - Madison. The Center's mission is to to perform the basic research that generates technology to convert cellulosic biomass to ethanol and other advanced biofuels. My role is to perform data analysis and assist in data interpretation of various biological datasets. I also consult and train graduate students, postdocs and staff in the use of statistical and data visualization tools. This talk will be based on a tutorial that I gave at a recent GLBRC Retreat.