Differential Expression Analysis with limma in R

Functional genomic technologies, such as sequencing and microarrays, can be used by scientists to get unbiased measurements of gene expression at large scale. No matter if you're creating your data from publicly available data sets or creating it, you will need to be able to analyze it. This course will show you how to use R/Bioconductor's flexible package limma to perform differential expression analysis on the most popular experimental designs. Additionally, you will learn how to prepare data, correct batch effects and visual assess results. You can also conduct enrichment testing. After completing this course, you will be able use these strategies for insight into any functional genomes study.