Microarrays were widely used in the ’00s to interrogate the gene expression of cells in a transcriptome-wide manner. Although the decreasing costs of sequencing has led RNA-seq to become the method of choice for genome-wide transcriptomics, microarrays are still used due to the relative simplicity of analysis. In addition there are many existing data sets using microarrays that are still valuable for analysis. This lesson will introduce you to using analysing gene expression experiments on microarrays using linear models of differential expression.
Prerequisites
The first portion of the lesson assumes a basic knowledge of R, and theoretical knowledge of how gene expression microarray experiments are peformed. The second portion assumes theoretical familiarity with how differentially expressed genes are identified using microarrays.