The end point of many different high throughput experiments is a list of interesting genes, often accompanied by metrics such as p-values or fold changes. Making biological sense of these lists can be challenging but is crucial if we are to target the most relevant aspects of biology.

In this course we look at the data sources and analysis techniques which allow us to find the interesting biology behind a set of genes. We look at functional gene set enrichment analysis from both lists of gene names and quantitative data. We consider the choices we get in these techniques, the artefacts and biases which can mislead us, and the options for how to present the results we get.

We run the analyses initially in a web browser, but then also show how to do this in R