Using ClusterProfiler for determining GO enrichment in clusters

GO analysis involves the use of ontologies to annotate genes based on their biological function, cellular component, and molecular processes. The GO Consortium provides a controlled vocabulary of terms that describe gene function, and these terms are arranged in a hierarchical structure. It aids in the interpretation of high-throughput genomic data, such as microarray and RNA-seq data, by identifying enriched biological themes and pathways among the differentially expressed genes.

In Bioconductor, GO analysis can be performed using various packages such as org.Hs.eg.db, GOstats, and clusterProfiler. These packages allow the user to map gene identifiers to GO terms and perform statistical tests to identify enriched terms in a set of genes.

In this recipe, we will look at how to go from a set of genes in a generic input to assessing them with plots from different GO-related packages.

Getting ready

For this recipe...