Slim-o-matic: a Semi-Automated Way to Generate Gene Ontology Slims

The Gene Ontology (GO) currently contains over 40,000 terms describing the locations, activities and processes of gene products. Several millions of gene products have been annotated using the GO, and these annotations are routinely used for multiple applications. However, because of the di↵erence of granularity in the annotations, it is useful to summarize GO annotations using GO slims. GO slims contain a subset of the GO terms, providing a higher-level, broader overview of the ontology while abstracting the finer details. Compiling GO slims is a time consuming process relying on manual human expertise, the process of creating the slims is often poorly documented, and maintaining and updating them can be di cult. In this paper, we present a semi-automated way to generate GO slims based on the annotation data available. We applied the tool to two di↵erent use cases, one for data overview in the newly released EBI Metagenomics pipeline, and one for gene-disease enrichment analysis using the DisGeNET platform. The slim-o-matic tool supports choosing the best terms for the slim, ensuring they are representative of the dataset, and have the best coverage using the minimal number of terms.