The emergence of novel genetic techniques and the exponential accumulation of genomic data have increased the need for bioinformatics tools.1,2
Biological ontologies facilitate the handling of complex biological data and contribute to the interoperability across multiple data sources.3,4
The Gene Ontology (GO) database summarizes information about the molecular functions, cellular components, and biological processes related to gene products.5
Many tools have been created to search, browse, and analyze the GO database.6
Many of these tools accept only a single gene or GO term as an input, hampering systematic comparisons between GO annotations associated with different GO terms and genes: Complex biological questions that, for example, involve more than one biological process or molecular function cannot be addressed if only one GO term is considered. Similarly, when elucidating a certain biological mechanism, sets of genes rather than single genes are often the focus, raising the need to simultaneously access GO associations of multiple genes. Another limitation in accessing the GO database is that while most programs (eg, EasyGO,7
) produce a short list of significantly enriched GO terms,10,11
they do not allow to query particular GO terms independent of enrichment, which might be of interest if one wants to know which of the genes that are linked to one GO term are associated with a second, user-defined term.
Here we present AGENDA (A
pplication for mining Gen
e Ontology da
ta), a novel web-based application for comparing GO annotations associated with multiple GO terms in different species. The program allows for complex queries using GO Slims17
and Boolean operators. Unlike the programs listed above, with AGENDA it is possible to analyze genes that are annotated to a certain GO term that is defined not by enrichment but by the user. Moreover, using AGENDA, evidences for each annotation can be accessed and the results of the analysis are visualized and can be exported. The usefulness of Boolean operators for mining the GO database had been previously acknowledged.12
Using Boolean operators to refine queries in a step-by-step manner, AGENDA allows to access the GO database in a more flexible manner than was possible before. By combining GO Slims with Boolean Operators, AGENDA facilitates complex queries of GO data in a step-by-step manner whereby the results of each step can be used principally as a starting point for follow-up steps.