TY - JOUR T1 - Bio.Ontology - Python tools for enrichment analysis and visualization of ontologies JF - bioRxiv DO - 10.1101/097139 SP - 097139 AU - Kamil Koziara AU - Julia Herman-Izycka AU - Bartek Wilczynski Y1 - 2016/01/01 UR - http://biorxiv.org/content/early/2016/12/28/097139.abstract N2 - Motivation Functional annotation and enrichment analysis based on ontologies has become one of the standard methods of analysis of experimental results. Over the past decade, many methods have been proposed for statistical quantification of enrichment of different functional terms and many implementations of these methods are available. As the popularity of these methods grows, the need for tools facilitating their automation increases.Results We present a complete Python library for statistical enrichment analysis of gene sets and gene rankings compatible with most available biological ontologies. It allows the user to perform all necessary steps: reading the ontologies and gene annotations in multiple formats; performing enrichment analysis using various methods and visualizing the results as readable reports. Importantly, our library includes methods for correcting for multiple hypotheses testing including computation of False Discovery Rates.Availability The library is compatible with recent versions of python interpreter (≥ 2.6 or ≥ 3.3) and is available on github at: https://github.com/regulomics/biopython together with an API documentation and a tutorial. The sample galaxy installation can be found at http://regulomics.mimuw.edu.pl/wp/GO/.Contact bartek{at}mimuw.edu.pl ER -