PT  - JOURNAL ARTICLE
AU  - Kamil Koziara
AU  - Julia Herman-Izycka
AU  - Bartek Wilczynski
TI  - Bio.Ontology - Python tools for enrichment analysis and visualization of ontologies
AID  - 10.1101/097139
DP  - 2016 Jan 01
TA  - bioRxiv
PG  - 097139
4099  - http://biorxiv.org/content/early/2016/12/28/097139.short
4100  - http://biorxiv.org/content/early/2016/12/28/097139.full
AB  - 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