title: AnGeLi: A Tool for the Analysis of Gene Lists from Fission Yeast.
abstract: Genome-wide assays and screens typically result in large lists of genes or proteins. Enrichments of functional or other biological properties within such lists can provide valuable insights and testable hypotheses. To systematically detect these enrichments can be challenging and time-consuming, because relevant data to compare against query gene lists are spread over many different sources. We have developed AnGeLi (Analysis of Gene Lists), an intuitive, integrated web-tool for comprehensive and customized interrogation of gene lists from the fission yeast, Schizosaccharomyces pombe. AnGeLi searches for significant enrichments among multiple qualitative and quantitative information sources, including gene and phenotype ontologies, genetic and protein interactions, numerous features of genes, transcripts, translation, and proteins such as copy numbers, chromosomal positions, genetic diversity, RNA polymerase II and ribosome occupancy, localization, conservation, half-lives, domains, and molecular weight among others, as well as diverse sets of genes that are co-regulated or lead to the same phenotypes when mutated. AnGeLi uses robust statistics which can be tailored to specific needs. It also provides the option to upload user-defined gene sets to compare against the query list. Through an integrated data submission form, AnGeLi encourages the community to contribute additional curated gene lists to further increase the usefulness of this resource and to get the most from the ever increasing large-scale experiments. AnGeLi offers a rigorous yet flexible statistical analysis platform for rich insights into functional enrichments and biological context for query gene lists, thus providing a powerful exploratory tool through which S. pombe researchers can uncover fresh perspectives and unexpected connections from genomic data. AnGeLi is freely available at: www.bahlerlab.info/AnGeLi.
authors.affiliation: Research Department of Genetics, Evolution and Environment - UCL Genetics Institute, University College London London, UK.
authors.forename: Danny A
authors.initials: DA
authors.lastname: Bitton
authors.affiliation: Research Department of Genetics, Evolution and Environment - UCL Genetics Institute, University College London London, UK.
authors.forename: Falk
authors.initials: F
authors.lastname: Schubert
authors.affiliation: Research Department of Genetics, Evolution and Environment - UCL Genetics Institute, University College London London, UK.
authors.forename: Shoumit
authors.initials: S
authors.lastname: Dey
authors.affiliation: Scientific IT Services, ETH Zürich Zürich, Switzerland.
authors.forename: Michal
authors.initials: M
authors.lastname: Okoniewski
authors.affiliation: Research Department of Genetics, Evolution and Environment - UCL Genetics Institute, University College London London, UK.
authors.forename: Graeme C
authors.initials: GC
authors.lastname: Smith
authors.affiliation: Research Department of Genetics, Evolution and Environment - UCL Genetics Institute, University College London London, UK.
authors.forename: Sanjay
authors.initials: S
authors.lastname: Khadayate
authors.affiliation: Research Department of Genetics, Evolution and Environment - UCL Genetics Institute, University College London London, UK.
authors.forename: Vera
authors.initials: V
authors.lastname: Pancaldi
authors.affiliation: Cambridge Systems Biology and Department of Biochemistry, University of Cambridge Cambridge, UK.
authors.forename: Valerie
authors.initials: V
authors.lastname: Wood
authors.affiliation: Research Department of Genetics, Evolution and Environment - UCL Genetics Institute, University College London London, UK.
authors.forename: Jürg
authors.initials: J
authors.lastname: Bähler
keywords: PomBase; S. pombe; data mining; database; gene cluster; genetic screen; large-scale assay; ontology