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Phenoclustering: online mining of cross-species phenotypes

Summary: Recently, several methods for analyzing phenotype data have been published, but only few are able to cope with data sets generated in different studies, with different methods, or for different species. We developed an online system in which more than 300 000 phenotypes from a wide variety...

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Detalles Bibliográficos
Autores principales: Groth, Philip, Kalev, Ivan, Kirov, Ivaylo, Traikov, Borislav, Leser, Ulf, Weiss, Bertram
Formato: Texto
Lenguaje:English
Publicado: Oxford University Press 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2905556/
https://www.ncbi.nlm.nih.gov/pubmed/20562418
http://dx.doi.org/10.1093/bioinformatics/btq311
Descripción
Sumario:Summary: Recently, several methods for analyzing phenotype data have been published, but only few are able to cope with data sets generated in different studies, with different methods, or for different species. We developed an online system in which more than 300 000 phenotypes from a wide variety of sources and screening methods can be analyzed together. Clusters of similar phenotypes are visualized as networks of highly similar phenotypes, inducing gene groups useful for functional analysis. This system is part of PhenomicDB, providing the world's largest cross-species phenotype data collection with a tool to mine its wealth of information. Availability: Freely available at http://www.phenomicdb.de Contact: bertram.weiss@bayerhealthcare.com Supplementary information: Supplementary data are available at Bioinformatics online.