BACKGROUND: Systematic, high-throughput studies of mouse phenotypes have been hampered by the inability to analyze individual animal data from a multitude of sources in an integrated manner. Studies generally make comparisons at the level of genotype or treatment thereby excluding associations that may be subtle or involve compound phenotypes. Additionally, the lack of integrated, standardized ontologies and methodologies for data exchange has inhibited scientific collaboration and discovery. RESULTS: Here we introduce a Mouse Phenotype Analysis System (MPHASYS), a platform for integrating data generated by studies of mouse models of human biology and disease such as aging and cancer. This computational platform is designed to provide a standardized methodology for working with animal data; a framework for data entry, analysis and sharing; and ontologies and methodologies for ensuring accurate data capture. We describe the tools that currently comprise MPHASYS, primarily ones related to mouse pathology, and outline its use in a study of individual animal-specific patterns of multiple pathology in mice harboring a specific germline mutation in the DNA repair and transcription-specific gene Xpd. CONCLUSION: MPHASYS is a system for analyzing multiple data types from individual animals. It provides a framework for developing data analysis applications, and tools for collecting and distributing high-quality data. The software is platform independent and freely available under an open-source license 1.
BACKGROUND: Systematic, high-throughput studies of mouse phenotypes have been hampered by the inability to analyze individual animal data from a multitude of sources in an integrated manner. Studies generally make comparisons at the level of genotype or treatment thereby excluding associations that may be subtle or involve compound phenotypes. Additionally, the lack of integrated, standardized ontologies and methodologies for data exchange has inhibited scientific collaboration and discovery. RESULTS: Here we introduce a Mouse Phenotype Analysis System (MPHASYS), a platform for integrating data generated by studies of mouse models of human biology and disease such as aging and cancer. This computational platform is designed to provide a standardized methodology for working with animal data; a framework for data entry, analysis and sharing; and ontologies and methodologies for ensuring accurate data capture. We describe the tools that currently comprise MPHASYS, primarily ones related to mouse pathology, and outline its use in a study of individual animal-specific patterns of multiple pathology in mice harboring a specific germline mutation in the DNA repair and transcription-specific gene Xpd. CONCLUSION: MPHASYS is a system for analyzing multiple data types from individual animals. It provides a framework for developing data analysis applications, and tools for collecting and distributing high-quality data. The software is platform independent and freely available under an open-source license 1.
Authors: Susan W P Wijnhoven; Rudolf B Beems; Marianne Roodbergen; Jolanda van den Berg; Paul H M Lohman; Karin Diderich; Gijsbertus T J van der Horst; Jan Vijg; Jan H J Hoeijmakers; Harry van Steeg Journal: DNA Repair (Amst) Date: 2005-08-22
Authors: Janan T Eppig; Carol J Bult; James A Kadin; Joel E Richardson; Judith A Blake; A Anagnostopoulos; R M Baldarelli; M Baya; J S Beal; S M Bello; W J Boddy; D W Bradt; D L Burkart; N E Butler; J Campbell; M A Cassell; L E Corbani; S L Cousins; D J Dahmen; H Dene; A D Diehl; H J Drabkin; K S Frazer; P Frost; L H Glass; C W Goldsmith; P L Grant; M Lennon-Pierce; J Lewis; I Lu; L J Maltais; M McAndrews-Hill; L McClellan; D B Miers; L A Miller; L Ni; J E Ormsby; D Qi; T B K Reddy; D J Reed; B Richards-Smith; D R Shaw; R Sinclair; C L Smith; P Szauter; M B Walker; D O Walton; L L Washburn; I T Witham; Y Zhu Journal: Nucleic Acids Res Date: 2005-01-01 Impact factor: 16.971
Authors: C Zhang; O Crasta; S Cammer; R Will; R Kenyon; D Sullivan; Q Yu; W Sun; R Jha; D Liu; T Xue; Y Zhang; M Moore; P McGarvey; H Huang; Y Chen; J Zhang; R Mazumder; C Wu; B Sobral Journal: Nucleic Acids Res Date: 2007-11-04 Impact factor: 16.971