The K0MP2 data are a critical resource for biomedical research, will inform human disease studies, be integrated with existing resources and will be accessed, analyzed and mined by mouse biologists, translational researchers, clinicians and wider biomedical community. The MIP2 project will support the K0MP2 project by providing the Data Coordination Centre which will process the complex phenotypic data provide access via a web portal. The DCC aims are to collect and store valid data as it appears throughout the project, to provide unified access to these data for specialist and non specialist users via the web and programmatically, and to support complex queries and statistical analyses. The project has several distinct components and tasks: The Pheno-DCC will validate, perform quality control and manage data acquired dynamically from centres. This will ensure data are robust and allow progress tracking of data at all stages of processing. Specialist data wranglers will manage this process and will interact with the users of the data to ensure user interfaces support the needs of the varied community who will access these data. The statistical and annotation pipelines and environment which will analyze raw data and summarize data for each mutant and assay for presentation to users. A supporting core database, the Core Data Archive, which will store all project data, provide programmatic access, push data to external resources such as NCBI and the Jackson Laboratory and critically provide data for the user interfaces. A single point of entry web portal hosted at www.knockoutmouse.org which will present data to users. I, integrate data from parallel mouse phenotyping projects and provide access to a statistical analysis and query environment Integrate K0MP2 data via biomedical databases at the EBI to ensure that the data are widely distributed to mouse biologists and other scientists .

Public Health Relevance

Research into the lab mouse informs human health by using the mouse as model system for human disease, and as a platform for determining gene function. The MIP2 project will process data generated by studying mutant mice, preserve this data, ensure it is statistically meaningful and integrate it with data generated by clinical studies on humans, and provided it via the web for use by the scientific community.

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
Specialized Center--Cooperative Agreements (U54)
Project #
3U54HG006370-03S1
Application #
8720168
Study Section
Special Emphasis Panel (ZHG1-HGR-M (M2))
Program Officer
Fletcher, Colin F
Project Start
2011-09-16
Project End
2016-07-31
Budget Start
2013-08-01
Budget End
2014-07-31
Support Year
3
Fiscal Year
2013
Total Cost
$436,500
Indirect Cost
$10,203
Name
European Molecular Biology Laboratory
Department
Type
DUNS #
321691735
City
Heidelberg
State
Country
Germany
Zip Code
69117
Meehan, Terrence F; Conte, Nathalie; West, David B et al. (2017) Disease model discovery from 3,328 gene knockouts by The International Mouse Phenotyping Consortium. Nat Genet 49:1231-1238
Bowl, Michael R; Simon, Michelle M; Ingham, Neil J et al. (2017) A large scale hearing loss screen reveals an extensive unexplored genetic landscape for auditory dysfunction. Nat Commun 8:886
Karp, Natasha A; Heller, Ruth; Yaacoby, Shay et al. (2017) Improving the Identification of Phenotypic Abnormalities and Sexual Dimorphism in Mice When Studying Rare Event Categorical Characteristics. Genetics 205:491-501
Oellrich, Anika; Meehan, Terrence F; Parkinson, Helen et al. (2016) Reporting phenotypes in mouse models when considering body size as a potential confounder. J Biomed Semantics 7:2
Smedley, Damian; Schubach, Max; Jacobsen, Julius O B et al. (2016) A Whole-Genome Analysis Framework for Effective Identification of Pathogenic Regulatory Variants in Mendelian Disease. Am J Hum Genet 99:595-606
Dickinson, Mary E; Flenniken, Ann M; Ji, Xiao et al. (2016) High-throughput discovery of novel developmental phenotypes. Nature 537:508-514
Karp, Natasha A; Meehan, Terry F; Morgan, Hugh et al. (2015) Applying the ARRIVE Guidelines to an In Vivo Database. PLoS Biol 13:e1002151
Hodgkins, Alex; Farne, Anna; Perera, Sajith et al. (2015) WGE: a CRISPR database for genome engineering. Bioinformatics 31:3078-80
Groza, Tudor; Köhler, Sebastian; Doelken, Sandra et al. (2015) Automatic concept recognition using the human phenotype ontology reference and test suite corpora. Database (Oxford) 2015:
Kurbatova, Natalja; Mason, Jeremy C; Morgan, Hugh et al. (2015) PhenStat: A Tool Kit for Standardized Analysis of High Throughput Phenotypic Data. PLoS One 10:e0131274

Showing the most recent 10 out of 23 publications