EuroPhenome: a repository for high-throughput mouse phenotyping data.
Morgan H,
Beck T,
Blake A,
Gates H,
Adams N,
Debouzy G,
Leblanc S,
Lengger C,
Maier H,
Melvin D,
Meziane H,
Richardson D,
Wells S,
White J,
Wood J;
EUMODIC Consortium,
de Angelis MH,
Brown SD,
Hancock JM,
Mallon AM.
Bosch F, Ruberte J, Ferre T, Pujol A, Otaegui P, Franckhauser S, Marvel J, Queste V, Dacquin R, Djebali S, Jurdic P, Kollias G, Chandras C, Douni E, Aidinis V, Barbacid M, Cañamero M, Dubus P, Balling R, Hauser H, Pasche B, Müller W, Lengeling A, Tocchini-Valentini G, Mandillo S, Golini E, Marazziti D, Deidda G, Rossi N, Matteoni R, Raspa M, Scavizzi F, Rossi N, Matteoni R, Raspa M, Scavizzi F, Butler RH, Di Segni G, Fruscoloni P, Calandra P, Mannironi C, Scarabino D, Tocchini-Valentini GD, Zamboni M, Putti S, Di Pietro C, Gastaldi S, Herault Y, Ryffel B, le Bert M, Pereirea PL, Brault V, Dalloneau E, Pothion S, Rosenthal N, Al Banchaabouchi M, Migliozzi R, Salimova E, de Angelis MH, Gailus-Durner V, Fuchs H, Adler T, Aguilar-Pimentel A, Becker L, Bekeredjian R, Busch DH, Calzada-Wack J, Da Silva-Buttkus P, Esposito I, Favor J, Fleischmann W, Garrett L, Glasl L, Götz A, Graw J, Hans W, Hölter-Koch SM, Ivandic B, Katus HA, Klingenspor M, Klopstock T, Lengger C, Ludwig T, Maier H, Micklich K, Minxuan S, Naton B, Neff F, Ollert M, Puk O, Quintanilla-Fend L, Racz I, Rathkolb B, Rozman J, Schäble KH, Schiller E, Schrewe A, Steinkamp R, Stöger C, Stöger T, Schulz H, Tost M, Treise I, Vogt-Weisenhorn D, Willershäuser M, Wolf E, Wolff-Muscate A, Wurst W, Zeh R, Zimmer A, Mandel JL, Hérault Y, Champy MF, Selloum M, Meziane H, Monassier L, Combe R, Roux M, Ayadi A, Muller S, Bedu E, Becker J, Leblanc S, Sorg T, Vasseur L, Jackson I, Cross S, Joynson R, Jadeja S, Avraham K, Dror A, Shivatzki S, Ballabio A, Diez-Roux G, Brown S, Gates H, Adams N, Atkins S, Beck T, Blake A, Chiev KP, Chouankam A, Cox R, Denny P, Emelyanova I, Fray M, Greenaway S, Hancock J, Hough T, Hunt K, Kendall R, Lee K, Mallon AM, Morgan H, Nolan P, Potter P, Stewart M, Teboul L, Vowell S, Wells S, Wood J, Zaman R, Schofield P, Gruenberger M, Griffin J, Wahli W, Preitner F, Delgado MB, Desvergne B, Michalik L, Bedu E, Neyses L, Cartwright E, Prehar S, Zi M, Ramirez-Solis R, Steel K, White J, Sunter D, Melvin D, Gerdin AK, Igosheva N, Estabel J, Messager S, Karp N, Shannon C, Roberson L, Richardson D, Podrini C, Lucas M.
Source
MRC Harwell, Mammalian Genetics Unit, MRC Harwell, Mary Lyon Centre, Harwell Science and Innovation Campus, Oxfordshire OX11 0RD, UK.
Abstract
The broad aim of biomedical science in the postgenomic era is to link genomic and phenotype information to allow deeper understanding of the processes leading from genomic changes to altered phenotype and disease. The EuroPhenome project (http://www.EuroPhenome.org) is a comprehensive resource for raw and annotated high-throughput phenotyping data arising from projects such as EUMODIC. EUMODIC is gathering data from the EMPReSSslim pipeline (http://www.empress.har.mrc.ac.uk/) which is performed on inbred mouse strains and knock-out lines arising from the EUCOMM project. The EuroPhenome interface allows the user to access the data via the phenotype or genotype. It also allows the user to access the data in a variety of ways, including graphical display, statistical analysis and access to the raw data via web services. The raw phenotyping data captured in EuroPhenome is annotated by an annotation pipeline which automatically identifies statistically different mutants from the appropriate baseline and assigns ontology terms for that specific test. Mutant phenotypes can be quickly identified using two EuroPhenome tools: PhenoMap, a graphical representation of statistically relevant phenotypes, and mining for a mutant using ontology terms. To assist with data definition and cross-database comparisons, phenotype data is annotated using combinations of terms from biological ontologies.
- PMID:
- 19933761
- [PubMed - indexed for MEDLINE]
- PMCID:
- PMC2808931
Free PMC ArticleFigure 1.
This interface shows the results of two queries using the Phenome Data Viewer. (A) The query builder menu on the left-hand side and the results panel on the right which displays a line graph of Blood glucose concentration from the Intraperitoneal glucose tolerance test (IPGTT) procedure performed on inbred mouse strains C57BL/6Ntac and C57BL/6J. (B) The same query builder for mutant data on the left-hand side and on the right, the bar chart graph of HDL-cholesterol for the Mysm-1 mutant.
Nucleic Acids Res. Nucleic Acids Res;38(Database issue):D577-D585.
Figure 3.
This interface shows the EuroPhenome Ontology Tree tool, with the MP ontology tree on the left-hand panel and six mutants on the right-hand panel, that have been identified from the annotation pipeline as having ‘hearing/vestibular/ear phenotypes’. A direct link to the graphical display for the procedures can be accessed from the data column.
Nucleic Acids Res. Nucleic Acids Res;38(Database issue):D577-D585.
Figure 2.
This interface shows the EuroPhenome PhenoMap tool, which is a heatmap representation of statistically significant phenovariants produced from the annotation pipeline. The top panel is an interactive tool to change the phenotyping pipeline (relating to EMPReSS) of interest, the sex, the P range and the effect size. Grey boxes in the map depict a procedure for which we currently do not hold data, the green boxes depict when data is available but no significant annotations were found at the current P-value and effect size. The red boxes show a significant annotation at the current P-value and effect size. Further details on red boxes can be obtained by hovering over the box.
Nucleic Acids Res. Nucleic Acids Res;38(Database issue):D577-D585.
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