We have added phenotype data from the International Mouse Phenotyping Consortium , who's goal is to discover functional insight for every mouse gene by generating and systematically phenotyping knockout mouse strains. This initially includes 890 mice affecting 763 genes with 222 unique phenotypes. IMPC data will be updated approximately monthly. IMPC data is presently accessible in the Monarch portal via Mouse gene pages (for example, Stk16 , Gpr107 , or Gpr22 ), or via phenotypic similarity comparison on disease pages (such as Sebastian Syndrome or Susceptibility to Malignant Hyperthermia 3 ). You can read more about our data sources here .

We have added ClinVar variant-disease associations into our database and first released into the Monarch Initiative portal in November, 2014. This new data accompanies previously incorporated ClinVar gene-disease associations (without the specificity of the variations). This initially includes 113,543 SNP, SNV, CNV (and other major rearrangements), linked to 13,591 genes and 11,154 diseases and phenotypes. The associations are also coupled to the original submitters and publications where the variations are reported. The data will be updated approximately monthly. You can read more about our data sources here .

As with most biomedical databases, the first step is to identify relevant data from the research community. The Monarch Initiative is focused primarily on phenotype-related resources. We bring in data associated with those phenotypes so that our users can begin to make connections among other biological entities of interest, such as: genes genotypes gene variants (including SNPs, SNVs, QTLs, CNVs, and other rearrangements big and small) models (including cell lines, animal strains, species, breeds, as well as targeted mutants) pathways orthologs phenotypes publications We import data from a variety of data sources in formats including databases, spreadsheets, delimited text files, XML, JSON, and Web APIs, on a monthly schedule, which is placed into a Postgres database (hosted by the NIF ). Our curation team semantically maps each resource into our data model, primarily using ontologies . This involves both typing relevant columns, mappings between columns (such as be...

Last week, I had the pleasure of teaching at the National Centre for Rare Diseases hosted by the Istituto Superiore di Sanità and Dr. Domenica Taruscio. This rare disease registry course is in its second year, and is focused on exposing the maintainers of rare disease registries various aspects of registry planning and management. I was very impressed with the specific way in which this course was run. The week started with a discussion of the different types of registries (aims, study design, data sources), management sustainability, and clinical outcomes analysis. This was followed by an innovative collaborative learning exercise in the afternoon, where the participants were broken up into three groups. The collaborative learning focused on positive interdependence, individual accountability, face-to-face interaction, group processing and exercise of small-group interpersonal skills - all skills needed to realize a quality registry resource in addition to simply being a quality ...

We'll be heading to American Society for Human Genetics 2014 conference in San Diego, October 18-22. Please check out our work in the following sessions: 170. PhenomeCentral: An integrated portal for sharing patient phenotype and genotype data for rare genetic disorders. Mon Oct 20 5:30p. Concurrent Platform Session C: From Bytes To Phenotypes. Hall B1, Ground Level, Convention Center Michael Brudno will present the new data sharing portal PhenomeCentral , which facilitates the identification of phenotypically similar patients, utilizing the Human Phenotype Ontology (HPO) for linking patient phenotypes. Monarch contributes the API for the Annotation Sufficiency metric, actively develops on the HPO, and has provided user testing and documentation. Cases from our work with the NIH Intramural Undiagnosed Disease Program (UDP) have been deposited into PhenomeCentral. 1499T. Standardized phenotyping enables rapid and accurate prioritization of disease-associated and previou...

This week Monarch team members co-chaired and attended a National Institutes of Environmental Health Science (NIEHS) workshop on Development of a Framework for an Environmental Health Science Language ( agenda & report ). From Love Canal to Chernobyl, from the Clean Water Act to pending regulation of dietary supplements, what we breathe and what we eat is known to contribute to human health outcomes. Consistent capture, transmission, and analysis of these data for comprehensive use in multiple research and clinical environments depends upon standardization and integration of the data across multiple disciplines. Because we need to compare phenotypes based upon both genotypes and environmental variables over time, Monarch is very interested in understanding ways to represent and integrate these data. We currently have a great diversity of model and human environmental data: reagents targeting specific gene products, physiological perturbations such as exposure to light, drug tre...

Today is the first official release of the Monarch Initiative website . After years of research to develop the methods to computationally compare phenotypes across species and facilitate the interpretation of disease-gene associations, we are proud to finally see the fruits of our labor brought to fruition. We now have a portal and widget to search, explore, and compare the phenotypic links between diseases, genes, phenotypes, and animal models. Our modest start includes phenotype data linked to genes and diseases from the following sources: HPO , OMIM , MGI , ZFIN , NCBI Gene , Panther (orthologs), BioGrid (interactions), and KEGG (pathways). Ensuring the integrity of the data, while time-consuming and laborious, is of utmost importance. We will continue to add more sources over time, targeting both large databases, as well as boutiques that cater to very specific data types. Stay tuned for announcements of new data when they are added.

Ongoing research from the Monarch Initiative was presented by Nicole Washington at AMIA Joint Summits on Translational Bioinformatics 2014 . Podium presentation in session TBI19: Phenomic Analysis and Interpretation: Improving the Translation of Model Organism Research into Disease Diagnostics. Summary: In order to determine the underlying mechanism of a disease, animal models can often elucidate the biological underpinnings of the phenotype. We present our findings on the distribution, significance, and information characteristics necessary to enable translation of model organism research into disease diagnostic clinical applications using an ontological approach. TBI Poster presentation on Visualizing clinically similar phenotypes Summary: Numerous tools for exploring diagnoses rely on the ability to compare clinical phenotypes across patients. These inquiries can be further enhanced with comparative phenotypes from animal models. Here we present novel semantic visualization me...