We've often been asked, why should we use the Human Phenotype Ontology to describe patient phenotypes, rather than a more widely-used clinical vocabulary such as ICD or SNOMED? Here are the answers to some of these frequently asked questions: 1. We should use what other big NIH projects, like ClinVar, are using. ClinVar is using HPO terms to describe phenotypes. This is done in collaboration with MedGen, which has imported HPO terms. Here is an example: http://www.ncbi.nlm.nih.gov/medgen/504827 There are now many bioinformatics tools that use the HPO to empower exome diagnostics. The Monarch team has published two of these recently 1) Exomiser ( Robinson et al., 2014 Genome Res. ) => For discovering new disease genes via model organism data, several successful use cases at UDP and elsewhere 2) PhenIX ( Zemojtel et al., 2014 Science Translational Medicine ) => For clinical diagnostics of “difficult” cases. This paper was on Russ Altman's year in review at AMIA this year. ...

Monarch replied to the 2015 Request for Information  “ Soliciting Input into the Deliberations of the Advisory Committee to the NIH Director (ACD) Working Group on the National Library of Medicine (NLM) ”. The RFI sought input regarding the strategic vision for the NLM to ensure that it remains an international leader in biomedical data and health information.  Below are the Monarch consortium's thoughts. Our comments are primarily informed by our work on the development of information resources in support of translational biomedical informatics. Dr. Melissa Haendel Dr. Peter Robinson Dr. Chris Mungall Dr. Harry Hochheiser Dr. David Eichmann Dr. Michel Dumontier Training The Biomedical Informatics Research Training Program is perhaps the single most valuable contribution to the research community, providing considerable value to all of the NLM’s constituencies. At a time when informatics positions are going unfilled and demand is expected to con...

How to annotate a patient's phenotypic profile using PhenoTips and the Human Phenotype Ontology Purpose We have observed that performance of computational search algorithms within and across species improves if a comprehensive list of phenotypic features is recorded. It is helpful if the person annotating thinks of the set of annotations as a query against all known phenotype profiles. Therefore, the set of phenotypes chosen for the annotation must be as specific as possible, and represent the most salient and important observable phenotypes. Towards this end, Monarch has been asked to provide guidance on how to create a quality patient profile using the Human Phenotype Ontology (HPO). Below we detail our annotation guidelines for use in the PhenoTips application, our partner organization.  The guidelines can also be considered more generically so as to be applicable to any annotation effort using HPO or even using other phenotype ontologies.  The annotations should b...

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 ...