To continue advancing towards our goals of improving patient health via integrated genomic and phenotypic data, the Monarch Initiative has begun two new, exciting collaborations.
Dr. David Osumi-Sutherland and Dr. Helen Parkinson, Head of Molecular Archival Resources at EMBL-EBI, are delighted to announce the beginning of a new collaboration between the EBI and the Monarch Initiative.
This collaboration will focus on integration of systematic phenotyping data from model organisms and biosamples, improvement of patient diagnosis using more deeply integrated model data, and improved rigor of semantic data integration for invertebrates, neural connectivity data, behavior, and molecular phenotypes. The Monarch team has collaborated with Drs. Parkinson and Osumi-Sutherland over many years on a variety of projects such as the International Mouse Phenotyping Consortium and the Global Alliance for Genomics and Health, and we are very excited to have funding from the NIH Office of the Director to support robust collaboration and integration with EBI resources.
Dr. Osumi-Sutherland is an expert in semantic data modeling and has directed and contributed to the Gene Ontology, the Virtual FlyBrain, FlyBase, and many other semantic standards. Dr. Parkinson is a trained geneticist and an expert on bioinformatics, biomedical ontologies, and knowledge engineering. The two will bring their vast experience with ontologies, biomedical data, model organisms, and biological data integration to assist in the development of the Monarch platform for variant prioritization and disease mechanism discovery.
The Monarch Initiative is also proud to announce our selection as a Driver Project for the Global Alliance for Genomics and Health (GA4GH) and their Connect Strategic Plan. GA4GH Connect will impact discovery, analysis, and interpretation of genomic data to enhance responsible sharing of this data by 2020.
Monarch is one of 13 international genomics groups selected as a Driver Project. Driver Projects were sourced from existing initiatives that have been leading genomic medicine research and data analysis and that were actively working with GA4GH in previous engagements. Monarch is thrilled to work closely with GA4GH as a Driver Project! Monarch’s leadership in developing the Human Phenotype Ontology (an IRDiRC recommended resource), the Exomiser variant prioritization tool that leverages cross-species genotype-phenotype data, Phenopackets, the patient-centered phenotyping tool Phenotypr, and their ClinGen/Monarch variant evidence modeling project are all relevant to the various new GA4GH workstreams.
These Projects will focus on creating data sharing frameworks and standards for complex genetic data, with goals of identifying ways to responsibly and securely share genomic data as openly as possible. These new standards and frameworks will advance research, improve clinical management, and lead to the creation of new interoperable tools for data analysis between different groups, communities, and countries. A primary aim is to encourage collaboration so genomic datasets can be used, analyzed, and managed in a way that advances scientific discoveries that will benefit patients with rare and complex diseases.
“Healthcare is harnessing the power of genomics to make better diagnoses and treatment decisions in rare disease and cancer across the world,” said Ewan Birney, Director of EMBL-EBI and Chair of the GA4GH Steering Committee, when discussing GA4GH. “We have a responsibility to enable this future for everyone, and to harness the resulting data for further research on human health and fundamental biology.”
Dr. Melissa Haendel will co-lead the Phenotype and Clinical Capture technical workstream, and Dr. Peter Robinson will direct the Monarch driver project.
The full announcement, here, was unveiled today at the GA4GH 5th Plenary Meeting. Also at this meeting, Monarch PI, Dr. Melissa Haendel presented the Monarch driver project on October 16th. “The Monarch Initiative is ecstatic about our collaborations with EBI and GA4GH. There is a great opportunity to impact human health by building standards and tooling for genomic data interpretation using a wide variety of already available public data sources,” said Dr. Haendel. “These new collaborations and improved data sharing will push us closer to our goal of disease diagnosis and discovery.”