Leveraging more than $3 million in support from The ALS Association, researchers from UMass Chan Medical School, the National Institutes of Health and Emory University have developed a cloud-based central repository of genetic data related to ALS and frontotemporal dementia (FTD). This repository, called ALS Compute, compiles data from multiple large-scale initiatives into one easily accessible dataset that is far more powerful than any single dataset alone.
Until now, the majority of ALS genetic data in the United States has been collected through six separate whole-genome sequencing (WGS) efforts: Answer ALS, CReATe Consortium, Genomic Translation for ALS Care, New York Genome Center ALS Consortium, National Institutes of Health (NIH) and Project Mine USA. While these efforts have contributed to the discovery of more than 40 genes linked to ALS, the number of researchers able to study ALS genetics has been limited by the need for a high-performance computing infrastructure, large amounts of data storage and significant financial resources.
ALS Compute was founded by John Landers, Ph.D., professor of neurology at UMass Chan Medical School; Bryan Traynor, M.D., Ph.D., senior investigator in the Laboratory of Neurogenetics at the National Institute on Aging; and Jonathan Glass, M.D., professor of neurology and pathology at Emory University School of Medicine.
To date, ALS Compute has consolidated more than 7,400 WGS samples with more to come, including approximately 35,000 control samples. The initial samples, along with tools to help analyze this trove of data, are available via the Terra platform hosted by National Human Genome Research Institute's Genomic Data Science Analysis, Visualization and Informatics Lab-Space (AnVIL).
“Our overall goal for ALS Compute is to increase access to ALS genetic data, especially for researchers in countries or at institutions that do not have the infrastructure to handle such large datasets,” Landers said. “By utilizing the AnVIL platform, we have been able to make both the data and analysis tools cloud-based. So not only have we made the process as simple as possible to access the data, but also eliminated the need for local computing resources to do the analysis. Our hope is that by expanding the number of individuals who work on ALS genetics, more novel discoveries will be made.”
The researchers have received more than $1.6 million in additional funding through the NIH to further this project. During the next phase, they intend to expand the cohort beyond the U.S. to Canada and other countries and incorporate additional annotations and analysis for the genetic variants identified. They also will continue to expand the cloud-based analysis tools available to researchers. Researchers interested in using this data can request access through DbGaP.
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