Database enhances sharing of complex functional genomic data
For the first time, researchers are able to easily share datasets that reveal the function of genomic variants in health and disease—thanks to the launch of a new, open-source database.
Developed by American, Australian and Canadian researchers, the database is the first publicly accessible repository for multiplex assays of variant effect (MAVE) data, used to interpret the results of experiments that systematically measure the impact of thousands of individual sequence variants on a gene’s function.
Previously, MAVE data from experiments has existed in silos. However, MaveDB, which is supported and developed by the University of Washington, the Walter and Eliza Hall Institute of Medical Research and the Brotman Baty Institute, is meant to enhance researchers’ ability to access and interpret complex functional genomic data and yield discoveries into their roles in disease.
“MaveDB makes it easier for scientists to share their datasets in a single location, using a flexible format that is applicable to multiple research fields, and enables other scientists to easily access this data to enhance their research,” says Alan Rubin, bioinformatics researcher at Australia’s Walter and Eliza Hall Institute.
“We’ve also ensured MaveDB can ‘talk’ to other databases to add an extra level of collaborative capacity,” adds Rubin. “For the growing field of MAVE research, this database is an important step towards open science and reproducibility by ensuring data is made available.”
In addition to creating MaveDB, researchers have developed data visualization software—MaveVis—which makes it easier to understand and interpret the results of MAVE experiments.
“MaveVis provides an immediate and consistent display for MAVE data, including valuable annotations such as protein structure information, that will accelerate collaborative research,” according to Rubin.
“We envision that as MaveDB becomes more widely used within the bioinformatics community, other applications will be added that provide new ways to visualize and interpret complex genomics data— leading to new discoveries that enhance biomedical research,” he concludes. “This could underpin the development of new medicines or the understanding of how a patient's genomic variants contribute to a disease.”
MaveDB and MaveVis are described in more detail in an article in the journal Genome Biology.