New Coronascape tool will help unlock big-data insights for COVID-19 - Sanford Burnham Prebys
Press Release

New Coronascape tool will help unlock big-data insights for COVID-19

AuthorCommunications
Date

September 15, 2020

Bioinformatics platform simplifies data analysis to help biologists glean scientific insights into the novel coronavirus as body of data surges.

Scientists at Sanford Burnham Prebys Medical Discovery Institute today announced they have released Coronascape (coronascape.org), a customized version of the Metascape bioinformatics platform that removes big-data analysis hurdles for biologists. Coronascape will enable scientists to interpret the growing body of big data related to COVID-19. More than 23,000 papers about COVID-19 have been published since January 2020—and this number continues to rise exponentially. 

“A significant number of publications on SARS-CoV-2 contain large-scale OMICs data, which is not readily interpretable and actionable by many researchers, creating a big-data bottleneck,” says Sumit Chanda, PhD, director of the Immunity and Pathogenesis Program at Sanford Burnham Prebys and senior member of the Metascape team. “Coronascape provides a central clearinghouse for scientists to laser-focus their OMICs analysis and data-mining efforts to find effective drug targets, therapies and vaccines for COVID-19." 

Large-scale studies that map all of the genes, proteins, RNA and more that underlie a biological system—called OMICs studies—are standard tools for a modern biologist. However, interpreting these big-data outputs to generate meaningful, actionable information is far from routine.

“Analyzing results from OMICs studies requires sophisticated tools and highly trained computational scientists,” explains Yingyao Zhou, PhD, director of data science and data engineering at the GNF, and lead architect of the Metascape platform. “These efforts can be costly and time intensive even for experts—taking anywhere from days to weeks to generate actionable information.” 

Metascape was launched in 2019 by scientists at Sanford Burnham Prebys, GNF and UC San Diego. The open-access, web-based portal integrates more than 40 advanced bioinformatics data sources to allow nontechnical users to generate insights in one click. To date, Metascape has facilitated the analysis of large OMICs datasets in more than 1,200 published scientific studies. 

“Metascape provides biologists with a platform from which they can access the power of numerous analytical tools—all within a simple interface—and generate easy-to-interpret reports,” explains Lars Pache, PhD, research assistant professor in the Chanda lab at Sanford Burnham Prebys. “Removing data-analysis barriers for the ever-growing body of SARS-CoV-2 OMICs data released by the worldwide scientific community allows researchers to spend more time on important biological questions surrounding COVID-19, and less time building and troubleshooting a data-analysis workflow.”

“The power of this technology is that you can take a 30,000-foot view of a biological system,” says Christopher Benner, PhD, professor at UC San Diego School of Medicine and Metascape team member. “Our initial analysis of independently derived OMICs datasets for COVID-19 have already identified numerous common threads. When results from scientists in different parts of the world align, then you can start to believe that what you are seeing is true—and move forward.” 

Additional Metascape team members who contributed to the development of Coronascape are Max Chang, PhD, senior bioinformatics programmer in the Benner lab at UC San Diego; and Bin Zhou, PhD, associate director of Data Science, Cheminformatics at GNF; Jun Yin, PhD, director of the bioinformatics core at Sanford Burnham Prebys; and Rabi Murad, PhD, bioinformatics scientist at Sanford Burnham Prebys.

Visual reporting tools such as PowerPoint presentations, Excel documents and additional options can be automatically generated, facilitating the communication of results. Metascape’s data is kept as up-to-date as possible through a two-phase approach that includes automatic crawling of data sources followed by manual quality control. To use Metascape, visit http://metascape.org.