As of June 2021, the ongoing COVID-19 pandemic has resulted in over 170 million confirmed COVID-19 cases and 3.7 million deaths globally.
Understanding the molecular mechanisms of COVID-19 pathogenesis, as well as the immune-cell subsets and molecular factors associated with protective or pathological immunity against SARS-CoV-2, the virus that causes COVID-19, could greatly aid the development of vaccines and therapeutics.
Single-cell technologies such as flow cytometry, mass cytometry, single-cell transcriptomics and single-cell multi-omic profiling offer unprecedented potential to dissect immune-response heterogeneity among individual cells. These technologies are being used to analyze COVID-19 at an astounding pace.
While there are many valuable COVID-19 datasets in the public domain, they must be acquired and standardized before researchers can use them to answer basic questions about the disease. The high-dimensional nature of these datasets also makes it difficult to translate the raw data into a visually comprehensible display that facilitates scientific discovery.
To enable the rapid exploration of multiple COVID-19 datasets, the Hutch Data Core partnered with Hutch computational biologists Drs. Yuan Tian and Raphael Gottardo to create the Fred Hutchinson COVID-19 Cell Atlas, an online resource for data visualization, exploration and discovery.
The individual COVID-19 Cell Atlases (one for each dataset, which merge into a unified Atlas) are built on the PubWeb platform, a collection of interoperable, open-source technologies that enable the analysis and dissemination of research data.
Key components of this platform include: