CZ CELLxGENE Discover: A Platform for Single-Cell Data Exploration
Author Information
Author(s): Abdulla Shibla, Aevermann Brian, Assis Pedro, Badajoz Seve, Bell Sidney M, Bezzi Emanuele, Cakir Batuhan, Chaffer Jim, Chambers Signe, Cherry J Michael, Chi Tiffany, Chien Jennifer, Dorman Leah, Garcia-Nieto Pablo, Gloria Nayib, Hastie Mim, Hegeman Daniel, Hilton Jason, Huang Timmy, Infeld Amanda, Istrate Ana-Maria, Jelic Ivana, Katsuya Kuni, Kim Yang Joon, Liang Karen, Lin Mike, Lombardo Maximilian, Marshall Bailey, Martin Bruce, McDade Fran, Megill Colin, Patel Nikhil, Predeus Alexander, Raymor Brian, Robatmili Behnam, Rogers Dave, Rutherford Erica, Sadgat Dana, Shin Andrew, Small Corinn, Smith Trent, Sridharan Prathap, Tarashansky Alexander, Tavares Norbert, Thomas Harley, Tolopko Andrew, Urisko Meghan, Yan Joyce, Yeretssian Garabet, Zamanian Jennifer, Mani Arathi, Cool Jonah, Carr Ambrose
Primary Institution: Chan Zuckerberg Initiative
Conclusion
CZ CELLxGENE Discover provides a comprehensive and standardized platform for exploring and analyzing single-cell transcriptomic data, hosting over 93 million unique cells.
Supporting Evidence
- CZ CELLxGENE hosts a growing corpus of community-contributed data of over 93 million unique cells.
- The platform allows researchers to explore individual datasets and perform cross-corpus analysis.
- CZ CELLxGENE has been adopted as a primary data-sharing platform for various research consortia.
Takeaway
CZ CELLxGENE is like a big library where scientists can find and study tiny cells to learn more about health and diseases.
Methodology
The platform provides curated and interoperable single-cell data, allowing users to explore datasets, perform analyses, and run meta-analyses.
Potential Biases
The data corpus may have biases due to the overrepresentation of certain demographics and diseases.
Limitations
Data from diverse ethnicities and age groups are underrepresented, with a majority coming from adults of European or unknown ethnicity.
Participant Demographics
63% of the cells are from human donors, with 62% from healthy individuals and 38% spanning 132 unique diseases.
Digital Object Identifier (DOI)
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