Journal
FRONTIERS IN CARDIOVASCULAR MEDICINE
Volume 9, Issue -, Pages -Publisher
FRONTIERS MEDIA SA
DOI: 10.3389/fcvm.2022.969421
Keywords
scRNA-seq; single-cell; cardiovascular; genomics; web portal; database
Categories
Funding
- National Institutes of Health (NIH)
- Leducq Foundation Transatlantic Network of Excellence (PlaqOmics) Young Investigator Grant [R00HL125912, R01HL14823]
- Netherlands CardioVascular Research Initiative of the Netherlands Heart Foundation
- ERA-CVD program druggable-MI-targets [CVON 2011/B019]
- EU [01KL1802]
- [848146]
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This article introduces PlaqView 2.0, an open-source web portal for exploring and analyzing cardiovascular single-cell datasets. PlaqView 2.0 offers enhanced features and functionalities, including additional cardiovascular single-cell datasets. It brings advanced tools and high-performance computing directly to users without the need for programming knowledge.
Single-cell RNA-seq (scRNA-seq) is a powerful genomics technology to interrogate the cellular composition and behaviors of complex systems. While the number of scRNA-seq datasets and available computational analysis tools have grown exponentially, there are limited systematic data sharing strategies to allow rapid exploration and re-analysis of single-cell datasets, particularly in the cardiovascular field. We previously introduced PlaqView, an open-source web portal for the exploration and analysis of published atherosclerosis single-cell datasets. Now, we introduce PlaqView 2.0 , which provides expanded features and functionalities as well as additional cardiovascular single-cell datasets. We showcase improved PlaqView functionality, backend data processing, user-interface, and capacity. PlaqView brings new or improved tools to explore scRNA-seq data, including gene query, metadata browser, cell identity prediction, ad hoc RNA-trajectory analysis, and drug-gene interaction prediction. PlaqView serves as one of the largest central repositories for cardiovascular single-cell datasets, which now includes data from human aortic aneurysm, gene-specific mouse knockouts, and healthy references. PlaqView 2.0 brings advanced tools and high-performance computing directly to users without the need for any programming knowledge. Lastly, we outline steps to generalize and repurpose PlaqView's framework for single-cell datasets from other fields.
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