TY - JOUR
T1 - PlaqView 2.0
T2 - A comprehensive web portal for cardiovascular single-cell genomics
AU - Ma, Wei Feng
AU - Turner, Adam W
AU - Gancayco, Christina
AU - Wong, Doris
AU - Song, Yipei
AU - Mosquera, Jose Verdezoto
AU - Auguste, Gaëlle
AU - Hodonsky, Chani J
AU - Prabhakar, Ajay
AU - Ekiz, H Atakan
AU - van der Laan, Sander W
AU - Miller, Clint L
N1 - Funding Information:
Funding for this research was provided by National Institutes of Health (NIH) grants R00HL125912 and R01HL14823, a Leducq Foundation Transatlantic Network of Excellence (PlaqOmics) Young Investigator Grant, Netherlands CardioVascular Research Initiative of the Netherlands Heart Foundation (CVON 2011/B019 and CVON 2017-20: Generating the best evidence-based pharmaceutical targets for atherosclerosis [GENIUS I&II]), and the ERA-CVD program druggable-MI-targets (grant number: 01KL1802). SL was funded through EU H2020 TO_AITION (grant number: 848146).
Publisher Copyright:
Copyright © 2022 Ma, Turner, Gancayco, Wong, Song, Mosquera, Auguste, Hodonsky, Prabhakar, Ekiz, van der Laan and Miller.
PY - 2022/8/8
Y1 - 2022/8/8
N2 - 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 (www.plaqview.com), 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.
AB - 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 (www.plaqview.com), 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.
KW - cardiovascular
KW - database
KW - genomics
KW - scRNA-seq
KW - single-cell
KW - web portal
UR - https://www.scopus.com/pages/publications/85136514402
U2 - 10.3389/fcvm.2022.969421
DO - 10.3389/fcvm.2022.969421
M3 - Article
C2 - 36003902
SN - 2297-055X
VL - 9
JO - Frontiers in cardiovascular medicine
JF - Frontiers in cardiovascular medicine
M1 - 969421
ER -