Please use this identifier to cite or link to this item: https://hdl.handle.net/11147/12585
Full metadata record
DC FieldValueLanguage
dc.contributor.authorMa, Wei Feng-
dc.contributor.authorTurner, Adam W.-
dc.contributor.authorGancayco, Christina-
dc.contributor.authorWong, Doris-
dc.contributor.authorSong, Yipei-
dc.contributor.authorMosquera, Jose Verdezoto-
dc.contributor.authorAuguste, Gaëlle-
dc.contributor.authorHodonsky, Chani J.-
dc.contributor.authorPrabhakar, Ajay-
dc.contributor.authorEkiz, Hüseyin Atakan-
dc.contributor.authorvan der Laan, Sander W.-
dc.contributor.authorMiller, Clint L.-
dc.date.accessioned2022-10-31T12:20:30Z-
dc.date.available2022-10-31T12:20:30Z-
dc.date.issued2022-08-
dc.identifier.issn2297-055X-
dc.identifier.urihttps://doi.org/10.3389/fcvm.2022.969421-
dc.identifier.urihttps://hdl.handle.net/11147/12585-
dc.descriptionFunding 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).en_US
dc.description.abstractSingle-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.en_US
dc.language.isoenen_US
dc.publisherFrontiers Media S.A.en_US
dc.relation.ispartofFrontiers in Cardiovascular Medicineen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectCardiovascular diseaseen_US
dc.subjectGenomicsen_US
dc.subjectscRNA-seqen_US
dc.subjectPlaqView 2.0en_US
dc.subjectWeb portalen_US
dc.titlePlaqview 2.0: a Comprehensive Web Portal for Cardiovascular Single-Cell Genomicsen_US
dc.typeArticleen_US
dc.authorid0000-0001-7718-6841-
dc.institutionauthorEkiz, Hüseyin Atakan-
dc.departmentİzmir Institute of Technology. Molecular Biology and Geneticsen_US
dc.identifier.wosWOS:000843470900001-
dc.identifier.scopus2-s2.0-85136514402-
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.doi10.3389/fcvm.2022.969421-
dc.identifier.pmid36003902-
dc.relation.issn2297-055Xen_US
dc.description.volume9en_US
dc.identifier.wosqualityQ2-
dc.identifier.scopusqualityQ2-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.languageiso639-1en-
item.openairetypeArticle-
item.grantfulltextopen-
item.fulltextWith Fulltext-
item.cerifentitytypePublications-
crisitem.author.dept04.03. Department of Molecular Biology and Genetics-
Appears in Collections:Molecular Biology and Genetics / Moleküler Biyoloji ve Genetik
PubMed İndeksli Yayınlar Koleksiyonu / PubMed Indexed Publications Collection
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
Files in This Item:
File Description SizeFormat 
fcvm-09-969421.pdfArticle (Makale)5.32 MBAdobe PDFView/Open
Show simple item record



CORE Recommender

SCOPUSTM   
Citations

10
checked on Mar 29, 2025

WEB OF SCIENCETM
Citations

9
checked on Mar 29, 2025

Page view(s)

336
checked on Mar 31, 2025

Download(s)

114
checked on Mar 31, 2025

Google ScholarTM

Check




Altmetric


Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.