Please use this identifier to cite or link to this item: https://hdl.handle.net/11147/12585
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dc.contributor.authorMa, Wei Fengen_US
dc.contributor.authorTurner, Adam W.en_US
dc.contributor.authorGancayco, Christinaen_US
dc.contributor.authorWong, Dorisen_US
dc.contributor.authorSong, Yipeien_US
dc.contributor.authorMosquera, Jose Verdezotoen_US
dc.contributor.authorAuguste, Gaëlleen_US
dc.contributor.authorHodonsky, Chani J.en_US
dc.contributor.authorPrabhakar, Ajayen_US
dc.contributor.authorEkiz, Hüseyin Atakanen_US
dc.contributor.authorvan der Laan, Sander W.en_US
dc.contributor.authorMiller, Clint L.en_US
dc.date.accessioned2022-10-31T12:20:30Z-
dc.date.available2022-10-31T12:20:30Z-
dc.date.issued2022-08-
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.authorid0000-0001-7718-6841en_US
dc.institutionauthorEkiz, Hüseyin Atakanen_US
dc.departmentİzmir Institute of Technology. Molecular Biology and Geneticsen_US
dc.identifier.wosWOS:000843470900001en_US
dc.identifier.scopus2-s2.0-85136514402en_US
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.scopusqualityQ1-
item.fulltextWith Fulltext-
item.grantfulltextopen-
item.openairetypeArticle-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.languageiso639-1en-
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
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