{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T20:34:12Z","timestamp":1772138052011,"version":"3.50.1"},"reference-count":12,"publisher":"Oxford University Press (OUP)","issue":"9","license":[{"start":{"date-parts":[[2022,3,11]],"date-time":"2022-03-11T00:00:00Z","timestamp":1646956800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"name":"NIH\/NIMH","award":["U01-MH116438"],"award-info":[{"award-number":["U01-MH116438"]}]},{"name":"NIH\/NIMH","award":["R01-MH109907"],"award-info":[{"award-number":["R01-MH109907"]}]},{"name":"NIH\/NIMH","award":["R01-MH123178"],"award-info":[{"award-number":["R01-MH123178"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,4,28]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Summary<\/jats:title>\n                    <jats:p>CellWalkR is an R package that integrates single-cell open chromatin data with cell type labels and bulk epigenetic data to identify cell type-specific regulatory regions. A Graphics Processing Unit (GPU) implementation and downsampling strategies enable thousands of cells to be processed in seconds. CellWalkR\u2019s user-friendly interface provides interactive analysis and visualization of cell labels and regulatory region mappings.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and implementation<\/jats:title>\n                    <jats:p>CellWalkR is freely available as an R package under a GNU GPL-2.0 License and can be accessed from https:\/\/github.com\/PFPrzytycki\/CellWalkR with an accompanying vignette.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Supplementary information<\/jats:title>\n                    <jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btac150","type":"journal-article","created":{"date-parts":[[2022,3,8]],"date-time":"2022-03-08T15:13:57Z","timestamp":1646752437000},"page":"2621-2623","source":"Crossref","is-referenced-by-count":10,"title":["CellWalkR: an R package for integrating and visualizing single-cell and bulk data to resolve regulatory elements"],"prefix":"10.1093","volume":"38","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3360-6936","authenticated-orcid":false,"given":"Pawel F","family":"Przytycki","sequence":"first","affiliation":[{"name":"Gladstone Institutes , San Francisco, CA, USA"}]},{"given":"Katherine S","family":"Pollard","sequence":"additional","affiliation":[{"name":"Gladstone Institutes , San Francisco, CA, USA"},{"name":"Chan Zuckerberg Biohub , San Francisco, CA, USA"},{"name":"Department of Epidemiology and Biostatistics, Institute for Computational Health Sciences, University of California , San Francisco, CA, USA"}]}],"member":"286","published-online":{"date-parts":[[2022,3,11]]},"reference":[{"key":"2023041402565697800_","article-title":"shiny: web application framework for R","author":"Chang","year":"2020"},{"key":"2023041402565697800_","doi-asserted-by":"crossref","first-page":"241","DOI":"10.1186\/s13059-019-1854-5","article-title":"Assessment of computational methods for the analysis of single-cell ATAC-seq data","volume":"20","author":"Chen","year":"2019","journal-title":"Genome Biol"},{"key":"2023041402565697800_","author":"Falbel","year":"2020"},{"key":"2023041402565697800_","doi-asserted-by":"crossref","first-page":"1337","DOI":"10.1038\/s41467-021-21583-9","article-title":"Comprehensive analysis of single cell ATAC-seq data with SnapATAC","volume":"12","author":"Fang","year":"2021","journal-title":"Nat. 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