{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,15]],"date-time":"2026-05-15T14:37:03Z","timestamp":1778855823725,"version":"3.51.4"},"reference-count":17,"publisher":"Oxford University Press (OUP)","license":[{"start":{"date-parts":[[2022,2,3]],"date-time":"2022-02-03T00:00:00Z","timestamp":1643846400000},"content-version":"vor","delay-in-days":33,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"UofSC Big Data Health Science Center","award":["Pilot Study"],"award-info":[{"award-number":["Pilot Study"]}]},{"name":"NSF XSEDE Startup Allocation","award":["MCB190139"],"award-info":[{"award-number":["MCB190139"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,1,17]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>In recent years, efficient scRNA-seq methods have been developed, enabling the transcriptome profiling of single cells massively in parallel. Meanwhile, its high dimensionality and complexity bring challenges to the data analysis and require extensive collaborations between biologists and bioinformaticians and\/or biostatisticians. The communication between these two units demands a platform for easy data sharing and exploration. Here we developed Single-Cell Transcriptomics Annotated Viewer (SCANNER), as a public web resource for the scientific community, for sharing and analyzing scRNA-seq data in a collaborative manner. It is easy-to-use without requiring special software or extensive coding skills. Moreover, it equipped a real-time database for secure data management and enables an efficient investigation of the activation of gene sets on a single-cell basis. Currently, SCANNER hosts a database of 19 types of cancers and COVID-19, as well as healthy samples from lungs of smokers and non-smokers, human brain cells and peripheral blood mononuclear cells (PBMC). The database will be frequently updated with datasets from new studies. Using SCANNER, we identified a larger proportion of cancer-associated fibroblasts cells and more active fibroblast growth-related genes in melanoma tissues in female patients compared to male patients. Moreover, we found ACE2 is mainly expressed in lung pneumocytes, secretory cells and ciliated cells and differentially expressed in lungs of smokers and never smokers.<\/jats:p>","DOI":"10.1093\/database\/baab086","type":"journal-article","created":{"date-parts":[[2021,12,27]],"date-time":"2021-12-27T20:17:13Z","timestamp":1640636233000},"source":"Crossref","is-referenced-by-count":4,"title":["SCANNER: a web platform for annotation, visualization and sharing of single cell RNA-seq data"],"prefix":"10.1093","volume":"2022","author":[{"given":"Guoshuai","family":"Cai","sequence":"first","affiliation":[{"name":"Department of Environmental Health Sciences, Arnold School of Public health, University of South Carolina , Columbia, SC 29208, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xuanxuan","family":"Yu","sequence":"additional","affiliation":[{"name":"Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina , Columbia, SC 29208, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Choonhan","family":"Youn","sequence":"additional","affiliation":[{"name":"San Diego Supercomputer Center, University of California San Diego , La Jolla, CA 92093, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jun","family":"Zhou","sequence":"additional","affiliation":[{"name":"Research Computing Group, University of South Carolina , Columbia, SC 29208, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1597-4719","authenticated-orcid":false,"given":"Feifei","family":"Xiao","sequence":"additional","affiliation":[{"name":"Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina , Columbia, SC 29208, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2022,1,17]]},"reference":[{"key":"2022063016494130100_R1","doi-asserted-by":"crossref","first-page":"610","DOI":"10.1016\/j.molcel.2015.04.005","article-title":"The technology and biology of single-cell RNA sequencing","volume":"58","author":"Kolodziejczyk","year":"2015","journal-title":"Mol. Cell"},{"key":"2022063016494130100_R2","doi-asserted-by":"crossref","DOI":"10.1038\/s12276-018-0071-8","article-title":"Single-cell RNA sequencing technologies and bioinformatics pipelines","volume":"50","author":"Hwang","year":"2018","journal-title":"Exp. Mol. Med."},{"key":"2022063016494130100_R3","author":"Stewart","year":"2015"},{"key":"2022063016494130100_R4","doi-asserted-by":"crossref","first-page":"62","DOI":"10.1109\/MCSE.2014.80","article-title":"XSEDE: accelerating scientific discovery","volume":"16","author":"Towns","year":"2014","journal-title":"Comput. Sci. Eng."},{"key":"2022063016494130100_R5","doi-asserted-by":"publisher","DOI":"10.1101\/664789.","article-title":"Single Cell Viewer (SCV): an interactive visualization data portal for single cell RNA sequence data","author":"Wang","year":"2019","journal-title":"bioRxiv"},{"key":"2022063016494130100_R6","doi-asserted-by":"crossref","first-page":"2311","DOI":"10.1093\/bioinformatics\/btz877","article-title":"Cerebro: interactive visualization of scRNA-seq data","volume":"36","author":"Hillje","year":"2019","journal-title":"Bioinformatics"},{"key":"2022063016494130100_R7","article-title":"Comparison of visualization tools for single-cell RNAseq data","volume":"2","author":"Cakir","year":"2020","journal-title":"NAR Genom. Bioinform."},{"key":"2022063016494130100_R8","doi-asserted-by":"crossref","DOI":"10.3390\/genes8120368","article-title":"scRNASeqDB: a database for RNA-seq based gene expression profiles in human single cells","volume":"8","author":"Cao","year":"2017","journal-title":"Genes (Basel)"},{"key":"2022063016494130100_R9","doi-asserted-by":"crossref","DOI":"10.1186\/1471-2105-9-559","article-title":"WGCNA: an R package for weighted correlation network analysis","volume":"9","author":"Langfelder","year":"2008","journal-title":"BMC Bioinform."},{"key":"2022063016494130100_R10","doi-asserted-by":"crossref","first-page":"108","DOI":"10.1038\/nature08460","article-title":"Systematic RNA interference reveals that oncogenic KRAS-driven cancers require TBK1","volume":"462","author":"Barbie","year":"2009","journal-title":"Nature"},{"key":"2022063016494130100_R11","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1126\/science.aad0501","article-title":"Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-seq","volume":"352","author":"Tirosh","year":"2016","journal-title":"Science"},{"key":"2022063016494130100_R12","doi-asserted-by":"crossref","first-page":"717","DOI":"10.7150\/jca.10865","article-title":"Perspective of targeting cancer-associated fibroblasts in melanoma","volume":"6","author":"Zhou","year":"2015","journal-title":"J. Cancer"},{"key":"2022063016494130100_R13","doi-asserted-by":"crossref","first-page":"2337","DOI":"10.1200\/JCO.2012.44.5031","article-title":"Sex is an independent prognostic indicator for survival and relapse\/progression-free survival in metastasized stage III to IV melanoma: a pooled analysis of five European organisation for research and treatment of cancer randomized controlled trials","volume":"31","author":"Joosse","year":"2013","journal-title":"J. Clin. Oncol."},{"key":"2022063016494130100_R14","doi-asserted-by":"crossref","first-page":"1016","DOI":"10.1016\/j.cell.2020.04.035","article-title":"SARS-CoV-2 receptor ACE2 is an interferon- stimulated gene in human airway epithelial cells and is detected in specific cell subsets across tissues","volume":"181","author":"Ziegler","year":"2020","journal-title":"Cell"},{"key":"2022063016494130100_R15","doi-asserted-by":"crossref","DOI":"10.1164\/rccm.202003-0693LE","article-title":"Tobacco smoking increases the lung gene expression of ACE2, the receptor of SARS-CoV-2","volume":"201","author":"Cai","year":"2020","journal-title":"Am. J. Respir. Crit. Care Med."},{"key":"2022063016494130100_R16","doi-asserted-by":"crossref","DOI":"10.1186\/s13059-017-1382-0","article-title":"SCANPY: large-scale single-cell gene expression data analysis","volume":"19","author":"Wolf","year":"2018","journal-title":"Genome Biol."},{"key":"2022063016494130100_R17","doi-asserted-by":"crossref","first-page":"1179","DOI":"10.1093\/bioinformatics\/btw777","article-title":"Scater: pre-processing, quality control, normalization and visualization of single-cell RNA-seq data in R","volume":"33","author":"McCarthy","year":"2017","journal-title":"Bioinformatics"}],"container-title":["Database"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/database\/article-pdf\/doi\/10.1093\/database\/baab086\/44349123\/baab086.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/database\/article-pdf\/doi\/10.1093\/database\/baab086\/44349123\/baab086.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,11,14]],"date-time":"2023-11-14T22:15:27Z","timestamp":1700000127000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/database\/article\/doi\/10.1093\/database\/baab086\/6520818"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,1,1]]},"references-count":17,"URL":"https:\/\/doi.org\/10.1093\/database\/baab086","relation":{},"ISSN":["1758-0463"],"issn-type":[{"value":"1758-0463","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2022,1,1]]},"published":{"date-parts":[[2022,1,1]]},"article-number":"baab086"}}