{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,28]],"date-time":"2026-01-28T13:44:58Z","timestamp":1769607898450,"version":"3.49.0"},"reference-count":22,"publisher":"Oxford University Press (OUP)","issue":"12","license":[{"start":{"date-parts":[[2020,4,23]],"date-time":"2020-04-23T00:00:00Z","timestamp":1587600000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"name":"Karolinska Institutet & AstraZeneca Integrated Cardio Metabolic Centre"},{"name":"Fondation Leducq \u2013 Transantlantic PlaqOmics Network"},{"name":"Hj\u00e4rt- och Lungfonden","award":["20170265"],"award-info":[{"award-number":["20170265"]}]},{"DOI":"10.13039\/501100004359","name":"Vetenskapsr\u00e5det","doi-asserted-by":"publisher","award":["2018-02529"],"award-info":[{"award-number":["2018-02529"]}],"id":[{"id":"10.13039\/501100004359","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,6,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Summary<\/jats:title>\n                  <jats:p>Single-cell RNA sequencing (scRNA-seq) is a technology to measure gene expression in single cells. It has enabled discovery of new cell types and established cell type atlases of tissues and organs. The widespread adoption of scRNA-seq has created a need for user-friendly software for data analysis. We have developed a web server, alona that incorporates several of the most popular single-cell analysis algorithms into a flexible pipeline. alona can perform quality filtering, normalization, batch correction, clustering, cell type annotation and differential gene expression analysis. Data are visualized in the web browser using an interface based on JavaScript, allowing the user to query genes of interest and visualize the cluster structure. alona accepts a compressed gene expression matrix and identifies cell clusters with a graph-based clustering strategy. Cell types are identified from a comprehensive collection of marker genes or by specifying a custom set of marker genes.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and implementation<\/jats:title>\n                  <jats:p>The service runs at https:\/\/alona.panglaodb.se and the Python package can be downloaded from https:\/\/oscar-franzen.github.io\/adobo\/.<\/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\/btaa269","type":"journal-article","created":{"date-parts":[[2020,4,16]],"date-time":"2020-04-16T11:10:23Z","timestamp":1587035423000},"page":"3910-3912","source":"Crossref","is-referenced-by-count":37,"title":["alona: a web server for single-cell RNA-seq analysis"],"prefix":"10.1093","volume":"36","author":[{"given":"Oscar","family":"Franz\u00e9n","sequence":"first","affiliation":[{"name":"Department of Medicine , Integrated Cardio Metabolic Centre, Karolinska Institutet, Huddinge 14157, Sweden"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Johan L M","family":"Bj\u00f6rkegren","sequence":"additional","affiliation":[{"name":"Department of Medicine , Integrated Cardio Metabolic Centre, Karolinska Institutet, Huddinge 14157, Sweden"},{"name":"Department of Genetics and Genomic Sciences , Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2020,4,23]]},"reference":[{"key":"2023063011482089500_btaa269-B1","doi-asserted-by":"crossref","first-page":"2865","DOI":"10.1093\/bioinformatics\/bty1044","article-title":"M3Drop: dropout-based feature selection for scRNASeq","volume":"35","author":"Andrews","year":"2019","journal-title":"Bioinformatics"},{"key":"2023063011482089500_btaa269-B2","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1137\/04060593X","article-title":"Augmented implicitly restarted lanczos bidiagonalization methods","volume":"27","author":"Baglama","year":"2005","journal-title":"SIAM J. Sci. Comput"},{"key":"2023063011482089500_btaa269-B3","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1038\/nbt.4314","article-title":"Dimensionality reduction for visualizing single-cell data using UMAP","volume":"37","author":"Becht","year":"2019","journal-title":"Nat. Biotechnol"},{"key":"2023063011482089500_btaa269-B4","doi-asserted-by":"crossref","first-page":"258","DOI":"10.1186\/1471-2105-12-258","article-title":"Cell subset prediction for blood genomic studies","volume":"12","author":"Bolen","year":"2011","journal-title":"BMC Bioinformatics"},{"key":"2023063011482089500_btaa269-B5","doi-asserted-by":"crossref","first-page":"1093","DOI":"10.1038\/nmeth.2645","article-title":"Accounting for technical noise in single-cell RNA-seq experiments","volume":"10","author":"Brennecke","year":"2013","journal-title":"Nat. Methods"},{"key":"2023063011482089500_btaa269-B6","doi-asserted-by":"crossref","first-page":"411","DOI":"10.1038\/nbt.4096","article-title":"Integrating single-cell transcriptomic data across different conditions, technologies, and species","volume":"36","author":"Butler","year":"2018","journal-title":"Nat. Biotechnol"},{"key":"2023063011482089500_btaa269-B7","doi-asserted-by":"crossref","first-page":"508","DOI":"10.1186\/s12864-016-2897-6","article-title":"Detection of high variability in gene expression from single-cell RNA-seq profiling","volume":"17","author":"Chen","year":"2016","journal-title":"BMC Genomics"},{"key":"2023063011482089500_btaa269-B8","doi-asserted-by":"crossref","first-page":"676","DOI":"10.1186\/s12864-019-6053-y","article-title":"Single Cell Explorer, collaboration-driven tools to leverage large-scale single cell RNA-seq data","volume":"20","author":"Feng","year":"2019","journal-title":"BMC Genomics"},{"key":"2023063011482089500_btaa269-B9","doi-asserted-by":"crossref","DOI":"10.1093\/database\/baz046","article-title":"PanglaoDB: a web server for exploration of mouse and human single-cell RNA sequencing data","volume":"2019","author":"Franz\u00e9n","year":"2019","journal-title":"Database"},{"key":"2023063011482089500_btaa269-B10","doi-asserted-by":"crossref","first-page":"3123","DOI":"10.1093\/bioinformatics\/btx337","article-title":"ASAP: a web-based platform for the analysis and interactive visualization of single-cell RNA-seq data","volume":"33","author":"Gardeux","year":"2017","journal-title":"Bioinformatics"},{"key":"2023063011482089500_btaa269-B11","doi-asserted-by":"crossref","first-page":"296","DOI":"10.1186\/s13059-019-1874-1","article-title":"Normalization and variance stabilization of single-cell RNA-seq data using regularized negative binomial regression","volume":"20","author":"Hafemeister","year":"2019","journal-title":"Genome Biol"},{"key":"2023063011482089500_btaa269-B12","doi-asserted-by":"crossref","first-page":"2930","DOI":"10.1093\/bioinformatics\/btx315","article-title":"Single-cell regulome data analysis by SCRAT","volume":"33","author":"Ji","year":"2017","journal-title":"Bioinformatics"},{"key":"2023063011482089500_btaa269-B13","doi-asserted-by":"crossref","first-page":"118","DOI":"10.1093\/biostatistics\/kxj037","article-title":"Adjusting batch effects in microarray expression data using empirical Bayes methods","volume":"8","author":"Johnson","year":"2007","journal-title":"Biostatistics"},{"key":"2023063011482089500_btaa269-B14","first-page":"2122","article-title":"A step-by-step workflow for low-level analysis of single-cell RNA-seq data with Bioconductor","volume":"5","author":"Lun","year":"2016","journal-title":"F1000Res"},{"key":"2023063011482089500_btaa269-B15","doi-asserted-by":"crossref","first-page":"4305","DOI":"10.1093\/bioinformatics\/bty517","article-title":"iS-CellR: a user-friendly tool for analyzing and visualizing single-cell RNA sequencing data","volume":"34","author":"Patel","year":"2018","journal-title":"Bioinformatics"},{"key":"2023063011482089500_btaa269-B16","first-page":"284","volume-title":"Computer and Information Sciences - ISCIS 2005","author":"Pons","year":"2015"},{"key":"2023063011482089500_btaa269-B17","doi-asserted-by":"crossref","first-page":"e47","DOI":"10.1093\/nar\/gkv007","article-title":"limma powers differential expression analyses for RNA-sequencing and microarray studies","volume":"43","author":"Ritchie","year":"2015","journal-title":"Nucleic Acids Res"},{"key":"2023063011482089500_btaa269-B18","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1038\/nmeth.2764","article-title":"Entering the era of single-cell transcriptomics in biology and medicine","volume":"11","author":"Sandberg","year":"2014","journal-title":"Nat. Methods"},{"key":"2023063011482089500_btaa269-B19","doi-asserted-by":"crossref","first-page":"5233","DOI":"10.1038\/s41598-019-41695-z","article-title":"From Louvain to Leiden: guaranteeing well-connected communities","volume":"9","author":"Traag","year":"2019","journal-title":"Sci. Rep"},{"key":"2023063011482089500_btaa269-B20","first-page":"2579","article-title":"Visualizing data using t-SNE","volume":"9","author":"van der Maaten","year":"2008","journal-title":"J. Mach. Learn. Res"},{"key":"2023063011482089500_btaa269-B21","doi-asserted-by":"crossref","first-page":"281","DOI":"10.1016\/j.cels.2018.11.005","article-title":"Scrublet: computational Identification of cell doublets in single-cell transcriptomic data","volume":"8","author":"Wolock","year":"2019","journal-title":"Cell Syst"},{"key":"2023063011482089500_btaa269-B22","doi-asserted-by":"crossref","first-page":"108","DOI":"10.1186\/s13073-017-0492-3","article-title":"Granatum: a graphical single-cell RNA-Seq analysis pipeline for genomics scientists","volume":"9","author":"Zhu","year":"2017","journal-title":"Genome Med"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/academic.oup.com\/bioinformatics\/advance-article-pdf\/doi\/10.1093\/bioinformatics\/btaa269\/33238582\/btaa269.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/36\/12\/3910\/50750617\/bioinformatics_36_12_3910.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/36\/12\/3910\/50750617\/bioinformatics_36_12_3910.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,6,30]],"date-time":"2023-06-30T11:49:00Z","timestamp":1688125740000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/36\/12\/3910\/5824295"}},"subtitle":[],"editor":[{"given":"Jan","family":"Gorodkin","sequence":"additional","affiliation":[],"role":[{"role":"editor","vocabulary":"crossref"}]}],"short-title":[],"issued":{"date-parts":[[2020,4,23]]},"references-count":22,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2020,6,1]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btaa269","relation":{},"ISSN":["1367-4803","1367-4811"],"issn-type":[{"value":"1367-4803","type":"print"},{"value":"1367-4811","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2020,6,15]]},"published":{"date-parts":[[2020,4,23]]}}}