Hu Nie, Peilu Lin, Yu Zhang, Yihong Wan, Jiesheng Li, Chengqian Yin, Lei Zhang
{"title":"Single-cell meta-analysis of inflammatory bowel disease with scIBD","authors":"Hu Nie, Peilu Lin, Yu Zhang, Yihong Wan, Jiesheng Li, Chengqian Yin, Lei Zhang","doi":"10.1038/s43588-023-00464-9","DOIUrl":null,"url":null,"abstract":"Understanding the heterogeneous intestinal microenvironment is critical to uncover the pathogenesis of inflammatory bowel disease (IBD). Recent advances in single-cell RNA sequencing (scRNA-seq) have identified certain cell types and genes that could contribute to IBD; however, a comprehensively integrated analysis of these scRNA-seq datasets is not yet available. Here we introduce scIBD, a platform for single-cell meta-analysis of IBD with interactive and visualization features, which combines highly curated single-cell datasets in a uniform workflow, enabling identifying rare or less-characterized cell types in IBD and dissecting the commonalities, as well as the differences between ulcerative colitis and Crohn’s disease. scIBD also incorporates multifunctional information—including regulon activity, GWAS-implicated risk genes and genes targeted by therapeutics—to infer clinically relevant cell-type specificity. Collectively, scIBD is a user-friendly web-based platform for the community to analyze the transcriptome features and gene regulatory networks associated with the pathogenesis and treatment of IBD at single-cell resolution. A platform for single-cell meta-analysis of inflammatory bowel disease, named scIBD, enables identification of rare or less-characterized cell types and the dissection of the commonalities and differences between ulcerative colitis and Crohn’s disease.","PeriodicalId":74246,"journal":{"name":"Nature computational science","volume":"3 6","pages":"522-531"},"PeriodicalIF":18.3000,"publicationDate":"2023-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature computational science","FirstCategoryId":"1085","ListUrlMain":"https://www.nature.com/articles/s43588-023-00464-9","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
Understanding the heterogeneous intestinal microenvironment is critical to uncover the pathogenesis of inflammatory bowel disease (IBD). Recent advances in single-cell RNA sequencing (scRNA-seq) have identified certain cell types and genes that could contribute to IBD; however, a comprehensively integrated analysis of these scRNA-seq datasets is not yet available. Here we introduce scIBD, a platform for single-cell meta-analysis of IBD with interactive and visualization features, which combines highly curated single-cell datasets in a uniform workflow, enabling identifying rare or less-characterized cell types in IBD and dissecting the commonalities, as well as the differences between ulcerative colitis and Crohn’s disease. scIBD also incorporates multifunctional information—including regulon activity, GWAS-implicated risk genes and genes targeted by therapeutics—to infer clinically relevant cell-type specificity. Collectively, scIBD is a user-friendly web-based platform for the community to analyze the transcriptome features and gene regulatory networks associated with the pathogenesis and treatment of IBD at single-cell resolution. A platform for single-cell meta-analysis of inflammatory bowel disease, named scIBD, enables identification of rare or less-characterized cell types and the dissection of the commonalities and differences between ulcerative colitis and Crohn’s disease.