Department of Medicine, Integrated Cardio Metabolic Centre, Karolinska Institutet, Huddinge 14157, Sweden.
Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
Bioinformatics. 2020 Jun 1;36(12):3910-3912. doi: 10.1093/bioinformatics/btaa269.
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.
The service runs at https://alona.panglaodb.se and the Python package can be downloaded from https://oscar-franzen.github.io/adobo/.
Supplementary data are available at Bioinformatics online.
单细胞 RNA 测序 (scRNA-seq) 是一种测量单细胞中基因表达的技术。它已经能够发现新的细胞类型,并建立了组织和器官的细胞类型图谱。scRNA-seq 的广泛采用,使得人们对数据分析的用户友好型软件产生了需求。我们开发了一个名为 alona 的网络服务器,它将几种最流行的单细胞分析算法整合到一个灵活的管道中。alona 可以进行质量过滤、归一化、批次校正、聚类、细胞类型注释和差异基因表达分析。数据通过基于 JavaScript 的界面在网络浏览器中可视化,允许用户查询感兴趣的基因并可视化聚类结构。alona 接受压缩的基因表达矩阵,并使用基于图的聚类策略识别细胞簇。细胞类型可以从综合的标记基因集合中识别,也可以通过指定自定义的标记基因集来识别。
该服务在 https://alona.panglaodb.se 上运行,Python 包可以从 https://oscar-franzen.github.io/adobo/ 下载。
补充数据可在 Bioinformatics 在线获取。