School of Biomedical Engineering, School of Ophthalmology and Optometry and Eye Hospital, Wenzhou Medical University, Wenzhou 325011, Zhejiang, China.
College of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, Zhejiang, China.
Bioinformatics. 2020 Aug 15;36(14):4217-4219. doi: 10.1093/bioinformatics/btaa532.
At present, a fundamental challenge in single-cell RNA-sequencing data analysis is functional interpretation and annotation of cell clusters. Biological pathways in distinct cell types have different activation patterns, which facilitates the understanding of cell functions using single-cell transcriptomics. However, no effective web tool has been implemented for single-cell transcriptome data analysis based on prior biological pathway knowledge.
Here, we present scTPA, a web-based platform for pathway-based analysis of single-cell RNA-seq data in human and mouse. scTPA incorporates four widely-used gene set enrichment methods to estimate the pathway activation scores of single cells based on a collection of available biological pathways with different functional and taxonomic classifications. The clustering analysis and cell-type-specific activation pathway identification were provided for the functional interpretation of cell types from a pathway-oriented perspective. An intuitive interface allows users to conveniently visualize and download single-cell pathway signatures. Overall, scTPA is a comprehensive tool for the identification of pathway activation signatures for the analysis of single cell heterogeneity.
http://sctpa.bio-data.cn/sctpa.
sujz@wmu.edu.cn or yufulong421@gmail.com or zgj@zjut.edu.cn.
Supplementary data are available at Bioinformatics online.
目前，单细胞 RNA 测序数据分析的一个基本挑战是对细胞簇进行功能解释和注释。不同细胞类型中的生物途径具有不同的激活模式，这有助于使用单细胞转录组学来理解细胞功能。然而，基于先前的生物学途径知识，尚未实现用于单细胞转录组数据分析的有效网络工具。
在这里，我们提出了 scTPA，这是一个基于网络的平台，用于分析人类和小鼠的单细胞 RNA-seq 数据的途径。scTPA 结合了四种广泛使用的基因集富集方法，根据具有不同功能和分类学分类的可用生物途径集合，估计单细胞的途径激活分数。提供聚类分析和细胞类型特异性激活途径识别，以便从途径导向的角度对细胞类型进行功能解释。直观的界面允许用户方便地可视化和下载单细胞途径特征。总体而言，scTPA 是用于识别途径激活特征的综合工具，可用于分析单细胞异质性。
http://sctpa.bio-data.cn/sctpa。
sujz@wmu.edu.cn 或 yufulong421@gmail.com 或 zgj@zjut.edu.cn。
补充数据可在生物信息学在线获得。
