scPlant:A versatile framework for single-cell transcriptomic data analysis in plants

作     者：Shanni Cao Zhaohui He Ruidong Chen Yuting Luo Liang-Yu Fu Xinkai Zhou Chao He Wenhao Yan Chen-Yu Zhang Dijun Chen 

作者机构：State Key Laboratory of Pharmaceutical BiotechnologySchool of Life SciencesNanjing UniversityNanjing 210023China National Key Laboratory of Crop Genetic ImprovementHubei Hongshan LaboratoryHuazhong Agricultural UniversityWuhanChina 

出 版 物：《Plant Communications》 (植物通讯（英文）)

年 卷 期：2023年第4卷第5期

页      面：1-14页

核心收录：

学科分类：0710[理学-生物学] 071001[理学-植物学] 07[理学] 

基　　金：supported by the National Natural Science Foundation of China(no.32070656) the Nanjing University Deng Feng Scholars Program 

主　　题：versatile Plant integration 

摘      要：Single-cell transcriptomics has been fully embraced in plant biological research and is revolutionizing our understanding of plant growth,development,and responses to external ***,single-cell tran-scriptomic data analysis in plants is not trivial,given that there is currently no end-to-end solution and that integration of various bioinformatics tools involves a large number of required ***,we pre-sent scPlant,a versatile framework for exploring plant single-cell atlases with minimuminput data provided by *** scPlant pipeline is implemented with numerous functions for diverse analytical tasks,ranging from basic data processing to advanced demands such as cell-type annotation and deconvolution,trajec-tory inference,cross-species data integration,and cell-type-specific gene regulatory network *** addition,a variety of visualization tools are bundled in a built-in Shiny application,enabling explo-ration of single-cell transcriptomic data on the fly.