Suppr超能文献

BrainCellR:一种用于跨脑单细胞数据集进行比较分析的精确细胞类型命名管道。

BrainCellR: A precise cell type nomenclature pipeline for comparative analysis across brain single-cell datasets.

作者信息

Chi Yuhao, Marini Simone, Wang Guang-Zhong

机构信息

CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China.

Department of Epidemiology, University of Florida, Gainesville, FL, USA.

出版信息

Comput Struct Biotechnol J. 2024 Nov 26;23:4306-4314. doi: 10.1016/j.csbj.2024.11.038. eCollection 2024 Dec.

Abstract

Single-cell studies in neuroscience require precise cell type classification and consistent nomenclature that allows for meaningful comparisons across diverse datasets. Current approaches often lack the ability to identify fine-grained cell types and establish standardized annotations at the cluster level, hindering comprehensive understanding of the brain's cellular composition. To facilitate data integration across multiple models and datasets, we designed BrainCellR. This pipeline provides researchers with a powerful and user-friendly tool for efficient cell type classification and nomination from single-cell transcriptomic data. While initially focused on brain studies, BrainCellR is applicable to other tissues with complex cellular compositions. BrainCellR goes beyond conventional classification approaches by incorporating a standardized nomenclature system for cell types at the cluster level. This feature enables consistent and comparable annotations across different studies, promoting data integration and providing deeper insights into the complex cellular landscape of the brain. All documents for BrainCellR, including source code, user manual and tutorials, are freely available at https://github.com/WangLab-SINH/BrainCellR.

摘要

神经科学中的单细胞研究需要精确的细胞类型分类和一致的命名法,以便能够对不同的数据集进行有意义的比较。当前的方法往往缺乏识别细粒度细胞类型和在聚类水平建立标准化注释的能力,这阻碍了对大脑细胞组成的全面理解。为了促进跨多个模型和数据集的数据整合,我们设计了BrainCellR。该管道为研究人员提供了一个强大且用户友好的工具,用于从单细胞转录组数据中高效地进行细胞类型分类和命名。虽然最初专注于大脑研究,但BrainCellR适用于其他具有复杂细胞组成的组织。BrainCellR通过在聚类水平纳入细胞类型的标准化命名系统,超越了传统的分类方法。这一特性使得不同研究之间能够进行一致且可比的注释,促进了数据整合,并为深入了解大脑复杂的细胞景观提供了更多见解。BrainCellR的所有文档,包括源代码、用户手册和教程,均可在https://github.com/WangLab-SINH/BrainCellR上免费获取。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6e8/11648093/86fcd34b9a91/ga1.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验