Author:
Chi Yuhao,Marini Simone,Wang Guang-Zhong
Abstract
AbstractSingle-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 package provides researchers with a powerful and user-friendly tool for efficient cell type classification and nomination from single-cell transcriptomic data. 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.Contactsimone.marini@ufl.eduorguangzhong.wang@picb.ac.cn
Publisher
Cold Spring Harbor Laboratory