School of Computer Science, Northwestern Polytechnical University, 710129 Xi'an, Shaanxi, China.
School of Life Science, Northwestern Polytechnical University, 710072 Xi'an, Shaanxi, China.
Bioinformatics. 2024 Feb 1;40(2). doi: 10.1093/bioinformatics/btae053.
Single-cell multi-omics technologies provide a unique platform for characterizing cell states and reconstructing developmental process by simultaneously quantifying and integrating molecular signatures across various modalities, including genome, transcriptome, epigenome, and other omics layers. However, there is still an urgent unmet need for novel computational tools in this nascent field, which are critical for both effective and efficient interrogation of functionality across different omics modalities. Scbean represents a user-friendly Python library, designed to seamlessly incorporate a diverse array of models for the examination of single-cell data, encompassing both paired and unpaired multi-omics data. The library offers uniform and straightforward interfaces for tasks, such as dimensionality reduction, batch effect elimination, cell label transfer from well-annotated scRNA-seq data to scATAC-seq data, and the identification of spatially variable genes. Moreover, Scbean's models are engineered to harness the computational power of GPU acceleration through Tensorflow, rendering them capable of effortlessly handling datasets comprising millions of cells.
Scbean is released on the Python Package Index (PyPI) (https://pypi.org/project/scbean/) and GitHub (https://github.com/jhu99/scbean) under the MIT license. The documentation and example code can be found at https://scbean.readthedocs.io/en/latest/.
单细胞多组学技术通过同时定量和整合各种模式（包括基因组、转录组、表观基因组和其他组学层）的分子特征，为描述细胞状态和重建发育过程提供了独特的平台。然而，在这个新兴领域，仍然迫切需要新的计算工具，这对于有效和高效地研究不同组学模式的功能至关重要。Scbean 是一个用户友好的 Python 库，旨在无缝整合用于检查单细胞数据的各种模型，包括配对和非配对的多组学数据。该库为降维、批次效应消除、从标记良好的 scRNA-seq 数据到 scATAC-seq 数据的细胞标签转移以及空间可变基因的识别等任务提供了统一和简单的接口。此外，Scbean 的模型经过设计，可以利用 GPU 加速的计算能力通过 Tensorflow 来实现，从而能够轻松处理包含数百万个细胞的数据集。
Scbean 已在 Python 包索引 (PyPI) (https://pypi.org/project/scbean/) 和 GitHub (https://github.com/jhu99/scbean) 上发布，并根据麻省理工学院许可证发布。文档和示例代码可在 https://scbean.readthedocs.io/en/latest/ 找到。
