Department of Biostatistics and Bioinformatics, Duke University, USA.
Department of Molecular Genetics and Microbiology, Duke University, USA.
Nucleic Acids Res. 2024 May 22;52(9):e46. doi: 10.1093/nar/gkae307.
SifiNet is a robust and accurate computational pipeline for identifying distinct gene sets, extracting and annotating cellular subpopulations, and elucidating intrinsic relationships among these subpopulations. Uniquely, SifiNet bypasses the cell clustering stage, commonly integrated into other cellular annotation pipelines, thereby circumventing potential inaccuracies in clustering that may compromise subsequent analyses. Consequently, SifiNet has demonstrated superior performance in multiple experimental datasets compared with other state-of-the-art methods. SifiNet can analyze both single-cell RNA and ATAC sequencing data, thereby rendering comprehensive multi-omic cellular profiles. It is conveniently available as an open-source R package.
SifiNet 是一个强大而准确的计算流程，用于识别不同的基因集，提取和注释细胞亚群，并阐明这些亚群之间的内在关系。独特的是，SifiNet 绕过了通常集成到其他细胞注释流程中的细胞聚类阶段，从而避免了聚类中的潜在不准确之处，这些不准确之处可能会影响后续分析。因此，SifiNet 在多个实验数据集上的表现优于其他最先进的方法。SifiNet 可以分析单细胞 RNA 和 ATAC 测序数据，从而提供全面的多组学细胞图谱。它作为一个开源的 R 包方便使用。
