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SifiNet: A robust and accurate method to identify feature gene sets and annotate cells.

Publication ,  Journal Article
Gao, Q; Ji, Z; Wang, L; Owzar, K; Li, Q-J; Chan, C; Xie, J
Published in: bioRxiv
April 6, 2024

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 multiomic cellular profiles. It is conveniently available as an open-source R package.

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Published In

bioRxiv

DOI

EISSN

2692-8205

Publication Date

April 6, 2024

Location

United States
 

Citation

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Gao, Q., Ji, Z., Wang, L., Owzar, K., Li, Q.-J., Chan, C., & Xie, J. (2024). SifiNet: A robust and accurate method to identify feature gene sets and annotate cells. BioRxiv. https://doi.org/10.1101/2023.05.24.541352
Gao, Qi, Zhicheng Ji, Liuyang Wang, Kouros Owzar, Qi-Jing Li, Cliburn Chan, and Jichun Xie. “SifiNet: A robust and accurate method to identify feature gene sets and annotate cells.BioRxiv, April 6, 2024. https://doi.org/10.1101/2023.05.24.541352.
Gao Q, Ji Z, Wang L, Owzar K, Li Q-J, Chan C, et al. SifiNet: A robust and accurate method to identify feature gene sets and annotate cells. bioRxiv. 2024 Apr 6;
Gao, Qi, et al. “SifiNet: A robust and accurate method to identify feature gene sets and annotate cells.BioRxiv, Apr. 2024. Pubmed, doi:10.1101/2023.05.24.541352.
Gao Q, Ji Z, Wang L, Owzar K, Li Q-J, Chan C, Xie J. SifiNet: A robust and accurate method to identify feature gene sets and annotate cells. bioRxiv. 2024 Apr 6;

Published In

bioRxiv

DOI

EISSN

2692-8205

Publication Date

April 6, 2024

Location

United States