scSID: A lightweight algorithm for identifying rare cell types by capturing differential expression from single-cell sequencing data-Reference-Cited by-同舟云学术

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scSID: A lightweight algorithm for identifying rare cell types by capturing differential expression from single-cell sequencing data

Published:2024-12 Issue: Volume:23 Page:589-600
ISSN:2001-0370
Container-title:Computational and Structural Biotechnology Journal
language:en
Short-container-title:Computational and Structural Biotechnology Journal

Author:

Wang Shudong,Li Hengxiao^ORCID,Zhang Kuijie,Wu Hao^ORCID,Pang Shanchen,Wu Wenhao,Ye Lan,Su Jionglong^ORCID,Zhang Yulin

Publisher

Elsevier BV

Reference48 articles.

1. Single-cell RNA sequencing to explore immune cell heterogeneity;Papalexi;Nat Rev Immunol,2018

2. Single-cell RNA sequencing in cancer: lessons learned and emerging challenges;Suvà;Mol Cell,2019

3. Single-cell RNA sequencing technologies and bioinformatics pipelines;Hwang;Exp Mol Med,2018

4. Critical downstream analysis steps for single-cell RNA sequencing data;Zhang;Brief Bioinform,2021

5. iNKT cell production of GM-CSF controls mycobacterium tuberculosis;Rothchild;PLoS Pathog,2014

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Connectivity Network Feature Sharing in Single-Cell RNA Sequencing Data Identifies Rare Cells;Journal of Chemical Information and Modeling;2024-08-03

2. Mining alternative splicing patterns in scRNA-seq data using scASfind;Genome Biology;2024-07-29

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