iDESC: identifying differential expression in single-cell RNA sequencing data with multiple subjects

iDESC: identifying differential expression in single-cell RNA sequencing data with multiple subjects

Abstract Background Single-cell RNA sequencing (scRNA-seq) technology has enabled assessment of transcriptome-wide changes at single-cell resolution. Due to the heterogeneity in environmental exposure and genetic background across subjects, subject effect contributes to the major source of variation...

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Bibliographic Details
Main Authors: Yunqing Liu, Jiayi Zhao, Taylor S. Adams, Ningya Wang, Jonas C. Schupp, Weimiao Wu, John E. McDonough, Geoffrey L. Chupp, Naftali Kaminski, Zuoheng Wang, Xiting Yan
Format: Article
Language:English
Published: BMC 2023-08-01
Series:BMC Bioinformatics
Subjects:
Single-cell RNA sequencing
Differential expression analysis
Subject effect
Zero-inflated negative binomial mixed model
Online Access:https://doi.org/10.1186/s12859-023-05432-8

Internet

https://doi.org/10.1186/s12859-023-05432-8

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