AUTHOR=Sun Jie , Morrison Robert , Kim Soyeon , Yan Kairuo , Park Hyun Jung 

TITLE=Quantitative measures to assess the quality of cellular indexing of transcriptomes and epitopes by sequencing data

JOURNAL=Frontiers in Bioinformatics

VOLUME=Volume 5 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/bioinformatics/articles/10.3389/fbinf.2025.1630161

DOI=10.3389/fbinf.2025.1630161

ISSN=2673-7647

ABSTRACT=BackgroundCellular indexing of transcriptomes and epitopes by sequencing (CITE-Seq) is a powerful technique to simultaneously measure gene expression and cell surface protein abundances in individual cells. To obtain accurate and reliable biological findings from CITE-Seq data, it is critical to ensure rigorous quality control (QC). However, no public method has yet been developed for CITE-Seq QC.ResultsIn this study, we propose the first software package for multi-layered, systemic, and quantitative quality control (CITESeQC). Recognizing the multi-layered nature of CITE-Seq data, CITESeQC performs QC across gene expressions, surface proteins, and their interactions. It systemically evaluates all genes and protein markers assayed in the data and filters out some of them based on individual quality measures. Furthermore, for quantitative QC that enables objective and standardized analyses, CITESeQC quantifies cell type-specific expression of genes and surface proteins using Shannon entropy and correlation-based measures. Finally, to ensure broad applicability, CITESeQC guides users through a simple process that generates a complete markdown report with supporting figures and explanations, requiring minimal user intervention.ConclusionBy quantifying the quality of CITE-Seq data, CITESeQC enables precise characterization of gene expression within cell types and reliable classification of cell types using surface protein markers, thereby enhancing its value for clinical applications.