Cell DiffErential Expression by Pooling (CellDEEP) highlights issues in differential gene expression in scRNA-seq

NAR Genomics and Bioinformatics, vol. 8, pp. lqag128

Abstract

Accurate identification of differentially expressed genes (DEGs) in single-cell RNA sequencing data remains challenging. Single-cell-specific statistical models often report large numbers of candidate genes but can exhibit inflated false positive rates, whereas pseudobulk approaches improve false discovery control at the cost of reduced sensitivity. To overcome the noise and bias that other tools have, and allow the user to have more control of the DEG process, we present CellDEEP, which uses a cell aggregation (metacell) approach. This tool provides a framework for flexible selection of pooling strategies and parameterization for differential expression analysis. Benchmarking on simulated and real datasets, including COVID-19 and rheumatoid arthritis, shows that CellDEEP often outperforms other methods, consistently reduces false positives compared to single-cell methods and recovers more true positives than pseudobulk methods. Our work shifts the focus from selecting a single 'best' method to an approach that reduces cell-level noise while preserving biological signal, together with transparent validation framework, advancing more reliable differential-expression analysis in single-cell transcriptomics.

Authors 7

1. Yiyi Cheng

   University of Glasgow · Bernhard Nocht Institute for Tropical Medicine

   Affiliation as printed

   Bernhard Nocht Institute of Tropical Medicine , 20359,Hamburg ,

   School of Infection & Immunity, University of Glasgow , G12 8TA,Glasgow ,

2. Toby Kettlewell

   University of Glasgow

   Affiliation as printed

   School of Mathematics & Statistics, University of Glasgow , G12 8QQ,Glasgow ,

3. Ross F Laidlaw Aachen Centre for Infectious Diseases

   University of Glasgow · Leiden University Medical Center

   Affiliation as printed

   Center for Infectious Diseases, Leiden University , 2300 RC,LUMC, Leiden ,

   School of Infection & Immunity, University of Glasgow , G12 8TA,Glasgow ,

4. Olympia M Hardy

   University of Glasgow

   Affiliation as printed

   School of Infection & Immunity, University of Glasgow , G12 8TA,Glasgow ,

5. A. McCluskey

   University of Glasgow · Bernhard Nocht Institute for Tropical Medicine

   Affiliation as printed

   Bernhard Nocht Institute of Tropical Medicine , 20359,Hamburg ,

   School of Infection & Immunity, University of Glasgow , G12 8TA,Glasgow ,

6. Thomas D. Otto corresponding

   Centre National de la Recherche Scientifique · Universität Hamburg · Inserm · University of Glasgow · Université de Montpellier · Bernhard Nocht Institute for Tropical Medicine · HAW Hamburg · Laboratory of Pathogens and Host Immunity

   Affiliation as printed

   Bernhard Nocht Institute of Tropical Medicine , 20359,Hamburg ,

   LPHI, CNRS, INSERM, Université de Montpellier , 34095,Montpellier, Occitanie ,

   School of Infection & Immunity, University of Glasgow , G12 8TA,Glasgow ,

   University of Hamburg , 20148,Hamburg ,

7. Domenico Somma corresponding

   University of Glasgow · Bernhard Nocht Institute for Tropical Medicine · Università Cattolica del Sacro Cuore

   Affiliation as printed

   Bernhard Nocht Institute of Tropical Medicine , 20359,Hamburg ,

   Division of Rheumatology and Clinical Immunology, Università Cattolica del Sacro Cuore , 00168,Rome ,

   School of Infection & Immunity, University of Glasgow , G12 8TA,Glasgow ,