UMI-count modeling and differential expression analysis for single-cell RNA sequencing
Open accessAbstract
Read counting and unique molecular identifier (UMI) counting are the principal gene expression quantification schemes used in single-cell RNA-sequencing (scRNA-seq) analysis. By using multiple scRNA-seq datasets, we reveal distinct distribution differences between these schemes and conclude that the negative binomial model is a good approximation for UMI counts, even in heterogeneous populations. We further propose a novel differential expression analysis algorithm based on a negative binomial model with independent dispersions in each group (NBID). Our results show that this properly controls the FDR and achieves better power for UMI counts when compared to other recently developed packages for scRNA-seq analysis.
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Smart-seq2 data showed zero-inflation on the single cell level, but aggregation to pseudobulk removed the excess of zero values.
“In contrast to the other technologies, the Smart-seq2 data showed zero-inflation on the single cell level (see also68,69), but aggregation to pseudobulk removed the excess of zero values.”
From scPower accelerates and optimizes the design of multi-sample single cell transcriptomic studies (2021) · cites this paper as [68]
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- Authors
- Chen, W., Li, Y., Easton, J., Finkelstein, D., Wu, G., & Chen, X.
- Affiliations
- St. Jude Children's Research Hospital (US)
- University of Minnesota (US)
- Corresponding author
- Chen, Xiang
- Venue
- Genome Biology
- Published
- 2018-05-31
- Volume
- 19
- Issue
- 1
- Pages
- 70-70
- ISSN
- 1465-6906 (ISSN-L)
- 1474-760X
- PMC
- PMC5984373
- OpenAlex
- W2805888371
- Cited by
- 113
- References
- 47
- Citations by year
- 2026: 8 · 2025: 14 · 2024: 14 · 2023: 21 · 2022: 12 · 2021: 22 · 2020: 14 · 2019: 7
- FWCI
- 3.80
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Genome biology (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, other-oa)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- American Lebanese Syrian Associated Charities
- National Cancer Institute (P30CA021765)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Keywords
- unique molecular identifiers, read counting, gene expression quantification, negative binomial regression, differential expression analysis, false discovery rate control, single-cell RNA sequencing, count distributions
- MeSH terms
- Algorithms, Humans, Immunologic Memory, T-Lymphocytes, Models, Statistical, Biomarkers, Sequence Analysis, RNA, Gene Expression Profiling, Cell Line, Tumor, Single-Cell Analysis
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