ArticleCell systems2026
The impact of package selection and versioning on single-cell RNA-seq analysis.
Article in Cell systems, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
22 citing papers in PubMed.
- Coordinated dysregulation of modular gene activity in human neuropathologies.bioRxiv : the preprint server for biology · 2026Article
- Consensus Pituitary Atlas, a scalable resource for annotation, novel marker discovery, and analyses in mouse pituitary gland research.Cell reports · 2026Article
- anndataR improves interoperability between R and Python in single-cell transcriptomics.Bioinformatics (Oxford, England) · 2026Article
- Multi-Omic and Single-Cell Approaches for Elucidating Cell Biology and Pathobiology of Lung Disease.American journal of respiratory cell and molecular biology · 2026Review
- REDAC: RNA-seq expression data analysis chatbot.Bioinformatics advances · 2026Article
- Combined somatic mutation and transcriptome analysis reveals region-specific differences in clonal architecture in human cortex.Cell reports · 2025Article
- Benchmarking large-scale single-cell RNA-seq analysis.bioRxiv : the preprint server for biology · 2025Article
- The overexpression of HOXC6 in LUSC and pan-squamous cell carcinomas indicates the coexistence of nuclear division regulatory mechanisms.Cancer biomarkers : section A of Disease markers · 2025Article
- PSCS: Unified Sharing of Single-Cell Omics Data, Analyses, and Results.Journal of proteome research · 2025Article
- Artificial Intelligence in Ocular Transcriptomics: Applications of Unsupervised and Supervised Learning.Cells · 2025Review
- Global trends in machine learning applications for single-cell transcriptomics research.Hereditas · 2025Article
- Nitidine chloride may mediate its antitumor effects by targeting kinesin family member 20A in colorectal cancer cells.World journal of clinical oncology · 2025Article
- CAFE: an integrated web app for high-dimensional analysis and visualization in spectral flow cytometry.Bioinformatics (Oxford, England) · 2025Article
- Exploring the latent space of transcriptomic data with topic modeling.NAR genomics and bioinformatics · 2025Article
- Pseudoassembly of k-mers.bioRxiv : the preprint server for biology · 2025Article
- Principled PCA separates signal from noise in omics count data.bioRxiv : the preprint server for biology · 2025Article
- Accurate quantification of nascent and mature RNAs from single-cell and single-nucleus RNA-seq.Nucleic acids research · 2025Article
- Primer on machine learning applications in brain immunology.Frontiers in bioinformatics · 2025Review
- CAFE: An Integrated Web App for High-Dimensional Analysis and Visualization in Spectral Flow Cytometry.bioRxiv : the preprint server for biology · 2024Article
- Assessing the impact of transcriptomics data analysis pipelines on downstream functional enrichment results.Nucleic acids research · 2024Article
Corrections and comments
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Standard single-cell RNA sequencing (scRNA-seq) workflows convert raw reads into cell-gene count matrices and then perform filtering, highly variable gene selection, dimensionality reduction, clustering, and differential expression analysis. Seurat and Scanpy are the most widely used implementations of these workflows and are generally assumed to yield similar results. Here, we examine the underlying algorithms of both packages and show that their outputs differ substantially across multiple analytic steps. The magnitude of Seurat-Scanpy differences is comparable to the variability introduced by sequencing fewer than 5% of reads or analyzing fewer than 20% of cells. We further find that software version changes can alter results, particularly in differential expression. Our findings underscore the need for users to critically evaluate analysis tools and for developers to prioritize transparency and reproducibility.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.