ArticleeLife2023
Avoiding false discoveries in single-cell RNA-seq by revisiting the first Alzheimer's disease dataset.
Article in eLife, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.
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Who cites it
19 citing papers in PubMed, 1 synthesis or guideline pooled it, 21 citations in OpenAlex.
- Improving reproducibility of differentially expressed genes in single-cell transcriptomic studies of neurodegenerative diseases through meta-analysis.Nature communications · 2025Pooled it
- Efficient differential expression analysis of large-scale single-cell transcriptomics data using Dreamlet.Nature communications · 2026Article
- Beta-Adrenergic Stimulation andbioRxiv : the preprint server for biology · 2026Article
- Differential expression analysis in single-cell and spatial RNA-seq without model assumptions.Cell reports methods · 2026Article
- Comparative analysis of nuclei isolation methods for brain single-nucleus RNA sequencing.Cell reports methods · 2026Article
- Selective weakening of population-coupled synaptic activity in vivo in a mouse model of amyloid-beta pathology.Nature communications · 2026Article
- Genetic risk in Alzheimer's disease.NPJ systems biology and applications · 2026Review
- Differential expression analysis in single cell and spatial RNASeq without model assumptions.bioRxiv : the preprint server for biology · 2025Article
- Precision and Accuracy in Quantitative Measurement of Gene Expression from Single-cell/nucleus RNA Sequencing Data.Genomics, proteomics & bioinformatics · 2025Article
- A Transcriptomic Roadmap of Parkinson's Disease Progression at Single Cell Resolution.medRxiv : the preprint server for health sciences · 2025Article
- SpotSweeper: spatially aware quality control for spatial transcriptomics.Nature methods · 2025Article
- A Reproducibility Focused Meta-Analysis Method for Single-Cell Transcriptomic Case-Control Studies Uncovers Robust Differentially Expressed Genes.bioRxiv : the preprint server for biology · 2025Article
- Loss of immune cell identity with age inferred from large atlases of single cell transcriptomes.Aging cell · 2024Article
- Single-cell atlas of transcriptomic vulnerability across multiple neurodegenerative and neuropsychiatric diseases.medRxiv : the preprint server for health sciences · 2024Article
- Transcriptional analysis of primary ciliary dyskinesia airway cells reveals a dedicated cilia glutathione pathway.JCI insight · 2024Article
- Single-nucleus sequencing reveals enriched expression of genetic risk factors in extratelencephalic neurons sensitive to degeneration in ALS.Nature aging · 2024Article
- SpotSweeper: spatially-aware quality control for spatial transcriptomics.bioRxiv : the preprint server for biology · 2024Article
- An overview of human single-cell RNA sequencing studies in neurobiological disease.Neurobiology of disease · 2023Review
- TMEM2: A New Dimension in Hyaluronan Biology.Proteoglycan researchArticle
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
Mathys et al. conducted the first single-nucleus RNA-seq (snRNA-seq) study of Alzheimer's disease (AD) (Mathys et al., 2019). With bulk RNA-seq, changes in gene expression across cell types can be lost, potentially masking the differentially expressed genes (DEGs) across different cell types. Through the use of single-cell techniques, the authors benefitted from increased resolution with the potential to uncover cell type-specific DEGs in AD for the first time. However, there were limitations in both their data processing and quality control and their differential expression analysis. Here, we correct these issues and use best-practice approaches to snRNA-seq differential expression, resulting in 549 times fewer DEGs at a false discovery rate of 0.05. Thus, this study highlights the impact of quality control and differential analysis methods on the discovery of disease-associated genes and aims to refocus the AD research field away from spuriously identified genes.
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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.