ArticlePLoS computational biology2023
The specious art of single-cell genomics.
Article in PLoS computational biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 219 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
219 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Functional genomic mechanisms of opioid action and opioid use disorder: a systematic review of animal models and human studies.Molecular psychiatry · 2023Pooled it
- Initial recommendations for performing, benchmarking and reporting single-cell proteomics experiments.Nature methods · 2023Guideline
- Convex approaches to isolate the shared and distinct genetic components of complex traits.Bioinformatics (Oxford, England) · 2026Article
- Quantifying distribution shifts in single-cell data with scXMatch.Bioinformatics (Oxford, England) · 2026Article
- scDiagnostics: systematic assessment of cell type annotation in single-cell transcriptomics data.Briefings in bioinformatics · 2026Article
- Bonsai reconstructs tree representations for distortion-free visualization and exploration of high-dimensional data.Nature biotechnology · 2026Article
- Uncovering smooth structures in single-cell data with neighbor embeddings guided by predictability-computability-stability.Patterns (New York, N.Y.) · 2026Article
- A High-Content Imaging Pipeline to Investigate Subcytotoxic Effects in RTgill-W1 Cells.Environmental science & technology · 2026Article
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- A week in the life of the human brain reveals stable states punctuated by chaotic-like transitions.Nature communications · 2026Article
- CAdir: Joint clustering of cells and genes for single-cell transcriptomics with visualization-driven cluster quality assessment.PLoS computational biology · 2026Article
- Gene regulatory networks: from correlative models to causal explanations.Nature reviews. Genetics · 2026Review
- The hippocampus as a small-world cognitive map.bioRxiv : the preprint server for biology · 2026Article
- Trypanosoma cruzi cell atlas as a single-cell resource for understanding parasite population heterogeneity and differentiation.Nature communications · 2026Article
- lcUMAPtSNE: use of non-linear dimensionality reduction techniques with genotype likelihoods.BMC genomics · 2026Article
- Biology Needs Philosophy, But What Philosophy?Bioscience · 2026Review
- Coherent cross-modal generation of synthetic biomedical data to advance multimodal precision medicine.PLoS computational biology · 2026Article
159 more citing papers are in PubMed but not listed here.
Corrections and comments
- Erratum issued
Authors and funding
2 authors.
Funding
Abstract
Dimensionality reduction is standard practice for filtering noise and identifying relevant features in large-scale data analyses. In biology, single-cell genomics studies typically begin with reduction to 2 or 3 dimensions to produce "all-in-one" visuals of the data that are amenable to the human eye, and these are subsequently used for qualitative and quantitative exploratory analysis. However, there is little theoretical support for this practice, and we show that extreme dimension reduction, from hundreds or thousands of dimensions to 2, inevitably induces significant distortion of high-dimensional datasets. We therefore examine the practical implications of low-dimensional embedding of single-cell data and find that extensive distortions and inconsistent practices make such embeddings counter-productive for exploratory, biological analyses. In lieu of this, we discuss alternative approaches for conducting targeted embedding and feature exploration to enable hypothesis-driven biological discovery.
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What OpenQuestion holds
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.