VeloViz: RNA velocity-informed embeddings for visualizing cellular trajectories.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:34500455", "kind": "science-record", "revision": 3, "content_hash": "sha256:8092060ee745e7f1cbef35bd39259a00a5f778a866c75482dc0dcd7f17821597", "created_at": "2026-11-01T17:36:04Z", "updated_at": "2026-11-01T21:26:11Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "VeloViz: RNA velocity-informed embeddings for visualizing cellular trajectories.", "doi": "10.1093/bioinformatics/btab653", "pmid": "34500455", "authors": ["Lyla Atta", "Arpan Sahoo", "Jean Fan"], "journal": "Bioinformatics (Oxford, England)", "year": 2022, "abstract": "MOTIVATION: Single-cell transcriptomics profiling technologies enable genome-wide gene expression measurements in individual cells but can currently only provide a static snapshot of cellular transcriptional states. RNA velocity analysis can help infer cell state changes using such single-cell transcriptomics data. To interpret these cell state changes inferred from RNA velocity analysis as part of underlying cellular trajectories, current approaches rely on visualization with principal components, t-distributed stochastic neighbor embedding and other 2D embeddings derived from the observed single-cell transcriptional states. However, these 2D embeddings can yield different representations of the underlying cellular trajectories, hindering the interpretation of cell state changes.\nRESULTS: We developed VeloViz to create RNA velocity-informed 2D and 3D embeddings from single-cell transcriptomics data. Using both real and simulated data, we demonstrate that VeloViz embeddings are able to capture underlying cellular trajectories across diverse trajectory topologies, even when intermediate cell states may be missing. By considering the predicted future transcriptional states from RNA velocity analysis, VeloViz can help visualize a more reliable representation of underlying cellular trajectories.\nAVAILABILITY AND IMPLEMENTATION: Source code is available on GitHub (https://github.com/JEFworks-Lab/veloviz) and Bioconductor (https://bioconductor.org/packages/veloviz) with additional tutorials at https://JEF.works/veloviz/. Datasets used can be found on Zenodo (https://doi.org/10.5281/zenodo.4632471).\nSUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.", "claims": [{"id": "claim-method", "statement": "RNA velocity analysis", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34500455", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "RNA velocity analysis"}], "state": "complete"}, {"id": "claim-data-access", "statement": "Datasets used can be found on Zenodo (https://doi.org/10.5281/zenodo.4632471).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34500455", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "Datasets used can be found on Zenodo (https://doi.org/10.5281/zenodo.4632471)."}], "state": "complete"}, {"id": "claim-target-result", "statement": "VeloViz embeddings can capture underlying cellular trajectories across diverse trajectory topologies, even when intermediate cell states may be missing.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:34500455", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "Using both real and simulated data, we demonstrate that VeloViz embeddings are able to capture underlying cellular trajectories across diverse trajectory topologies, even when intermediate cell states may be missing."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": "VeloViz embeddings can capture underlying cellular trajectories across diverse trajectory topologies, even when intermediate cell states may be missing.", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:34500455"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "blocked", "blocked_on": "data:accession_absent", "description": "The GEO series accession resolves and its sample accessions are listed. 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