ArticleNature communications2026
ArchVelo: archetypal velocity modeling for single-cell multi-omic trajectories.
Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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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.
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Who cites it
1 citing paper in PubMed.
- ArchVelo: archetypal velocity modeling for single-cell multi-omic trajectories.Nature communications · 2026Article
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5 authors.
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Abstract
Inferring cellular dynamics from static single-cell data remains a central challenge in genomics. We introduce ArchVelo, a computational framework for modeling gene regulation and inferring trajectories from paired single-cell chromatin accessibility (scATAC-seq) and transcriptomic (scRNA-seq) data. ArchVelo represents chromatin accessibility as archetypes-shared regulatory programs-to model their dynamic influence on transcription. It outperforms existing methods in trajectory inference accuracy and gene-level latent time alignment, enables trajectory decomposition into archetypal components, and identifies the underlying transcription factors. After benchmarking on mouse brain and human hematopoiesis datasets, we apply ArchVelo to CD8 T cells in viral infection and reveal distinct trajectories of differentiation and proliferation. Focusing on progenitor exhausted CD8 T cells, critical for sustained immunity and immunotherapy response, we identify differentiation from Ccr6
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