ArticleNature methods2025
Scvi-hub: an actionable repository for model-driven single-cell analysis.
Article in Nature methods, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
11 citing papers in PubMed.
- Progressive suppression of regulated cell death defines terminal macrophage states in liver cirrhosis.Annals of medicine · 2026Article
- Spatiotemporal transcriptomics for tumour microenvironment remodelling in cancer progression and therapy.Clinical and translational medicine · 2026Review
- ArchMap is a web-based platform for reference-based analysis of single-cell datasets.Nature genetics · 2026Article
- Hematopoietic Stem and Progenitor Cells Establish Dynamic Podosome-Like Structures to Interact with Fibronectin.Advanced biology · 2026Article
- Translational insights and clinical challenges of targeting cancer stem cells.Signal transduction and targeted therapy · 2026Review
- SCONE: a subset-contrastive method for multi-omics network embedding.Briefings in bioinformatics · 2026Article
- ScGeo reveals non-canonical trajectories beyond RNA velocity in radiation-induced hematopoietic recovery.Bioinformatics advances · 2026Article
- Decoding Treg diversity and dysfunction to advance Treg-based therapies in autoimmune and inflammatory diseases.Frontiers in immunology · 2026Review
- Why "Where" Matters as Much as "How Much": Single-Cell and Spatial Transcriptomics in Plants.International journal of molecular sciences · 2025Review
- Article
- Advancing automated cell type annotation with large language models and single-cell isoform sequencing.Computational and structural biotechnology journal · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
The growing availability of single-cell omics datasets presents new opportunities for reuse, while challenges in data transfer, normalization and integration remain a barrier. Here we present scvi-hub: a platform for efficiently sharing and accessing single-cell omics datasets using pretrained probabilistic models. It enables immediate execution of fundamental tasks like visualization, imputation, annotation and deconvolution on new query datasets using state-of-the-art methods, with massively reduced storage and compute requirements. We show that pretrained models support efficient analysis of large references, including the CZI CELLxGENE Discover Census. Scvi-hub is built within the scvi-tools open-source environment and integrated into scverse. Scvi-hub offers a scalable and user-friendly framework for accessing and contributing to a growing ecosystem of ready-to-use models and datasets, thus putting the power of atlas-level analysis at the fingertips of a broad community of users.
Indexed as
Identifiers
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.