ArticleBioinformatics (Oxford, England)2026
anndataR improves interoperability between R and Python in single-cell transcriptomics.
Article in Bioinformatics (Oxford, England), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- The HuBMAP Framework for Advancing Data FAIRness.bioRxiv : the preprint server for biology · 2026Article
- Orchestrating Spatial Transcriptomics Analysis with Bioconductor.bioRxiv : the preprint server for biology · 2025Article
- shinyUMAP: an online tool for promoting understanding of single cell omics data visualization.bioRxiv : the preprint server for biology · 2025Article
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
summaryMany single-cell transcriptomics datasets are stored in the HDF5-backed AnnData (H5AD) file format, as popularized by the Python scverse ecosystem. However, accessing these datasets from R, allowing users to take advantage of the strengths of each language, can be difficult. anndataR facilitates this access by allowing users to natively read and write H5AD files in R, convert them to and from SingleCellExperiment or Seurat objects, or even work with the resulting R AnnData object directly. We perform rigorous testing to ensure compatibility between Python-written and R-written H5AD files, guaranteeing long-term interoperability between languages. AVAILABILITY AND IMPLEMENTATION: anndataR's source code is available on GitHub at scverse/anndataR under the MIT license. It is compatible with R version 4.5, has been archived at 10.5281/zenodo.18775712 and included within Bioconductor: 10.18129/B9.bioc.anndataR. Installation instructions and tutorials can be found in the online documentation at anndatar.scverse.org. Issues can be reported at the GitHub repository. Code to reproduce the analyses performed can be found on GitHub at LouiseDck/anndataR-paper, archived at 10.5281/zenodo.18792241.
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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.