Isaac Virshup

anndataR improves interoperability between R and Python in single-cell transcriptomics

anndataR enables interoperability between R and Python by allowing native reading and writing of H5AD files in R, with compatibility testing and conversion to R single-cell objects.

anndata: Annotated data

The paper introduces anndata, a Python package for handling annotated data matrices, providing features like sparse data support and a PyTorch interface.

SpatialData: an open and universal data framework for spatial omics

SpatialData, a Zarr/OME-NGFF-based format plus Python library, unifies images, labels, points, shapes and tables across spatial omics platforms with coordinate alignment, lazy loading and cross-modal aggregation.

OME-Zarr: a cloud-optimized bioimaging file format with international community support

This paper describes OME-Zarr, a cloud-optimized bioimaging file format developed through community collaboration to improve scalability and data access.

Matrix and analysis metadata standards (MAMS) to facilitate harmonization and reproducibility of single-cell data

The paper introduces MAMS, a metadata standard for single-cell data matrices and analysis workflows, to improve reproducibility and interoperability across datasets.

Squidpy: a scalable framework for spatial omics analysis

Squidpy extends Scanpy/AnnData with spatial neighbor graphs and a lazy-loading image container, enabling spatial statistics, ligand-receptor tests, image features, and ~10-fold faster neighborhood enrichment than Giotto.

constclust: Consistent Clusters for scRNA-seq

constclust identifies robust cell clusters in scRNA-seq data by reconciling clustering results across parameter variations, improving accuracy and reproducibility with lower computational cost.