{"categories":[{"label":"Bio-Informatics","url":"https://skillfed.io/packages/category/scientific-engineering-bio-informatics"}],"enrichment":{"capability":"MuData is a container for multimodal omics data that organizes multiple AnnData objects (one per modality) with shared and modality-specific observations and features, and provides HDF5-based I/O via .h5mu files.","skillfed_tags":["single-cell-genomics","multimodal-data","scverse"],"use_cases":["Store and retrieve 10X Genomics multiome data (RNA + ATAC) with shared cell metadata and modality-specific feature annotations.","Combine multiple single-cell assays measured on the same cells into one analysis-ready container with linked observations.","Save multimodal analysis results to disk in a structured HDF5 format and selectively read individual modalities back.","Organize metadata for multimodal experiments where cell-level annotations apply across all assays but feature annotations differ per modality.","Build reproducible multimodal analysis pipelines that preserve data structure and metadata through multiple processing steps."],"what_it_does":"MuData extends the AnnData single-cell data structure to handle multimodal omics experiments where multiple assays (RNA, ATAC, protein, etc.) are measured on the same cells. It stores each modality as a separate AnnData object within a unified container, allowing shared cell and feature metadata while preserving modality-specific annotations. The package provides HDF5-based persistence through .h5mu files, which mirror the .h5ad format but support hierarchical storage of multiple modalities.\n\nTypically used in single-cell genomics workflows where data from technologies like 10X Genomics multiome (RNA + ATAC) or other multi-assay platforms need to be loaded, processed, and stored together. The package is part of the scverse ecosystem and integrates with muon for convenient readers of common multimodal file formats. It depends on anndata, h5py, numpy, pandas, and scipy for core functionality.","worth_installing":"Yes. MuData is actively maintained, has no known vulnerabilities, and fills a clear role in the scverse ecosystem for multimodal omics data. The low install friction, permissive license, and integration with established tools like anndata and muon make it a straightforward choice if you work with multimodal single-cell data. Install it if you need to organize or persist data from multiple assays measured on the same cells."},"id":"mudata","links":{"html":"https://skillfed.io/packages/mudata","md":"https://skillfed.io/packages/mudata.md","pypi":"https://pypi.org/project/mudata/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-07-07","license_spdx":null,"license_treatment":"permissive","name":"mudata","python_support":"supports_current","summary":"Multimodal data"},"popularity":{"monthly_downloads":194170,"position":9844,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.3.10"}