BiocPy: Facilitate Bioconductor Workflows in Python

BiocPy brings Bioconductor's core data structures and analysis tools to the Python ecosystem. These structures, including BiocFrame and GenomicRanges, serve as essential and foundational data structures, acting as the building blocks for extensive and complex representations. For example, container classes like SummarizedExperiment, SingleCellExperiment, and MultiAssayExperiment represent single or multi-omic experimental data and metadata.

Note

Resources:

• 🔥 Workshop tutorials from Bioc2024
• 📚 [WIP] BiocPy book - Tutorials and guides

Core Packages

For a complete list of packages, visit our GitHub organization.

Data Structures

Package	Description	PyPI	Links
BiocFrame	Bioconductor-like data frames		GitHub | Docs
IRanges	Interval arithmetic operations		GitHub | Docs | Bioconductor
GenomicRanges	Genomic location analysis		GitHub | Docs | Bioconductor

Containers

Package	Description	PyPI	Links
SummarizedExperiment	Genomic experiments container		GitHub | Docs | Bioconductor
SingleCellExperiment	Single-cell genomics container		GitHub | Docs | Bioconductor
SpatialExperiment	Spatial transcriptomics container		GitHub | Docs | Bioconductor
SpatialFeatureExperiment	Extends Spatial transcriptomics container		GitHub | Docs | Bioconductor
MultiAssayExperiment	Multi-omics data framework		GitHub | Docs | Bioconductor

R Interoperability

Package	Description	PyPI	Links
rds2py	Read RDS files directly in Python		GitHub | Docs
BiocUtils	Common utilities mirroring R's base functionality		GitHub | Docs
mopsy	Matrix operations with R-like syntax		GitHub | Docs
pyBiocFileCache	Resource caching system		GitHub | Docs | Bioconductor
txdb	Genome annotations from TxDB objects		GitHub | Docs

Delayed Operations

Package	Description	PyPI	Links
DelayedArray	Delayed operations in Python		GitHub | Docs | Bioconductor
HDF5Array	HDF5-backed arrays		GitHub | Docs | Bioconductor
TileDBArray	TileDB-backed arrays		GitHub | Docs | Bioconductor

---

Get Started

All packages in the BiocPy are published to BiocPy PyPI org. Install the core packages using the biocpy wrapper:

pip install biocpy

Individual packages can be installed separately. See each package's documentation for specific installation instructions.

Environments

We provide conda/mamba configuration files to create environments containing most BiocPy (& friends) packages. Check out the environments repository for more information.

---

Friends of BiocPy

BiocPy integrates with several analysis tools and frameworks

Analysis Tools

• libscran: Multi-model single-cell analysis in R, Python and JavaScript.
• SingleR-inc: Cell type annotation for single-cell data.

Data Management

• ArtifactDB: Language-agnostic access to data across computational environments.
• tatami-inc: Read various matrix representations through a common interface.

Model Training

• CellArr: TileDB-based genomic data storage with AI/ML dataloaders.

---

Contributing

We welcome contributions! Check out our developer guide to get started.