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Changelog

All notable changes to this project will be documented in this file.

The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.

[1.0.5] - December 29, 2025

Updated

"assembly" argument is optional. Assembly is inferred from Cooler if possible, with fallback to optional argument.

[1.0.4] - October 31, 2025

Added

Add: support for NCBI or UCSC genomes by name, based off of: https://github.com/open2c/bioframe/blob/main/bioframe/io/data/_assemblies.yml
Add Hoang Tran as a package author

[1.0.3] - October 15, 2025

Fixed

Python 3.10 or higher is required. Update pyproject.toml & documentation to reflect this.

[1.0.2] - April 30, 2025

Added

Examples

immune-joint-analysis: Demonstrates the use of the jointly-hic toolkit for joint analysis of CD4+ and CD8+ T cell Hi-C and ChIP-seq data available via the ENCODE portal.
breast-tissue-joint-analysis: Demonstrates the use of the jointly-hic toolkit for joint analysis of human breast tissue Hi-C data (Choppavarapu et al.), along with breast tissue and MCF-7 cell ChIP-seq, RNA-seq, DNase-seq, and ATAC-seq data from the ENCODE portal.

[1.0.0] - April 11, 2025

Added

Core Features

Command-line interface (jointly) with six core subcommands:
- embed: Joint decomposition of Hi-C matrices using PCA, NMF, or SVD
- post-process: UMAP dimensionality reduction and k-means clustering
- trajectory: Trajectory inference using k-means and UMAP projections
- embedding2yaml: Extract metadata from embeddings to generate experiment YAML
- tracks2yaml: Convert CSV metadata into YAML for signal track ingestion
- hdf5db: Build a compressed HDF5 database (JointDb) integrating Hi-C embeddings and epigenetic signal data

Input & Output

Support for multi-resolution .mcool Hi-C input files
Outputs include .parquet, .csv.gz, .pkl.gz, .png, and .h5 formats
Compatibility with ENCODE bigwig tracks
Configurable percentile-based filtering, chromosome restrictions, and mini-batch sizing

Visualization

Generates UMAP visualizations with color-coded cluster and sample metadata
Supports multi-neighbor UMAP and multi-k clustering in a single run

Integration

hdf5db output for joint Hi-C + epigenomics database format (JointDb)

Scalability

Out-of-core, fixed-memory matrix decomposition
Designed for time courses, tissue atlases, and multi-condition comparisons

Distribution

Published on PyPI
Available as a Docker image on GitHub Container Registry (GHCR)

CI/CD

Continuous integration with test and linting checks on every PR and push to main
Automatic GitHub release tagging, PyPI publication, and Docker publishing via GitHub Actions

[Unreleased] - MMMM DD, YYYY

TBD: Next milestone features will be added here as development progresses.