Quality control analysis for AIND HCR data processing. Provides tools for validating tile alignment, camera alignment, segmentation, spectral unmixing, and spot detection.
Use Cases:
-
Interactive analysis - Within a CodeOcean capsule/cloud workstation (or local machine):
- Make sure processed HCR data asset is attached to capsule
// run just tile_alignment python launch_qc.py --dataset HCR_788639-25_2025-06-06_13-00-00_processed_2025-06-17_07-08-14 --output-dir /root/capsule/scratch/qc-test --tile-alignment --pyramid-level 4
// run all qc python launch_qc.py --dataset HCR_788639-25_2025-06-06_13-00-00_processed_2025-06-17_07-08-14 --output-dir /root/capsule/scratch/qc-test --all --pyramid-level 0
-
Reproducible runs - With CodeOcean app panel
-
Pipeline integration - As automated QC steps (not implemented yet)
Intergration will AIND QC portal will happen when team identifies and evaluates essential plots.
See CHANGELOG.md for full details.
| Version | Date | Summary |
|---|---|---|
| v0.7.0 | 04/02/2026 | S3 QC plot management, integrated dataset violins/pairplots, pandas 3 fix |
| v0.6.0 | 03/18/2026 | Cluster similarity module, GMM thresholding, spectral unmixing spot-reassignment |
| v0.4.0 | 10/16/2025 | Metadata parsing, soma classifier, HCR cell filters |
| v0.3.9 | 08/11/2025 | Spot detection viz, segmentation overview, single-cell expression plots |
| v0.3.8 | 08/08/2025 | Refactor to viz api |
| v0.3.7 | 08/01/2025 | Spot metric distributions, cluster centroid plots, cell x gene analysis |
To use the software, in the root directory, run
pip install -e .To develop the code, run
pip install -e .[dev]Run pre_commit_checks.py, which includes coverage, black, isort, flake8, & interrogate
- Internal members please create a branch.
- External members please fork the repository and open a pull request from the fork.
We'll primarily use Angular style for commit messages. Roughly, they should follow the pattern:
<type>: <short summary>
type is one of:
- build: Changes that affect build tools or external dependencies (example scopes: pyproject.toml, setup.py)
- ci: Changes to our CI configuration files and scripts (examples: .github/workflows/ci.yml)
- docs: Documentation only changes
- feat: A new feature
- fix: A bugfix
- perf: A code change that improves performance
- refactor: A code change that neither fixes a bug nor adds a feature
- test: Adding missing tests or correcting existing tests