Graph-linked unified embedding for unpaired single-cell multi-omics data integration
Project description
GLUE (Graph-Linked Unified Embedding)
Graph-linked unified embedding for single-cell multi-omics data integration
For more details, please check out our preprint.
Directory structure
.
├── scglue # Main Python package
├── data # Data files
├── evaluation # Method evaluation pipelines
├── experiments # Experiments and case studies
├── tests # Unit tests for the Python package
├── docs # Documentation files
├── custom # Customized third-party packages
├── packrat # Reproducible R environment via packrat
├── env.yaml # Reproducible Python environment via conda
├── setup.py # Setup script for the Python package
├── release.sh # Script for releasing a new version
├── LICENSE
└── README.md
Package installation
It is recommended to install scglue
within a
conda environment.
First, initialize an empty conda environment (here named "scglue"):
conda env create -n scglue "python>=3.6" && conda activate scglue
Then, install scglue via:
pip install scglue
Package usage
Please checkout the documentations and tutorials at scglue.readthedocs.io.
Package development
Install scglue in editable form via flit:
pip install flit && flit install -s
Run unit tests:
pytest --cov="scglue" --cov-report="term-missing" tests [--cpu-only]
Build documentation:
sphinx-build -a -b html docs docs/_build
Reproduce results
-
Checkout the repository to v0.1.1:
git checkout tags/v0.1.1
-
Create a local conda environment using the
env.yaml
file, and then install scglue:conda env create -p conda -f env.yaml && conda activate ./conda flit install -s
-
Set up a project-specific R environment:
packrat::restore() # Packrat should be automatically installed if not available. install.packages("data/download/Saunders-2018/DropSeq.util_2.0.tar.gz", repos = NULL) install.packages("custom/Seurat_4.0.2.tar.gz", lib = "packrat/custom", repos = NULL)
R 4.0.2 was used during the project, but any version above 4.0.0 should be compatible.
-
Follow instructions in
data
to prepare the necessary data. -
Follow instructions in
evaluation
for method evaluation. -
Follow instructions in
experiments
for case studies.
Project details
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