News
Latest update: A Chinese manual is now available at https://scglue.readthedocs.io/zh_CN/latest/!
最新更新: GLUE的官方中文手册已上线,请见https://scglue.readthedocs.io/zh_CN/latest/!
Graph-linked unified embedding for single-cell multi-omics data integration
For more details, please check out our publication.
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├── 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
├── pyproject.toml # Python package metadata
├── LICENSE
└── README.md
The scglue
package can be installed via conda using one of the following commands:
conda install -c conda-forge -c bioconda scglue # CPU only
conda install -c conda-forge -c bioconda scglue pytorch-gpu # With GPU support
Or, it can also be installed via pip:
pip install scglue
Installing within a conda environment is recommended.
Please checkout the documentations and tutorials at scglue.readthedocs.io.
A Chinese version is also available here.
Install scglue in editable form via flit (first install flit via conda or pip if not installed already):
flit install -s
Run unit tests:
pytest --cov="scglue" --cov-report="term-missing" tests [--cpu-only]
Build documentation:
sphinx-build -b gettext docs docs/_build/gettext
sphinx-intl update -p docs/_build/gettext -l zh_CN -d docs/locale
sphinx-build -b html -D language=en docs docs/_build/html/en # English version
sphinx-build -b html -D language=zh_CN docs docs/_build/html/zh_CN # Chinese version
Checkout the repository to v0.2.0:
git checkout tags/v0.2.0
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.