spateo 离线安装包

<p align="center"> <img height="150" src="https://github.com/aristoteleo/spateo-release/blob/main/docs/_static/logo.png" /> </p [](https://spateo-release.readthedocs.io/en/latest/) [Installation](https://spateo-release.readthedocs.io/en/latest/installation.html) - [Tutorials](https://spateo-release.readthedocs.io/en/latest/tutorials/index.html) - [API](https://spateo-release.readthedocs.io/en/latest/autoapi/spateo/index.html) - [Citation](https://linkinghub.elsevier.com/retrieve/pii/S0092-8674(22)00399-3) - [Technical](https://spateo-release.readthedocs.io/en/latest/technicals/index.html) # spateo-release Spatiotemporal modeling of spatial transcriptomics Cells do not live in a vacuum, but in a milieu defined by cell–cell communication that can be quantified via recent advances in spatial transcriptomics. Here we present spateo, a open source framework that welcomes community contributions for quantitative spatiotemporal modeling of spatial transcriptomics. Leveraging the ultra-high spatial-resolution, large field of view and high RNA capture sensitivity of stereo-seq, spateo enables single cell resolution spatial transcriptomics via nuclei-staining and RNA signal based cell segmentation. Spateo also delivers novel methods for spatially constrained clustering to identify continuous tissue domains, spatial aware differential analyses to reveal spatial gene expression hotspots and modules, as well as the intricate ligand-receptor interactions. Importantly, spateo is equipped with sophisticated methods for building whole-body 3D models of embryogenesis by leveraging serial profilings of drosophila embryos across different stages. Spateo thus enables us to evolve from the reductionism of single cells to the holisticism of tissues and organs, heralding a paradigm shift in moving toward studying the ecology of tissue and organ while still offering us the opportunity to reveal associated molecular mechanisms. ## Spateo Development Process - Follow feature-staging-main review process - create a specific branch for new feature - implement and test on your branch; add unit tests - create pull request - discuss with lab members and merge into the main branch once all checks pass - Follow python [Google code style](https://google.github.io/styleguide/pyguide.html) ## Code quality - File and function docstrings should be written in [Google style](https://google.github.io/styleguide/pyguide.html) - We use `black` to automatically format code in a standardized format. To ensure that any code changes are up to standard, use `pre-commit` as such. ``` # Run the following two lines ONCE. pip install pre-commit pre-commit install ``` Then, all future commits will call `black` automatically to format the code. Any code that does not follow the standard will cause a check to fail. ## Unit testing Unit-tests should be written for most functions. To run unit tests, simply run the following. ``` # Install ONCE. pip install -r dev-requirements.txt # Run test make test ``` Any failing tests will cause a check to fail.