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BayesTME: A unified statistical framework for spatial transcriptomics

tests Documentation Status DOI

This package implements BayesTME, a fully Bayesian method for analyzing ST data without needing single-cell RNA-seq (scRNA) reference data.

Documentation

Citation

If you use this code, please cite the manuscript:

Zhang H, Hunter MV, Chou J, Quinn JF, Zhou M, White RM, Tansey W. BayesTME: An end-to-end method for multiscale spatial transcriptional profiling of the tissue microenvironment. Cell Syst. 2023 Jul 19;14(7):605-619.e7. doi: 10.1016/j.cels.2023.06.003. PMID: 37473731; PMCID: PMC10368078.

Bibtex citation:

@article{Zhang:2023aa,
	author = {Zhang, Haoran and Hunter, Miranda V and Chou, Jacqueline and Quinn, Jeffrey F and Zhou, Mingyuan and White, Richard M and Tansey, Wesley},
	journal = {Cell Syst},
	month = {Jul},
	number = {7},
	pages = {605--619},
	title = {BayesTME: An end-to-end method for multiscale spatial transcriptional profiling of the tissue microenvironment.},
	volume = {14},
	year = {2023}}

Developer Setup

Please run make install_precommit_hooks from the root of the repository to install the pre-commit hooks.

When you run any git commit command these pre-commit hooks will run and format any files that you changed in your commit.

Any unchanged files will not be formatted.

Internal Contributions

When contributing to this repository, please use the feature branch workflow documented here: https://github.com/tansey-lab/wiki/blob/master/FEATURE_BRANCH_WORKFLOW.md