MACTA_py (Multi-tool Automated Cell Type Annotation in Python)

The goal of this code is to assemble multiple python-based cell type annotation tools into one in silico pipeline.

Auto-Annotation Tools Currently Implemented:

• celltypist

Installation for Development

git clone https://github.com/AleksBekker/MACTA_py
pipenv install -d
pipenv run pip install ".[EXTRAS_YOU_WILL_BE_USING]"

Citations

Anndata

Isaac Virshup, Sergei Rybakov, Fabian J. Theis, Philipp Angerer, F. Alexander Wolf bioRxiv 2021.12.16.473007; doi: https://doi.org/10.1101/2021.12.16.473007

Cellassign

Zhang, A.W., O’Flanagan, C., Chavez, E.A. et al. Probabilistic cell-type assignment of single-cell RNA-seq for tumor microenvironment profiling. Nat Methods 16, 1007–1015 (2019). https://doi.org/10.1038/s41592-019-0529-1

Celltypist

Cross-tissue immune cell analysis reveals tissue-specific adaptations and clonal architecture in humans. bioRxiv, 2021.2004.2028.441762 (2021). https://www.biorxiv.org/content/10.1101/2021.04.28.441762v2

Scanpy

Wolf, F., Angerer, P. & Theis, F. SCANPY: large-scale single-cell gene expression data analysis. Genome Biol 19, 15 (2018). https://doi.org/10.1186/s13059-017-1382-0

SCVI

Romain Lopez, Jeffrey Regier, Michael B Cole, Michael Jordan, Nir Yosef. "Bayesian Inference for a Generative Model of Transcriptome Profiles from Single-cell RNA Sequencing." In submission. Preprint available at https://www.biorxiv.org/content/early/2018/03/30/292037

SCVI-Tools

Gayoso, Adam, et al. “A Python Library for Probabilistic Analysis of Single-Cell Omics Data.” Nature Biotechnology, Feb. 2022, https://doi.org/10.1038/s41587-021-01206-w.

Other Packages

Please refer to the repo's dependency tree (github.com/AleksBekker/MACTA_py/network/dependencies) for information on all other packages used, including:

• Pandas
• Pydantic