A tool for studying metabolic tasks from single-cell and spatial transcriptomics
Project description
Metabolic functionalities of mammalian cells from single-cell and spatial transcriptomics
About scCellFie
Single-cell CellFie is a Python implementation of CellFie, a tool for studying metabolic tasks originally developed in MATLAB by the Lewis Lab. This version is designed to be compatible with single-cell and spatial data analysis using Scanpy.
Installation
To install scCellFie, use pip:
pip install sccellfie
Features
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Single cell and spatial data analysis: Tailored for analysis of metabolic tasks using fully single cell resolution and in space.
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Scanpy compatibility: Fully integrated with Scanpy, the popular single cell analysis toolkit.
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User-friendly: Python-based for easier use and integration into existing workflows.
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Speed: This implementation further leverages the original CellFie. It is now memory efficient and run much faster! A dataset of ~70k single cells can be analyzed in ~30 min.
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New analyses: From marker selection of relevant metabolic tasks to integration with inference of cell-cell communication.
Acknowledgments
This implementation is inspired by the original CellFie tool developed by the Lewis Lab. Please consider citing their work if you find this tool useful:
- Model-based assessment of mammalian cell metabolic functionalities using omics data. Cell Reports Methods, 2021. https://doi.org/10.1016/j.crmeth.2021.100040
- ImmCellFie: A user-friendly web-based platform to infer metabolic function from omics data. STAR Protocols, 2023. https://doi.org/10.1016/j.xpro.2023.102069
- Inferring secretory and metabolic pathway activity from omic data with secCellFie. bioRxiv, 2023. https://doi.org/10.1101/2023.05.04.539316
Project details
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