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
Single-cell CellFie is a computational tool for studying metabolic tasks using Python, inspired by the original implementation of CellFie, another tool originally developed in MATLAB by the Lewis Lab. This version is designed to be compatible with single-cell and spatial data analysis using Scanpy, while including a series of improvements and new analyses.
This image was created with the assistance of DALL·E
Installation
To install scCellFie, use pip:
pip install sccellfie
Features
Single cell and spatial data analysis: Tailored for analysis of metabolic tasks using fully single cell resolution and in space.
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 ~5 min.
New analyses: From marker selection of relevant metabolic tasks to integration with inference of cell-cell communication.
User-friendly: Python-based for easier use and integration into existing workflows.
Scanpy compatibility: Fully integrated with Scanpy, the popular single cell analysis toolkit.
How to cite
Preprint is coming soon!
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. Metabolic Engineering, 2024. https://doi.org/10.1016/j.ymben.2023.12.006
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Hashes for scCellFie-0.2.1-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 3e829e4c7bf84223f3c3775dd4031202eec11fb6e8f696dd50610d08a3df102d |
|
MD5 | fd82cb42e6f245c0862443479a361b0a |
|
BLAKE2b-256 | d487910ad4616c691d56120cb4abc5ccc72370eccda8009a156f645c106101ca |