Genetics-informed pathogenic spatial mapping
Project description
gsMap
Introduction
gsMap (genetically informed spatial mapping of cells for complex traits)
integrates spatial transcriptomics (ST) data with genome-wide association study (GWAS)
summary statistics to map cells to human complex traits, including diseases,
in a spatially resolved manner.
Key Features
- Spatially-aware High-Resolution Trait Mapping
- Spatial Region Identification
- Putative Causal Genes Identification
Installation
Install using pip:
conda create -n gsMap python>=3.10
conda activate gsMap
pip install gsMap
Install from source:
git clone https://github.com/LeonSong1995/gsMap.git
cd gsMap
pip install -e .
Verify the installation by running the following command:
gsmap --help
Usage
Please check out the documentation and tutorials at gsMap Documentation.
Online Visualization
To visualize the traits-cell association spatial maps, please refer to gsMap Visualization.
Citation
Song, L., Chen, W., Hou, J., Guo, M. & Yang, J. Spatially reso lved mapping of cells associated with human complex traits. medRxiv, 2024.2010.2031.24316538 (2024) (Nature in press).
Please cite the paper and give us a STAR if you find gsMap useful for your research.
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