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

Model Architecture

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.