bsml320 / scGWAS

A method which leverages scRNA-seq data to achieve two goals: (1) to infer the cell types in which the disease-associated genes manifest and (2) to construct cellular modules which imply disease-specific activation of different processes.

scGWAS: scRNA-seq assisted GWAS analysis

scGWAS leverages scRNA-seq data to identify the genetically mediated associations between traits and cell types.

Install

scGWAS is a java package and does not need to install. Users only need to set up the Java Running Environment, which can be downloaded here.

Running example:

To run the package only one command line is needed:

java -jar scGWAS_r0.jar configure.txt

All parameters are provided to JAR through the configure file. Please check here for available parameters.

Notes

• The JAR package is in the folder code
• A runnable example can be found in the folder example
• The folder analysis includes all codes for preparing the input files, post-processing including the proportional test, exploration of random modules and NES calculaiton, and figure preparation.
• We provide 18 scRNA-seq panels that were already pre-processed and ready for applications. These panels were collected for 9 major tissues and can be sufficient for the majority of complex diseases and traits. If you still need to process your own panel of scRNA-seq data, please follow the code in the folder analysis to prepare and normalize the input data.
• We also provide other supporting files, including the reference network and house-keeping genes that were generally suggested to be excluded.

Citation

The underlying method is described in Jia P et al. Landscape of trait-cell type associations by integrating single-cell transcriptomics-wide and genome-wide association studies (scGWAS)

Contact

Please contact Peilin Jia ([e-mail]) or Zhongming Zhao ([e-mail]) if you have any questions.