Tools for Integrating Single-Cell RNA-seq Studies with Genome-Wide Association Studies
To develop statistical methods and computational tools for integrating single-cell RNA-sequencing data with genome-wide association studies.
Results & Resources
The Zhou lab developed a computational method, CoCoNet, for integrating GWAS data with single-cell RNA-seq to facilitate the detection of disease-relevant tissues or cell types. Additionally, they implemented CoCoNet in a R package with underlying code to ensure scalable computation. They applied CoCoNet for an in-depth analysis of various diseases by integrating the corresponding GWASs with bulk RNA-seq data, showing that they can help identify specific cell types and disease-targeted tissues. Their work is further described in this preprint.