high dimensional WGCNA (hdWGCNA)


hdWGCNA is an R package for performing weighted gene co-expression network analysis (WGCNA) in high dimensional transcriptomics data such as single-cell RNA-seq or spatial transcriptomics. hdWGCNA is highly modular and can construct co-expression networks across multi-scale cellular and spatial hierarchies. hdWGNCA identifies robust modules of inerconnected genes, and provides context for these modules through various biological knowledge sources. hdWGCNA requires data formatted as Seurat objects, one of the most ubiquitous formats for single-cell data. Check out the hdWGCNA in single-cell data tutorial or the hdWGCNA in spatial transcriptomics data tutorial to get started. Note: hdWGCNA is under active development, so you may run into errors and small typos. We welcome users to write GitHub issues to report bugs, ask for help, and to request potential enhancements. If you use hdWGCNA in your research, please cite the following papers in addition to the original WGCNA publication:

Morabito et al. bioRxiv 2022

Morabito & Miyoshi et al. Nature Genetics 2021

Visit hdWGCNA Github page here