hdWGCNA identifies co-expression networks in high-dimensional transcriptomics data

Biological systems are immensely complex, organized into a multi-scale hierarchy of functional units based on tightly regulated interactions between distinct molecules, cells, organs, and organisms. While experimental methods enable transcriptome-wide measurements across millions of cells, popular bioinformatic tools do not support systems-level analysis. Here we present hdWGCNA, a comprehensive framework for analyzing co-expression networks in high-dimensional transcriptomics data such as single-cell and spatial RNA sequencing (RNA-seq). hdWGCNA provides functions for network inference, gene module identification, gene enrichment analysis, statistical tests, and data visualization. Beyond conventional…

• DM
  Dr. Miriam and Sheldon G. Adelson Medical Research Foundation
• UC
  Uganda Cancer Institute
• UO
  University of California, Irvine
• NI
  National Institute on Aging

  Awards: 1RF1AG071683, 3U19AG068054-02S, U54 AG054349-06
• NI
  National Institute on Drug Abuse

  Award: 1U01DA053826
• NI
  National Institute of Neurological Disorders and Stroke

  Award: P01NS084974- 06A1