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The gene-regulatory landscape of the brain is highly dynamic in health and disease, coordinating a menagerie of biological processes across distinct cell types. Understanding these regulatory programs requires a holistic experimental and analytical approach. Here, we present a single-cell study of 380,000 nuclei in late-stage Alzheimer’s Disease (AD) using parse biosciences whole transcriptome kit, profiling gene expression in thousands of genes and uncovering vast neuronal and glial heterogeneity in late-stage AD.
We introduce a co-expression network analysis strategy for single-cell data (hd-WGCNA) to perform a systems-level meta-analysis of AD transcriptomics to uncover underlying regulatory architecture. hd-WGCNA is based on a meta-analytical approach to jointly form co-expression networks in metacells constructed from the integrated snRNA-seq dataset as well as bulk-tissue RNA-seq data of the human cortex, where each edge in a co-expressed module is supported by both bulk RNA-seq data and snRNA-seq data. Finally, this work provides an unbiased single-cell atlas of transcriptomic regulation of AD in distinct brain regions.