Keon Arbabi

brisc is a multithreaded CPU toolkit for single-cell analysis that is faster and more reproducible than existing tools like Scanpy and Seurat.

The paper identifies reduced SST mRNA and depletion of specific upper-layer Sst interneurons in schizophrenia using single-nucleus RNA-seq and spatial transcriptomics.

The paper maps cellular and molecular changes in the mouse brain during pregnancy and postpartum using spatial single-cell technologies, identifying three gene expression programs and linking depression risk genes to specific brain regions.

This study identifies 26 risk loci for fibromyalgia through a genome-wide association analysis of 2.5 million individuals, revealing genetic links to neural functions and chronic pain disorders.

This study benchmarks GWAS causal gene prioritization methods for drug discovery using 445 diseases, finding the nearest gene method performs as well as more complex approaches.

The paper shows that within-cell-type electrophysiological heterogeneity is malleable and can be restored by blocking HCN currents in epilepsy models.

This study maps the regenerative response to newborn brain injury in mice using spatial transcriptomics, revealing niche-specific changes in cell states, composition, and spatial organization.

The paper quantifies microglial contamination in Patch-seq datasets and shows its impact on electrophysiological properties of neurons.

The paper applies sparse k-means clustering to human brain development data to identify age-related clusters and reveal lifespan-stage changes in the visual cortex.