Anna S. E. Cuomo

Single-cell eQTL mapping in 5.4 million PBMCs from 1,925 individuals with matched WGS finds common-variant eQTLs for 83% and rare-variant signals for 47% of 21,404 genes.

The paper identifies immune cell type-specific gene expression regulated by tandem repeats using multi-omics data from large cohorts.

The paper introduces CASTIE, a method for context-dependent eQTL mapping in single-cell data, identifying regulatory variants missed by static models and linking them to disease traits.

The paper uses single-cell eQTL data to identify cell-type-specific effector genes associated with 69 diseases and 31 biomarker traits, revealing distinct immune cell contributions to disease.

The paper maps chromatin accessibility and genetic variation in immune cells, showing how integrating cell-type-specific data improves disease risk understanding.

SAIGE-QTL is a tool for single-cell eQTL analysis that directly maps eQTLs without pseudobulk aggregation and improves power for detecting rare variants.

The paper introduces MEOTIVE, a statistical framework to identify genetic effects on gene expression variability, revealing new mechanisms of genome regulation and associations with autoimmune disease risk.

CellRegMap identifies context-specific regulatory variants using scRNA-seq by analyzing allelic effects across cell types and states.

This study evaluates normalization, aggregation, and statistical methods for sc-eQTL mapping to improve eQTL discovery in single-cell RNA-seq data.

The paper uses single-cell RNA sequencing to study genetic variant effects on dopaminergic neuron differentiation from iPSCs, identifying eQTL and cell fate markers.

The paper uses single-cell RNA-seq of differentiating iPS cells from 125 donors to identify expression quantitative trait loci influencing gene expression during endoderm differentiation.