Dylan H. de Vries

The paper identifies co-expression QTLs (co-eQTLs) using single-cell RNA-seq data, revealing how genetic variants affect gene co-expression patterns and regulatory networks in specific cell types.

The paper uses blood eQTL meta-analysis to explore the polygenic architecture of complex traits, finding that trans-eQTLs are more informative for identifying causal genes than cis-eQTLs.

The paper uses single-cell RNA-sequencing to show that gene expression in immune cells is influenced by genetic variation and pathogen exposure, revealing context-specific regulatory mechanisms.

The paper introduces Decon2, a method to deconvolute bulk blood eQTL effects into immune cell subpopulations, showing high concordance with experimental and single-cell studies.

The paper analyzes de novo mutations in developmental disorders using exome sequencing of 4,293 families, identifying 94 genes and estimating a birth prevalence of 0.22-0.47%.

The paper uses single-cell RNA sequencing to identify cell-type specific cis-eQTLs in peripheral blood mononuclear cells and validates them against whole blood RNA-seq data.