Jonathan D. Rosen

The paper introduces standardized formats and tools for processing MPRA data to improve reproducibility and integration across studies.

The paper shows larger eQTL studies detect more signals that colocalize with GWAS signals, improving understanding of gene-trait relationships.

This study identifies 557 new gene-trait associations for hematological traits using transcriptome-wide association analysis in UK Biobank data.

The paper improves genotype imputation for CF patients using the TOPMed reference panel and a CF-specific imputation panel, enhancing marker coverage and PRS accuracy.

HPRep quantifies reproducibility in HiChIP and PLAC-seq data by using a stratified and weighted correlation metric, outperforming existing Hi-C-based measures.

This paper performs a large-scale TWAS of blood cell phenotypes, identifies 239 gene-trait associations, and develops an R Shiny app to visualize TWAS results.

This study characterizes 3D epigenomic landscapes during human corticogenesis, revealing chromatin looping and super interactive promoters involved in lineage-specific gene regulation.

This study identifies 5,552 blood-cell trait-variant associations across 746,667 individuals from 5 global populations, including 71 novel loci and ancestry-specific variants not found in European ancestry populations.

This study identifies 5,106 new genetic variants associated with blood cell traits using large-scale GWAS, highlighting the polygenic and monogenic basis of hematopoiesis.

This study uses TOPMed whole genome sequences to improve imputation quality and detect rare variant associations in admixed African and Hispanic/Latino populations, identifying two novel associations with hematological traits.

The paper develops an improved Hi-C protocol and bias-correction pipeline to map chromatin loops in human neurogenesis and brain tissues, showing their role in neural differentiation and GWAS gene identification.