Richard H. Duerr

This study identifies 619 IBD risk signals, resolves 81 high-confidence variants, and prioritizes 664 candidate effector genes using GWAS, eQTL, and exome sequencing.

This study uses exome and genome sequencing to identify 68 genes directly associated with inflammatory bowel disease, providing clearer genetic insights and therapeutic targets.

The paper analyzes over 800,000 human genomes to assess penetrance of clinically relevant variants, finding that 95% of pLoF variants in severe diseases have explanations for lack of disease manifestation.

SECANT improves clustering and annotation of single-cell multi-omics data by integrating surface protein and RNA information with biology-guided semi-supervised learning.

This study benchmarks DOGMA-seq and CITE-seq in human T cells, finding DOGMA-seq provides more information with optimized permeabilization despite slightly lower mRNA and ADT library quality.

This paper introduces GMM-Demux, a method to identify and remove multiplets in scRNA-seq data, showing improved accuracy and error reduction.

The paper identifies 7 novel IBD-causing genes in Ashkenazi Jewish IBD patients using exome sequencing and analyzes their overlap with early-onset IBD and other diseases.

BREM-SC is a Bayesian model that jointly clusters single-cell transcriptomic and proteomic data, improving accuracy and quantifying clustering uncertainty.