Joseph G. Ibrahim

This study integrates polygenic risk scores and proteomic risk scores to improve prediction of complex traits across diverse populations.

This paper maps genetic, proteomic, and metabolomic effects along human white-matter tracts using UK Biobank data, revealing localized associations with neurodegenerative and psychiatric traits.

Canopy2 infers tumor phylogeny using bulk DNA and single-cell RNA sequencing data, outperforming existing methods in reconstructing clonal trees.

MRLocus estimates gene-to-trait mediation effects using Bayesian methods on eQTL and GWAS data, showing high accuracy and better uncertainty estimation in simulations and real applications.

The paper introduces a method to detect and classify differential epigenomic activity across multiple conditions, showing improved performance and speed compared to existing tools.

The paper introduces FSCseq, a model-based clustering method for RNA-seq data that selects informative genes, accounts for normalization factors, and identifies cancer subtypes.

ICeD-T improves immune cell abundance estimation in tumor samples by handling aberrant gene expression patterns, outperforming existing methods in simulations and real data.

The paper introduces a nonparametric method for RNA-seq differential expression analysis that accounts for inferential uncertainty, showing improved false discovery rate control compared to existing methods.

apeglm replaces DESeq2's Normal prior on log fold changes with an adaptive Cauchy prior, reducing variance for low-count genes while preserving true large effect sizes.

The paper examines the heritability of regional brain volumes using genetic and neuroimaging data from multiple cohorts, finding high heritability and consistent patterns across populations.