Nicholas Mancuso

This paper evaluates transcriptome-wide association studies (TWAS) for causal gene prioritization, showing its strengths and limitations in identifying causal genes at GWAS loci.

This paper introduces a probabilistic framework to fine-map transcriptome-wide association study signals, prioritizing causal genes while accounting for linkage disequilibrium and pleiotropy.

The paper characterizes genetic control of gene expression and splicing in developing human brains using eQTL and sQTL analysis, identifying novel regulatory regions and links to neuropsychiatric disorders.

The paper quantifies the overlap between GWAS genes for 62 complex traits and Mendelian disorder genes, finding significant enrichment and elevated effect sizes for phenotypically-matched genes.

This study integrates a large prostate cancer GWAS with gene expression data to identify 235 genes associated with risk, prioritizing causal genes through Bayesian credible sets.

This paper introduces a method to quantify local genetic correlations between complex traits using GWAS summary data, identifying genomic regions contributing to genetic correlations and inferring causality.

This study investigates the role of rare genetic variation in prostate cancer heritability using targeted sequencing of GWAS risk regions across multiple ancestries.