Joel Mefford

The paper estimates the covariance between liability to a disorder and age at onset in censored populations using a mixture distribution model applied to twin data.

This study identifies synergistic sets of genetic risk variants in psychiatric disorders, suggesting subtypes and reinterpreting shared genetic effects.

This study quantifies the heritability of drug response to statins, metformin, warfarin, and methotrexate in UK Biobank participants and identifies genetic modifiers of drug effects and side effects.

The paper introduces QuadKAST, a scalable algorithm for detecting epistasis in complex traits, and identifies 32 trait-gene pairs with significant quadratic effects in UK Biobank data.

The paper identifies causal genes at QTLs associated with fear-related behavior using complementation testing and finds six genes, including four with known synaptic roles and one long non-coding RNA.

This study identifies six novel genetic loci, including two rare variants, and shows that a polygenic risk score strongly predicts prostate cancer risk.

GBAT improves detection of trans-gene regulation by addressing multiple testing, read-mapping biases, and confounders in eQTL analysis.

The paper tests gene expression prediction models' performance across populations and finds poor generalizability to African Americans compared to European Americans.

This paper introduces CelFiE, a method to estimate cell type contributions to cfDNA, showing it can detect rare cell types and find increased skeletal muscle cfDNA in ALS patients.

This study identifies 588 SNP-metabolite associations using the METSIM cohort, revealing pleiotropy, temporal changes, and age-related genetic control shifts.

The paper identifies a bias in using principal components (PCs) for confounder correction in genomic studies, showing that it can lead to false positives, especially for large genetic effects.

This paper introduces a reference-free method for generating polygenic risk scores (PRS) that avoids over-fitting and computational inefficiencies, and demonstrates applications in pleiotropy detection and mixed-model association testing.