S. Taylor Head

The paper shows that RNA-seq quantification methods and reference annotations significantly impact eQTL analysis, colocalization, and TWAS results across multiple tissues and phenotypes.

ICONIC is an R package that integrates instrumental variable and negative-control methods for causal inference in multi-omic studies, offering diagnostics and benchmarks for mediation analysis.

POISE infers parent-of-origin effects in unlabeled genomic data using spectral decomposition and bootstrap confidence intervals, identifying 134 new variants in lipid metabolism and immune regulation from UK Biobank data.

This study performs a cell-type-aware transcriptome-wide association study (TWAS) of mammographic density phenotypes, identifying novel genes and prioritizing known GWAS loci through cell-type-specific gene expression analysis.

This study identifies genetic risk mechanisms for six cancers by analyzing isoform-level expression data, finding more associations and greater heritability explained compared to gene-level analysis.

CADET improves transcriptome-wide association studies in admixed populations by integrating local ancestry and eQTL data to enhance gene expression prediction and association testing.

This study performs cis- and trans-eQTL TWAS on breast and ovarian cancer data to identify 101 and 8 risk-associated genes, respectively, with several driven by trans-eQTLs.

The paper uses whole-exome sequencing to identify rare variants in multiplex families with orofacial clefts, finding variants in seven families but no clear evidence that subclinical phenotypes clarify inheritance patterns.

The paper estimates the diagnostic yield of sequencing 418 genes in OFC cases and controls, finding a higher prevalence of likely pathogenic variants in cases.

POIROT detects parent-of-origin effects in GWAS by comparing phenotypic covariance matrices across genotypes, showing improved power and robustness to non-normality.