Colm T. O’Dushlaine

TRACE identifies archaic ancestry using ancestral recombination graphs from contemporary genomes, revealing ghost admixture and challenging existing interpretations of archaic introgression.

The paper introduces COAST-SS, a method to identify allelic series using summary statistics, showing it is effective and robust to LD matrix misspecification.

This paper shows that genome-wide association studies on ratio traits can be misleading, as associations may be driven by the denominator rather than the numerator, and proposes a method to correct for collider bias.

This study shows that machine learning-derived phenotypes for GWAS can lead to false discoveries depending on their causal relationship with the target phenotype and environment.

EmbedGEM evaluates embeddings for genetic discovery by assessing heritability and disease relevance using polygenic risk scores and genome-wide association statistics.

The paper introduces COAST, a rare variant association test for allelic series, which improves power over SKAT-O in detecting gene-trait associations in lipid and cell count traits using UK Biobank data.

This study examines proteomic variation between two Nigerian ethnic groups and identifies novel cis-pQTL associated with BMI.

The paper identifies a rare variant that lowers ACE2 expression and reduces COVID-19 risk, and develops a genetic risk score predicting severe disease.

The paper conducts a genome-wide association study of liver fat, iron, and extracellular fluid fraction using UK Biobank MRI data, identifying novel genetic loci for these traits.

The paper introduces REGENIE, a fast whole genome regression method for quantitative and binary traits, showing computational efficiency and accuracy on UK Biobank data.

This study performs whole genome sequencing of human embryonic stem cells to identify genetic variants and provides resources for cell line selection.

The paper performs exome-wide association studies in large cohorts to identify genetic variants linked to human age, finding new candidates and confirming known ones.

This study identifies rare genetic variants associated with type 2 diabetes using exome sequencing of 20,791 cases and 24,440 controls, and provides a Bayesian framework to improve variant prioritization.

This study identifies 111 genetic loci and 163 risk variants associated with atrial fibrillation using a GWAS of over 1 million individuals.

The paper analyzes cryptic relatedness in a large exome cohort, identifies numerous close relationships, reconstructs pedigrees, and demonstrates their utility in improving mutation phasing and identifying de novo mutations.

KaryoScan detects chromosomal anomalies from whole-exome sequencing, identifying aneuploidies and complex rearrangements in large cohorts.

The paper identifies and analyzes exonic copy number variants (CNVs) in 50,726 DiscovEHR participants, linking them to clinical traits and phenotypes.

The paper identifies OCD-associated genes by combining evolutionary and functional data with targeted sequencing in humans and animal models.