Thomas Lumley

Using a "one-strain-many-compounds" (OSMAC) approach to screen a collection of diverse fungi from Aotearoa New Zealand for antibacterial activity against Escherichia coli

The paper screens 32 New Zealand fungi for antibacterial activity against E. coli using OSMAC, finding several active isolates and highlighting media effects on bioactivity.

A One-Shot Lossless Algorithm for Cross-Cohort Learning in Mixed-Outcomes Analysis

This paper introduces mixWAS, a one-shot, lossless algorithm for integrating distributed EHR datasets to identify cross-cohort genetic associations across multiple outcomes.

Beyond consensus sequence: a quantitative scheme for inferring transmission using deep sequencing in a bacterial transmission model

The paper develops a model to infer bacterial transmission using deep sequencing data from a mouse model, showing that within-host variant abundance differences can accurately identify transmission pairs.

Chromatin interactions and expression quantitative trait loci reveal genetic drivers of multimorbidities

The paper identifies genetic drivers of multimorbidities by analyzing chromatin interactions and eQTL data to uncover regulatory interactions across multiple phenotypes.

A Comprehensive Evaluation of the Genetic Architecture of Sudden Cardiac Arrest

This study evaluates the genetic architecture of sudden cardiac arrest through GWAS and Mendelian randomization, finding genetic correlations with CAD, height, BMI, and electrical instability traits.

FastSKAT: Sequence kernel association tests for very large sets of markers

FastSKAT improves SKAT's efficiency by approximating tail probabilities with fewer eigenvalues, enabling faster analysis of large genetic datasets.

A Bayesian approach to multivariate and multilevel modelling with non-random missingness for hierarchical clinical proteomics data

The paper introduces a Bayesian multivariate multilevel model to analyze hierarchical clinical proteomics data with non-random missingness, showing improved performance over existing methods.