Chris C. Holmes

BARTharm improves MRI data harmonization by using image quality metrics and Bayesian non-parametric models, outperforming ComBat in removing scanner-induced bias while preserving biological signals.

This study identifies six novel genetic loci associated with BMI change over adulthood using UK Biobank health records, finding lower heritability for BMI change compared to baseline BMI.

This study shows that optimal polygenic score strategies vary by trait and ancestry, with smaller African-ancestry training sets outperforming larger European-ancestry sets for some traits.

This paper investigates how genetic risk for common diseases changes with age using UK Biobank data, finding that most genetic risk factors have a decreasing impact over time.

The paper improves statistical power in severe malaria genetic studies by addressing phenotypic imprecision through a probabilistic diagnostic model and data-tilting approach.

This paper warns against using unsupervised machine learning algorithms like PCoA and HAC to infer malaria parasite ancestry from genetic distance matrices, highlighting their limitations and providing guidance for more rigorous analysis.

The paper introduces a method to analyze heterogeneous treatment effects using reference classes in RCTs, showing increased treatment effect in higher risk strata of a malaria trial.

The paper introduces a statistical method to test for association between a response variable and a tree structure across all hierarchy levels while controlling false positives.

DeMixT improves transcriptomic deconvolution by estimating component proportions and expression profiles in heterogeneous samples, showing high accuracy in validation and TCGA data.

The paper examines the impact of IFN-lambda4 on HCV diversity using host and viral genetic data from 485 patients, finding that IFN-lambda4 variants influence viral amino acid diversity and load.