Arun Durvasula

The paper examines gene expression evolution in primate immune cells under different conditions, finding that perturbation-responsive genes evolve faster than baseline genes.

This paper introduces CT-FM and CT-FM-SNP methods to identify causal cell types and variants for diseases, finding most SNPs affect traits via a single cell type set.

This study evaluates how admixture, selection, and demographic history influence GWAS power and fine-mapping precision in admixed populations using simulations and empirical data.

The paper extends SISTR to jointly estimate selection coefficients across STRs, showing variation in mutation and selection parameters and greater selective burden of de novo STR mutations compared to standing variation.

The paper uses pathway-specific polygenic scores to identify gene-adiposity interactions affecting liver biomarkers, finding more specific and interpretable results compared to standard polygenic scores and GWIS.

The paper shows that environmental variance increases with age, reducing heritability and PRS accuracy for multiple traits and diseases, suggesting younger cohorts are better for risk prediction models.

The paper quantifies and distinguishes three types of gene-environment interactions using statistical methods applied to UK Biobank data, identifying significant associations across various traits and environmental variables.

The paper shows a bottleneck model fits worse than a panmictic model, refuting a recent claim of a severe population bottleneck during the Early to Middle Pleistocene transition.

This paper introduces PSMC+, an extension of the PSMC algorithm that accounts for background selection in demographic inference, improving accuracy in effective population size estimation.

The paper introduces LDSPEC to estimate correlations between causal disease effects of proximal SNPs, finding significant correlations that vary with distance, allele frequency, LD, and functional annotations, implicating stabilizing selection.

This study assesses the contribution of Neanderthal introgression to human complex traits using UK Biobank data, finding significant but depleted effects compared to modern human variants.

This paper introduces an age-dependent topic modelling method to identify disease subtypes with differential genetic risk using UK Biobank and All of Us data.

The paper shows that negative selection on complex traits leads to population-specific genetic architectures, reducing the accuracy of genetic risk prediction in non-European populations using European-derived variants.

The paper identifies archaic ancestry in African populations, showing they inherited 2-19% of their genetic ancestry from an archaic population diverging before Neanderthals and modern humans.

The paper uses population genomic data to characterize the degree of dominance for new mutations and develops a new theory for its evolution.