Luke Anderson-Trocmé

The paper introduces a topological clustering method for genetic data from biobanks, showing it can reveal population structure and aid in quality control and polygenic score analysis.

The paper constructs a genetic reference panel for the Quebec population using whole-genome sequencing and GWAS to improve phenotype-genotype association discovery.

This paper introduces branch relatedness and efficient algorithms for computing branch GRMs using tree sequences, enabling large-scale genomic analysis.

The paper models French Canadian ancestry using genealogical and genetic data, revealing population structure shaped by geography and migration.

The paper introduces PCA-UMAP for visualizing population structure in large genomic datasets, revealing subpopulations and fine-scale relationships between geography, genotypes, and phenotypes.

The paper identifies a batch effect in 1000 Genomes Project data causing spurious mutation calls and affecting GWAS results, suggesting legacy data may need to be retired or upgraded.