Alex Diaz-Papkovich

From Wikipedia to AI: Measuring 25 years of synthesis of human genetics research in the public-facing information ecosystem

The paper analyzes how human genetics research is represented in Wikipedia and AI-generated encyclopedias over 25 years, finding frequent mentions of genetics in pages about ethnicity and nationality.

Topological stratification of continuous genetic variation in large biobanks

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.

A multi-ancestry genetic reference for the Quebec population

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

Using the ancestral recombination graph to study the history of rare variants in founder populations

This paper uses ancestral recombination graphs to impute and trace rare variants in founder populations, showing high accuracy in mutation age and regional frequency estimation.

Conserved whole-brain spatiomolecular gradients shape adult brain functional organization

The paper identifies three conserved spatiomolecular gradients in the adult human brain that align with developmental axes and predict functional territories.

On the Genes, Genealogies, and Geographies of Quebec

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

Recent fluctuations in Mexican American genomes have altered the genetic architecture of biomedical traits

The paper shows that increased Amerindigenous ancestry in Mexican Americans over time has altered the genetic architecture of traits like height and polygenic risk scores.

A molecular gradient along the longitudinal axis of the human hippocampus informs large-scale behavioral systems

The paper identifies a molecular gradient along the human hippocampus's longitudinal axis that correlates with distinct brain systems and behavioral functions.

Revealing multi-scale population structure in large cohorts

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