Marie Forest

This paper introduces ggmix, a penalized linear mixed model for SNP selection and population structure adjustment in high-dimensional genetic prediction models, showing improved accuracy and parsimony over existing methods.

This paper introduces a method to estimate genome-wide genealogies for thousands of samples, revealing new insights into human evolutionary history and selection.

This paper uses machine learning to predict osteoporotic fracture risk from genotypes, finding that genomic predictions outperform clinical risk factors in identifying fracture risk.

PRS-on-Spark generates polygenic risk scores efficiently, supporting diverse data inputs and improving variance explained for major depression.