Matthew Scicluna

This paper shows PHATE can better capture continuous population structure in genomic data than PCA or UMAP by tuning scale and balancing populations.

This paper develops a deep learning framework for genomic ancestry prediction that is generalizable across diverse populations and interpretable using attribution techniques.

The paper computes local feature attributions for t-SNE using gradient-based methods and validates them on synthetic and biological datasets.