Hopper: a mathematically optimal algorithm for sketching biological data

Benjamin Demeo, Bonnie Berger

Abstract: Single-cell RNA-sequencing has grown massively in scale since its inception, presenting substantial analytic and computational challenges. Even simple downstream analyses, such as dimensionality reduction and clustering, require days of runtime and hundreds of gigabytes of memory for today’s largest datasets. In addition, current methods often favor common cell types, and miss salient biological features captured by small cell populations.