Accelerating single-cell genomic analysis with GPUs

Autor: Corey Nolet, Avantika Lal, Rajesh Ilango, Taurean Dyer, Rajiv Movva, John Zedlewski, Johnny Israeli
Rok vydání: 2022
DOI: 10.5281/zenodo.7449709
Popis: Single-cell genomic technologies are rapidly improving our understanding of cellular heterogeneity in biological systems. In recent years, technological and computational improvements have continuously increased the scale of single-cell experiments, and now allow for millions of cells to be analyzed in a single experiment. However, existing software tools for single-cell analysis do not scale well to such large datasets. RAPIDS is an open-source suite of Python libraries that use GPU computing to accelerate data science workflows. Here, we report the use of RAPIDS and GPU computing to accelerate single-cell genomic analysis workflows and present open-source examples that can be reused by the community.
Databáze: OpenAIRE