CS-BWAMEM: A fast and scalable read aligner at the cloud scale for whole genome sequencing

Abstract

The deep-coverage whole-genome sequencing (WGS) can generate billions of reads to be sequenced. It is time consuming for state-of-the-art aligners, such as BWA-MEM, to align the tremendous number of reads onto the reference genome. Inherently, the reads can be aligned using a massively parallel approach, and the alignment process should not be bounded by the limited number of computing cores of a single server. We present cloudscale BWAMEM (CS-BWAMEM), an ultrafast and highly scalable aligner built on top of cloud infrastructures. It leverages the abundant computing resources in a public or private cloud to fully exploit the parallelism obtained from the enormous number of reads. With CSBWAMEM, the pair-end whole-genome reads (30x) can be aligned within 80 minutes in a 25-node cluster with 300 cores.

Peipei Zhou

Assistant Professor of ECE Department

My research interests include Customized Computer Architecture and Programming Abstraction for Health & AI Applications