sBWT: memory efficient implementation of the hardware-acceleration-friendly Schindler transform for the fast biological sequence mapping

Abstract

Motivation: The Full-text index in Minute space (FM-index) derived from the Burrows-Wheeler transform (BWT) is broadly used for fast string matching in large genomes or a huge set of sequencing reads. Several graphic processing unit (GPU) accelerated aligners based on the FM-index have been proposed recently; however, the construction of the index is still handled by central processing unit (CPU), only parallelized in data level (e.g. by performing block-wise suffix sorting in GPU), or not scalable for large genomes. Results: To fulfill the need for a more practical, hardware-parallelizable indexing and matching approach, we herein propose sBWT based on a BWT variant (i.e. Schindler transform) that can be built with highly simplified hardware-acceleration-friendly algorithms and still suffices accurate and fast string matching in repetitive references. In our tests, the implementation achieves significant speedups in indexing and searching compared with other BWT-based tools and can be applied to a variety of domains.