An FPGA-Based Data Pre-Processing Architecture to Accelerate De-Novo Genome Assembly

Abstract

Genome assembly is a field of bioinformatics which refers to the process of taking small fragments of genetic material and putting them back together in order to reconstruct the original DNA sequence from which the fragments originated. As the DNA genome assembly input datasets in most cases have a very large amount of data, it is important to develop custom architectures in order to speed up these processes and gain significant execution time reduction. In this paper we present the Reads Matching Filter (RMF), an input dataset prefiltering process, based on string matching and implemented on Field Programmable Gate Array (FPGA) technology, in order to reduce the genome assembly execution time. The outputs of the RMF running on the FPGA as well as the original input dataset are given as input to the Velvet genome assembler which produces the assembly of the input sequences. The Velvet genome assembler is based on the manipulation of de Bruijn graphs, and produces its output via the removal of errors and the simplication of repeated regions. The FPGA-based RMF pre-filtering process manages to speedup the entire genome assembly processing, including I/O, by up to 6 times, while maintaining the quality of the output sequence contigs (i.e. the series of overlapping DNA sequences).