A Fast Sketch-Based Assembler For Genomes

De novo genome assembly describes the process of reconstructing an unknown genome from a large collection of short (or long) reads sequenced from the genome. A single run of Next-Generation Sequencing (NGS) technologies can produce billions of reads, making genome assembly computationally demanding. One of the major computational steps in modern day short read assemblers involves the construction and use of a string data structure called the de Bruijn graph. In fact, a majority of short read assemblers build the complete de Bruijn graph for the set of input reads, and subsequently traverse and prune low-quality edges, in order to generate genomic "contigs" - the output of assembly. These steps of graph construction and traversal, contribute to well over 90% of the runtime and memory. In this paper, we present a fast algorithm, FastEtch, that uses sketching to build an approximate version of the de Bruijn graph for the purpose of generating an assembly. The algorithm uses Count-Min sketch, which is a probabilistic data structure for streaming data sets. The result is an approximate de Bruijn graph that stores information pertaining only to a selected subset of nodes that are most likely to contribute to the contig generation step. In addition, edges are not stored; instead that fraction which contribute to our contig generation are detected on-the-fly. This approximate approach is intended to significantly improve performance (both execution time and memory footprint) whilst possibly compromising on the output assembly quality. For further scalability, we have implemented a multi-threaded parallel code. Experimental results using our algorithm conducted on E. coli, Yeast, and C. elegans genomes show that our method is able to produce assemblies with quality comparable or better than most other state-of-the-art assemblers, while running in significantly reduced memory and time footprint.