  The formal version of our work has been published in BMC Bioinformatics and
can be found here: http://www.biomedcentral.com/1471-2105/13/S6/S1 Motivation:
To tackle the problem of huge memory usage associated with de Bruijn
graph-based algorithms, upon which some of the most widely used de novo genome
assemblers have been built, we released SparseAssembler1. SparseAssembler1 can
save as much as 90% memory consumption in comparison with the state-of-art
assemblers, but it requires rounds of denoising to accurately assemble genomes.
In this paper, we introduce a new general model for genome assembly that uses
only sparse k-mers. The new model replaces the idea of the de Bruijn graph from
the beginning, and achieves similar memory efficiency and much better
robustness compared with our previous SparseAssembler1. Results: We demonstrate
that the decomposition of reads of all overlapping k-mers, which is used in
existing de Bruijn graph genome assemblers, is overly cautious. We introduce a
sparse k-mer graph structure for saving sparse k-mers, which greatly reduces
memory space requirements necessary for de novo genome assembly. In contrast
with the de Bruijn graph approach, we devise a simple but powerful strategy,
i.e., finding links between the k-mers in the genome and traversing following
the links, which can be done by saving only a few k-mers. To implement the
strategy, we need to only select some k-mers that may not even be overlapping
ones, and build the links between these k-mers indicated by the reads. We can
traverse through this sparse k-mer graph to build the contigs, and ultimately
complete the genome assembly. Since the new sparse k-mers graph shares almost
all advantages of de Bruijn graph, we are able to adapt a Dijkstra-like
breadth-first search algorithm to circumvent sequencing errors and resolve
polymorphisms.
