Background: The de Bruijn graph data structure is widely used in next-generation sequencing (NGS). Many programs, e.g. de novo assemblers, rely on in-memory representation of this graph. However, current techniques for representing the de Bruijn graph of a human genome require a large amount of memory (≥ 30 GB). Results: We propose a new encoding of the de Bruijn graph, which occupies an order of magnitude less space than current representations. The encoding is based on a Bloom filter, with an additional structure to remove critical false positives. Conclusions: An assembly software implementing this structure, Minia, performed a complete de novo assembly of human genome short reads using 5.7 GB of memory in 23 hours.
Building upon this probabilistic representation, REF introduce an exact de Bruijn Graph representation that couples a Bloom-filter-based approximate de Bruijn Graph with an exact table storing critical false positive edges.
Space-efficient and exact de Bruijn graph representation based on a Bloom filter
Algorithms for Molecular Biology
Algorithms for Molecular Biology
Computer Science Medicine