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Relative Lempel-Ziv Compression of Genomes for Large-Scale Storage and Retrieval

2010; Springer Science+Business Media; Linguagem: Inglês

10.1007/978-3-642-16321-0_20

1611-3349

Shanika Kuruppu, Simon J. Puglisi, Justin Zobel,

DNA and Biological Computing

Self-indexes – data structures that simultaneously provide fast search of and access to compressed text – are promising for genomic data but in their usual form are not able to exploit the high level of replication present in a collection of related genomes. Our ‘RLZ’ approach is to store a self-index for a base sequence and then compress every other sequence as an LZ77 encoding relative to the base. For a collection of r sequences totaling N bases, with a total of s point mutations from a base sequence of length n, this representation requires just $nH_k(T) + s\log n + s\log \frac{N}{s} + O(s)$ bits. At the cost of negligible extra space, access to ℓ consecutive symbols requires $\O(\ell + \log n)$ time. Our experiments show that, for example, RLZ can represent individual human genomes in around 0.1 bits per base while supporting rapid access and using relatively little memory.