“On-Demand Indexing for Referential Compression of DNA Sequences”
PLoS ONE, vol. 10, no. 7, pp. e0132460, Jul. 2015.DOI: 10.1371/journal.pone.0132460.
Abstract: The decreasing costs of genome sequencing is creating a demand for scalable storage and processing tools and techniques to deal with the large amounts of generated data. Referential compression is one of these techniques, in which the similarity between the DNA of organisms of the same or an evolutionary close species is exploited to reduce the storage demands of genome sequences up to 700 times. The general idea is to store in the compressed file only the differences between the to-be-compressed and a well known reference sequence. In this paper, we propose a method for improving the performance of referential compression by removing the most costly phase of the process, the complete reference indexing. Our approach, called On-Demand Indexing (ODI) compresses human chromosomes five to ten times faster than other state-of-the-art tools (on average), while achieving similar compression ratios.
Research line(s): Fault and Intrusion Tolerance in Open Distributed Systems (FIT)