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dc.contributor.authorKülekci, M. Oğuzhan
dc.contributor.authorHon, Wing-Kai
dc.contributor.authorShah, Rahul
dc.contributor.authorVitter, Jeffrey Scott
dc.contributor.authorXu, Bojian
dc.date.accessioned2014-01-24T22:09:53Z
dc.date.available2014-01-24T22:09:53Z
dc.date.issued2011-07-27
dc.identifier.citationOğuzhan Külekci, M, Wing-Kai Hon, Rahul Shah, Jeffrey Scott Vitter, and Bojian Xu. 2011. “Ψ-RA: A Parallel Sparse Index for Genomic Read Alignment.” BMC Genomics 12 Suppl 2 (Suppl 2): S7. http://dx.doi.org/10.1186/1471-2164-12-S2-S7
dc.identifier.urihttp://hdl.handle.net/1808/12849
dc.description.abstractBackground Genomic read alignment involves mapping (exactly or approximately) short reads from a particular individual onto a pre-sequenced reference genome of the same species. Because all individuals of the same species share the majority of their genomes, short reads alignment provides an alternative and much more efficient way to sequence the genome of a particular individual than does direct sequencing. Among many strategies proposed for this alignment process, indexing the reference genome and short read searching over the index is a dominant technique. Our goal is to design a space-efficient indexing structure with fast searching capability to catch the massive short reads produced by the next generation high-throughput DNA sequencing technology.

Results We concentrate on indexing DNA sequences via sparse suffix arrays (SSAs) and propose a new short read aligner named Ψ-RA (PSI-RA: parallel sparse index read aligner). The motivation in using SSAs is the ability to trade memory against time. It is possible to fine tune the space consumption of the index based on the available memory of the machine and the minimum length of the arriving pattern queries. Although SSAs have been studied before for exact matching of short reads, an elegant way of approximate matching capability was missing. We provide this by defining the rightmost mismatch criteria that prioritize the errors towards the end of the reads, where errors are more probable. Ψ-RA supports any number of mismatches in aligning reads. We give comparisons with some of the well-known short read aligners, and show that indexing a genome with SSA is a good alternative to the Burrows-Wheeler transform or seed-based solutions.

Conclusions Ψ-RA is expected to serve as a valuable tool in the alignment of short reads generated by the next generation high-throughput sequencing technology. Ψ-RA is very fast in exact matching and also supports rightmost approximate matching. The SSA structure that Ψ-RA is built on naturally incorporates the modern multicore architecture and thus further speed-up can be gained. All the information, including the source code of Ψ-RA, can be downloaded at: http://www.busillis.com/o_kulekci/PSIRA.zip webcite.
dc.publisherBioMed Central
dc.rightsThis is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
dc.rights.urihttp://creativecommons.org/licenses/by/2.0
dc.titleΨ-RA: a parallel sparse index for genomic read alignment
dc.typeArticle
kusw.kuauthorXu, Bojian
kusw.kuauthorVitter, Jeffrey Scott
kusw.kudepartmentDepartment of Electrical Engineering and Computer Science
kusw.oastatusfullparticipation
dc.identifier.doi10.1186/1471-2164-12-S2-S7
kusw.oaversionScholarly/refereed, publisher version
kusw.oapolicyThis item meets KU Open Access policy criteria.
dc.rights.accessrightsopenAccess


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This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Except where otherwise noted, this item's license is described as: This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.