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  Alignment-free estimation of nucleotide diversity

Haubold, B., Reed, F. A., & Pfaffelhuber, P. (2011). Alignment-free estimation of nucleotide diversity. Bioinformatics, 27(4), 449-455. doi:10.1093/bioinformatics/btq689.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-000F-D406-1 Version Permalink: http://hdl.handle.net/21.11116/0000-0005-6758-5
Genre: Journal Article

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 Creators:
Haubold, Bernhard1, Author              
Reed, Floyd A.2, Author              
Pfaffelhuber, Peter, Author
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1Research Group Bioinformatics, Department Evolutionary Genetics, Max Planck Institute for Evolutionary Biology, Max Planck Society, ou_1445644              
2Research Group Population Genetics, Department Evolutionary Genetics, Max Planck Institute for Evolutionary Biology, Max Planck Society, ou_1445646              

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 Abstract: Motivation: Sequencing capacity is currently growing more rapidly than CPU speed, leading to an analysis bottleneck in many genome projects. Alignment-free sequence analysis methods tend to be more efficient than their alignment-based counterparts. They may, therefore, be important in the long run for keeping sequence analysis abreast with sequencing. Results: We derive and implement an alignment-free estimator of the number of pairwise mismatches, πm. Our implementation of πm, pim, is based on an enhanced suffix array and inherits the superior time and memory efficiency of this data structure. Simulations demonstrate that πm is accurate if mutations are distributed randomly along the chromosome. While real data often deviates from this ideal, πm remains useful for identifying regions of low genetic diversity using a sliding window approach. We demonstrate this by applying it to the complete genomes of 37 strains of Drosophila melanogaster, and to the genomes of two closely related Drosophila species, D.simulans and D.sechellia. In both cases, we detect the diversity minimum and discuss its biological implications.

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Language(s): eng - English
 Dates: 2011-02-15
 Publication Status: Published in print
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 Identifiers: eDoc: 572048
DOI: 10.1093/bioinformatics/btq689
Other: 2860/S 39203
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Title: Bioinformatics
Source Genre: Journal
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Pages: - Volume / Issue: 27 (4) Sequence Number: - Start / End Page: 449 - 455 Identifier: ISSN: 0266-706 (print)
ISSN: 1367-4803 (print)
ISSN: 1367-4811 (online)
ISSN: 1460-2059 (online)