SNEP: Simultaneous detection of nucleotide and expression polymorphisms using Affymetrix GeneChip

<p>Abstract</p> <p>Background</p> <p>High-density short oligonucleotide microarrays are useful tools for studying biodiversity, because they can be used to investigate both nucleotide and expression polymorphisms. However, when different strains (or species) produce dif...

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Main Authors: Takada Toyoyuki, Harushima Yoshiaki, Horiuchi Youko, Fujisawa Hironori, Eguchi Shinto, Mochizuki Takako, Sakaguchi Takayuki, Shiroishi Toshihiko, Kurata Nori
Format: Article
Language:English
Published: BMC 2009-05-01
Series:BMC Bioinformatics
Online Access:http://www.biomedcentral.com/1471-2105/10/131
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author Takada Toyoyuki
Harushima Yoshiaki
Horiuchi Youko
Fujisawa Hironori
Eguchi Shinto
Mochizuki Takako
Sakaguchi Takayuki
Shiroishi Toshihiko
Kurata Nori
author_facet Takada Toyoyuki
Harushima Yoshiaki
Horiuchi Youko
Fujisawa Hironori
Eguchi Shinto
Mochizuki Takako
Sakaguchi Takayuki
Shiroishi Toshihiko
Kurata Nori
author_sort Takada Toyoyuki
collection DOAJ
description <p>Abstract</p> <p>Background</p> <p>High-density short oligonucleotide microarrays are useful tools for studying biodiversity, because they can be used to investigate both nucleotide and expression polymorphisms. However, when different strains (or species) produce different signal intensities after mRNA hybridization, it is not easy to determine whether the signal intensities were affected by nucleotide or expression polymorphisms. To overcome this difficulty, nucleotide and expression polymorphisms are currently examined separately.</p> <p>Results</p> <p>We have developed SNEP, a new method that allows simultaneous detection of both nucleotide and expression polymorphisms. SNEP involves a robust statistical procedure based on the idea that a nucleotide polymorphism observed at the probe level can be regarded as an outlier, because the nucleotide polymorphism can reduce the hybridization signal intensity. To investigate the performance of SNEP, we used three species: barley, rice and mice. In addition to the publicly available barley data, we obtained new rice and mouse data from the strains with available genome sequences. The sensitivity and false positive rate of nucleotide polymorphism detection were estimated based on the sequence information. The robustness of expression polymorphism detection against nucleotide polymorphisms was also investigated.</p> <p>Conclusion</p> <p>SNEP performed well regardless of the genome size and showed a better performance for nucleotide polymorphism detection, when compared with other previously proposed methods. The R-software 'SNEP' is available at <url>http://www.ism.ac.jp/~fujisawa/SNEP/</url>.</p>
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spelling doaj.art-fb726101abc148d2ad507f79cb24bc7f2022-12-21T21:43:29ZengBMCBMC Bioinformatics1471-21052009-05-0110113110.1186/1471-2105-10-131SNEP: Simultaneous detection of nucleotide and expression polymorphisms using Affymetrix GeneChipTakada ToyoyukiHarushima YoshiakiHoriuchi YoukoFujisawa HironoriEguchi ShintoMochizuki TakakoSakaguchi TakayukiShiroishi ToshihikoKurata Nori<p>Abstract</p> <p>Background</p> <p>High-density short oligonucleotide microarrays are useful tools for studying biodiversity, because they can be used to investigate both nucleotide and expression polymorphisms. However, when different strains (or species) produce different signal intensities after mRNA hybridization, it is not easy to determine whether the signal intensities were affected by nucleotide or expression polymorphisms. To overcome this difficulty, nucleotide and expression polymorphisms are currently examined separately.</p> <p>Results</p> <p>We have developed SNEP, a new method that allows simultaneous detection of both nucleotide and expression polymorphisms. SNEP involves a robust statistical procedure based on the idea that a nucleotide polymorphism observed at the probe level can be regarded as an outlier, because the nucleotide polymorphism can reduce the hybridization signal intensity. To investigate the performance of SNEP, we used three species: barley, rice and mice. In addition to the publicly available barley data, we obtained new rice and mouse data from the strains with available genome sequences. The sensitivity and false positive rate of nucleotide polymorphism detection were estimated based on the sequence information. The robustness of expression polymorphism detection against nucleotide polymorphisms was also investigated.</p> <p>Conclusion</p> <p>SNEP performed well regardless of the genome size and showed a better performance for nucleotide polymorphism detection, when compared with other previously proposed methods. The R-software 'SNEP' is available at <url>http://www.ism.ac.jp/~fujisawa/SNEP/</url>.</p>http://www.biomedcentral.com/1471-2105/10/131
spellingShingle Takada Toyoyuki
Harushima Yoshiaki
Horiuchi Youko
Fujisawa Hironori
Eguchi Shinto
Mochizuki Takako
Sakaguchi Takayuki
Shiroishi Toshihiko
Kurata Nori
SNEP: Simultaneous detection of nucleotide and expression polymorphisms using Affymetrix GeneChip
BMC Bioinformatics
title SNEP: Simultaneous detection of nucleotide and expression polymorphisms using Affymetrix GeneChip
title_full SNEP: Simultaneous detection of nucleotide and expression polymorphisms using Affymetrix GeneChip
title_fullStr SNEP: Simultaneous detection of nucleotide and expression polymorphisms using Affymetrix GeneChip
title_full_unstemmed SNEP: Simultaneous detection of nucleotide and expression polymorphisms using Affymetrix GeneChip
title_short SNEP: Simultaneous detection of nucleotide and expression polymorphisms using Affymetrix GeneChip
title_sort snep simultaneous detection of nucleotide and expression polymorphisms using affymetrix genechip
url http://www.biomedcentral.com/1471-2105/10/131
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