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SNPAnalyzer 2.0: A web-based integrated workbench for linkage disequilibrium analysis and association analysis

BACKGROUND: Since the completion of the HapMap project, huge numbers of individual genotypes have been generated from many kinds of laboratories. The efforts of finding or interpreting genetic association between disease and SNPs/haplotypes have been on-going widely. So, the necessity of the capabil...

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Detalles Bibliográficos
Autores principales: Yoo, Jinho, Lee, Youngbok, Kim, Yujung, Rha, Sun Young, Kim, Yangseok
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2008
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2453143/
https://www.ncbi.nlm.nih.gov/pubmed/18570686
http://dx.doi.org/10.1186/1471-2105-9-290
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author Yoo, Jinho
Lee, Youngbok
Kim, Yujung
Rha, Sun Young
Kim, Yangseok
author_facet Yoo, Jinho
Lee, Youngbok
Kim, Yujung
Rha, Sun Young
Kim, Yangseok
author_sort Yoo, Jinho
collection PubMed
description BACKGROUND: Since the completion of the HapMap project, huge numbers of individual genotypes have been generated from many kinds of laboratories. The efforts of finding or interpreting genetic association between disease and SNPs/haplotypes have been on-going widely. So, the necessity of the capability to analyze huge data and diverse interpretation of the results are growing rapidly. RESULTS: We have developed an advanced tool to perform linkage disequilibrium analysis, and genetic association analysis between disease and SNPs/haplotypes in an integrated web interface. It comprises of four main analysis modules: (i) data import and preprocessing, (ii) haplotype estimation, (iii) LD blocking and (iv) association analysis. Hardy-Weinberg Equilibrium test is implemented for each SNPs in the data preprocessing. Haplotypes are reconstructed from unphased diploid genotype data, and linkage disequilibrium between pairwise SNPs is computed and represented by D', r(2 )and LOD score. Tagging SNPs are determined by using the square of Pearson's correlation coefficient (r(2)). If genotypes from two different sample groups are available, diverse genetic association analyses are implemented using additive, codominant, dominant and recessive models. Multiple verified algorithms and statistics are implemented in parallel for the reliability of the analysis. CONCLUSION: SNPAnalyzer 2.0 performs linkage disequilibrium analysis and genetic association analysis in an integrated web interface using multiple verified algorithms and statistics. Diverse analysis methods, capability of handling huge data and visual comparison of analysis results are very comprehensive and easy-to-use.
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spelling pubmed-24531432008-07-11 SNPAnalyzer 2.0: A web-based integrated workbench for linkage disequilibrium analysis and association analysis Yoo, Jinho Lee, Youngbok Kim, Yujung Rha, Sun Young Kim, Yangseok BMC Bioinformatics Software BACKGROUND: Since the completion of the HapMap project, huge numbers of individual genotypes have been generated from many kinds of laboratories. The efforts of finding or interpreting genetic association between disease and SNPs/haplotypes have been on-going widely. So, the necessity of the capability to analyze huge data and diverse interpretation of the results are growing rapidly. RESULTS: We have developed an advanced tool to perform linkage disequilibrium analysis, and genetic association analysis between disease and SNPs/haplotypes in an integrated web interface. It comprises of four main analysis modules: (i) data import and preprocessing, (ii) haplotype estimation, (iii) LD blocking and (iv) association analysis. Hardy-Weinberg Equilibrium test is implemented for each SNPs in the data preprocessing. Haplotypes are reconstructed from unphased diploid genotype data, and linkage disequilibrium between pairwise SNPs is computed and represented by D', r(2 )and LOD score. Tagging SNPs are determined by using the square of Pearson's correlation coefficient (r(2)). If genotypes from two different sample groups are available, diverse genetic association analyses are implemented using additive, codominant, dominant and recessive models. Multiple verified algorithms and statistics are implemented in parallel for the reliability of the analysis. CONCLUSION: SNPAnalyzer 2.0 performs linkage disequilibrium analysis and genetic association analysis in an integrated web interface using multiple verified algorithms and statistics. Diverse analysis methods, capability of handling huge data and visual comparison of analysis results are very comprehensive and easy-to-use. BioMed Central 2008-06-23 /pmc/articles/PMC2453143/ /pubmed/18570686 http://dx.doi.org/10.1186/1471-2105-9-290 Text en Copyright © 2008 Yoo et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 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.
spellingShingle Software
Yoo, Jinho
Lee, Youngbok
Kim, Yujung
Rha, Sun Young
Kim, Yangseok
SNPAnalyzer 2.0: A web-based integrated workbench for linkage disequilibrium analysis and association analysis
title SNPAnalyzer 2.0: A web-based integrated workbench for linkage disequilibrium analysis and association analysis
title_full SNPAnalyzer 2.0: A web-based integrated workbench for linkage disequilibrium analysis and association analysis
title_fullStr SNPAnalyzer 2.0: A web-based integrated workbench for linkage disequilibrium analysis and association analysis
title_full_unstemmed SNPAnalyzer 2.0: A web-based integrated workbench for linkage disequilibrium analysis and association analysis
title_short SNPAnalyzer 2.0: A web-based integrated workbench for linkage disequilibrium analysis and association analysis
title_sort snpanalyzer 2.0: a web-based integrated workbench for linkage disequilibrium analysis and association analysis
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2453143/
https://www.ncbi.nlm.nih.gov/pubmed/18570686
http://dx.doi.org/10.1186/1471-2105-9-290
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