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

Jinho Yoo, Youngbok Lee, Yujung Kim, Sun Young Rha, Yangseok Kim

Research output: Contribution to journalArticle

68 Citations (Scopus)

Abstract

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', r2 and LOD score. Tagging SNPs are determined by using the square of Pearson's correlation coefficient (r2). 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.

Original languageEnglish
Article number290
JournalBMC bioinformatics
Volume9
DOIs
Publication statusPublished - 2008 Jun 23

Fingerprint

Linkage Disequilibrium
Web-based
Single Nucleotide Polymorphism
Haplotypes
Statistics
Data handling
Genetic Association
Haplotype
Genotype
HapMap Project
Information Storage and Retrieval
Diploidy
Pearson Correlation
Data Preprocessing
Data Handling
Tagging
Correlation coefficient
Preprocessing
Completion
Pairwise

All Science Journal Classification (ASJC) codes

  • Medicine(all)
  • Structural Biology
  • Applied Mathematics

Cite this

@article{63a184cc99fc4aa892a5e4f4dfb83c32,
title = "SNPAnalyzer 2.0: A web-based integrated workbench for linkage disequilibrium analysis and association analysis",
abstract = "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', r2 and LOD score. Tagging SNPs are determined by using the square of Pearson's correlation coefficient (r2). 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.",
author = "Jinho Yoo and Youngbok Lee and Yujung Kim and Rha, {Sun Young} and Yangseok Kim",
year = "2008",
month = "6",
day = "23",
doi = "10.1186/1471-2105-9-290",
language = "English",
volume = "9",
journal = "BMC Bioinformatics",
issn = "1471-2105",
publisher = "BioMed Central",

}

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.

In: BMC bioinformatics, Vol. 9, 290, 23.06.2008.

Research output: Contribution to journalArticle

TY - JOUR

T1 - SNPAnalyzer 2.0

T2 - A web-based integrated workbench for linkage disequilibrium analysis and association analysis

AU - Yoo, Jinho

AU - Lee, Youngbok

AU - Kim, Yujung

AU - Rha, Sun Young

AU - Kim, Yangseok

PY - 2008/6/23

Y1 - 2008/6/23

N2 - 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', r2 and LOD score. Tagging SNPs are determined by using the square of Pearson's correlation coefficient (r2). 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.

AB - 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', r2 and LOD score. Tagging SNPs are determined by using the square of Pearson's correlation coefficient (r2). 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.

UR - http://www.scopus.com/inward/record.url?scp=47249133881&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=47249133881&partnerID=8YFLogxK

U2 - 10.1186/1471-2105-9-290

DO - 10.1186/1471-2105-9-290

M3 - Article

C2 - 18570686

AN - SCOPUS:47249133881

VL - 9

JO - BMC Bioinformatics

JF - BMC Bioinformatics

SN - 1471-2105

M1 - 290

ER -