METU-SNP: An Integrated Software System for SNPComplex Disease Association Analysis

Üstünkar, Gürkan; Son, Yeşim Aydın

doi:10.1515/jib-2011-187

Cited by 4 publications

(2 citation statements)

References 16 publications

(22 reference statements)

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“…Additioanlly, iSNP has the unique capability of updating the information by automatically synchronizing with the online accessible SNP databases. The java-based METU-SNP desktop application developed by our group provides all-in-one genome wide association analysis of SNP-disease relations [19]. Initially, iSNP database presented here will be utilized by the METU-SNP application which will be available through web (pisnp.ii.metu.edu.tr).…”

Section: Discussionmentioning

confidence: 99%

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iSNP: An integrated, automatically updated SNP database

Carkacwglu

Gedikoglu

Son

2012

2012 7th International Symposium on Health Informatics and Bioinformatics

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Single Nucleotide Polymorphisms (SNP) is a DNA sequence variation that occurs when a single nucleotide differs between members of a biological species or paired chromosomes in an individual. Studies on SNP data are important for scientists to shed light on identifying genetic variations underlying complex diseases. While recent advances in highthroughput genotyping technologies are resulting in data accumulation at large scales, the need for collection and service of this data under a standard format and globally normalized and structured metadata that houses the structured SNP data is becoming essential. Here, we present iSNP that is a regularly updated, machine curated database that holds SNP and its associated metadata from publicly available databases under a structured standard format that can be efficiently utilized within different applications.

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Section: Discussionmentioning

confidence: 99%

“…Associations among ta- bles are done over gene or SNP identifiers. The relational database structure of METU-SNP [19] is adopted for iSNP database as presented with ER diagram in Figure 2. iSNP has an integrated modular architecture.…”

Section: Isnp Databasementioning

confidence: 99%

iSNP: An integrated, automatically updated SNP database

Carkacwglu

Gedikoglu

Son

2012

2012 7th International Symposium on Health Informatics and Bioinformatics

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Designing and Implementing Pharmacogenomics Study

Son

Hızel

2013

Omics for Personalized Medicine

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Comparative study for haplotype block partitioning methods – Evidence from chromosome 6 of the North American Rheumatoid Arthritis Consortium (NARAC) dataset

et al. 2018

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Haplotype-based methods compete with “one-SNP-at-a-time” approaches on being preferred for association studies. Chromosome 6 contains most of the known genetic biomarkers for rheumatoid arthritis (RA) disease. Therefore, chromosome 6 serves as a benchmark for the haplotype methods testing. The aim of this study is to test the North American Rheumatoid Arthritis Consortium (NARAC) dataset to find out if haplotype block methods or single-locus approaches alone can sufficiently provide the significant single nucleotide polymorphisms (SNPs) associated with RA. In addition, could we be satisfied with only one method of the haplotype block methods for partitioning chromosome 6 of the NARAC dataset? In the NARAC dataset, chromosome 6 comprises 35,574 SNPs for 2,062 individuals (868 cases, 1,194 controls). Individual SNP approach and three haplotype block methods were applied to the NARAC dataset to identify the RA biomarkers. We employed three haplotype partitioning methods which are confidence interval test (CIT), four gamete test (FGT), and solid spine of linkage disequilibrium (SSLD). P-values after stringent Bonferroni correction for multiple testing were measured to assess the strength of association between the genetic variants and RA susceptibility. Moreover, the block size (in base pairs (bp) and number of SNPs included), number of blocks, percentage of uncovered SNPs by the block method, percentage of significant blocks from the total number of blocks, number of significant haplotypes and SNPs were used to compare among the three haplotype block methods. Individual SNP, CIT, FGT, and SSLD methods detected 432, 1,086, 1,099, and 1,322 associated SNPs, respectively. Each method identified significant SNPs that were not detected by any other method (Individual SNP: 12, FGT: 37, CIT: 55, and SSLD: 189 SNPs). 916 SNPs were discovered by all the three haplotype block methods. 367 SNPs were discovered by the haplotype block methods and the individual SNP approach. The P-values of these 367 SNPs were lower than those of the SNPs uniquely detected by only one method. The 367 SNPs detected by all the methods represent promising candidates for RA susceptibility. They should be further investigated for the European population. A hybrid technique including the four methods should be applied to detect the significant SNPs associated with RA for chromosome 6 of the NARAC dataset. Moreover, SSLD method may be preferred for its favored benefits in case of selecting only one method.

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METU-SNP: An Integrated Software System for SNPComplex Disease Association Analysis

Cited by 4 publications

References 16 publications

iSNP: An integrated, automatically updated SNP database

iSNP: An integrated, automatically updated SNP database

Designing and Implementing Pharmacogenomics Study

Comparative study for haplotype block partitioning methods – Evidence from chromosome 6 of the North American Rheumatoid Arthritis Consortium (NARAC) dataset

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