A post-hoc genome-wide association study using matched samples

Jungsoo Gim, Sungkyoung Choi, Jongho Im, Jae Kwang Kim, Taesung Park

Research output: Contribution to journalArticle

Abstract

Genome-wide association studies have identified many causal candidate loci associated with common complex phenotypes, such as type-2 diabetes and obesity. However, most of these studies have been drawn from non-randomised case/control experiments, where the units exposed to one group generally differ from those exposed to the other group. The aim of this study was to address the issues arising from non-randomised case/control experiments. In order to achieve this, we have proposed a post-hoc association analysis using subsets of samples selected by the proposed matching technique. This method was applied to two different binary traits, type-2 diabetes and obesity, in Korean subjects. It identified nine and two additional variants for type-2 diabetes and obesity, respectively, which were not identified using the total dataset. Our study demonstrates that the proposed a post-hoc genomewide association analysis can determine additional candidate causal variants responsible for common complex phenotypes.

Original languageEnglish
Pages (from-to)197-209
Number of pages13
JournalInternational Journal of Data Mining and Bioinformatics
Volume14
Issue number3
DOIs
Publication statusPublished - 2016 Jan 1

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Genome-Wide Association Study
Medical problems
Type 2 Diabetes Mellitus
chronic illness
Obesity
Genes
candidacy
Phenotype
experiment
Group
Experiments

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Biochemistry, Genetics and Molecular Biology(all)
  • Library and Information Sciences

Cite this

Gim, Jungsoo ; Choi, Sungkyoung ; Im, Jongho ; Kim, Jae Kwang ; Park, Taesung. / A post-hoc genome-wide association study using matched samples. In: International Journal of Data Mining and Bioinformatics. 2016 ; Vol. 14, No. 3. pp. 197-209.
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A post-hoc genome-wide association study using matched samples. / Gim, Jungsoo; Choi, Sungkyoung; Im, Jongho; Kim, Jae Kwang; Park, Taesung.

In: International Journal of Data Mining and Bioinformatics, Vol. 14, No. 3, 01.01.2016, p. 197-209.

Research output: Contribution to journalArticle

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