Diplotyper: Diplotype-based association analysis

Sunshin Kim, Kyungchae Park, Chol Shin, Nam H. Cho, Jeong Jae Ko, Insong Koh, Kyubum Kwack

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)

Abstract

Background: It was previously reported that an association analysis based on haplotype clusters increased power over single-locus tests, and that another association test based on diplotype trend regression analysis outperformed other, more common association approaches. We suggest a novel algorithm to combine haplotype cluster- and diplotype-based analyses. Methods. Diplotyper combines a novel algorithm designed to cluster haplotypes of interest from a given set of haplotypes with two existing tools: Haploview, for analyses of linkage disequilibrium blocks and haplotypes, and PLINK, to generate all possible diplotypes from given genotypes of samples and calculate linear or logistic regression. In addition, procedures for generating all possible diplotypes from the haplotype clusters and transforming these diplotypes into PLINK formats were implemented. Results: Diplotyper is a fully automated tool for performing association analysis based on diplotypes in a population. Diplotyper was tested through association analysis of hepatic lipase (LIPC) gene polymorphisms or diplotypes and levels of high-density lipoprotein (HDL) cholesterol. Conclusions: Diplotyper is useful for identifying more precise and distinct signals over single-locus tests.

Original languageEnglish
Article numberS5
JournalBMC Medical Genomics
Volume6
Issue numberSUPPL2
DOIs
Publication statusPublished - 2013

Bibliographical note

Funding Information:
This study was supported by a grant from the Korea Health technology R&D Project, Ministry of Health & Welfare, Republic of Korea (A110749), grants from Korea Centers for Disease Control and Prevention (4845-301, 4851-302, 4851-307), and the Priority Centers Program of the National Research Foundation of Korea (NRF), which is funded by the Ministry of Education, Science, and Technology (No. 2009-0093821).

Funding Information:
The population data used in the present study was provided by the Korea Association Resource (KARE) project from the Korean Genome Epidemiology Study (KoGES), which is conducted by the Korean National Institute of Health (KNIH). A cross-sectional analysis of samples from urban and rural communities in Korea was conducted. The populations [33] were recruited from rural (Ansung) and urban (Ansan) communities in South Korea that were part of the KoGES, established in 2001. A total of 5,018 subjects from the Ansung community and 5,020 subjects from the Ansan community participated in the present study. The age of the participants ranged from 40 to 69 years. A total of 8842 subjects remained after selection of samples for quality control purposes [33]. However, an additional 1,306 subjects who were undergoing treatment for hypertension, diabetes, myocardial infarction or hyperlipidemia were excluded from the study since therapy for these conditions could change HDL-C levels. A detailed list of the

ASJC Scopus subject areas

  • Genetics
  • Genetics(clinical)

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