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PRaDA : Web-based analyzer for Pathway Relation and Disease Associated SNP

웹 기반 단일염기다형성 연관 패스웨이 분석 도구

  • Yu, Kijin (Database/Bioinformatics Laboratory, School of Electrical & Computer Engineering, Chungbuk National University) ;
  • Park, Soo Ho (Database/Bioinformatics Laboratory, School of Electrical & Computer Engineering, Chungbuk National University) ;
  • Ryu, Keun Ho (Database/Bioinformatics Laboratory, School of Electrical & Computer Engineering, Chungbuk National University)
  • 유기진 (충북대학교 데이터베이스/바이오인포매틱스 연구실) ;
  • 박수호 (충북대학교 데이터베이스/바이오인포매틱스 연구실) ;
  • 류근호 (충북대학교 데이터베이스/바이오인포매틱스 연구실)
  • Received : 2018.09.06
  • Accepted : 2018.09.27
  • Published : 2018.09.30

Abstract

Genome-Wide Association Study (GWAS) have been used to identify susceptibility genes for complex human diseases and many recent studies succeed to report common genetic factors for various diseases. Unfortunately, it is hard to understand all biological functions and mechanisms around the complex disease with GWAS only although the number of known associated genes with diseases is increased drastically because GWAS is a single locus based approach while not a gene but numerous factors may affect a disease associated pathways. PRaDA generates a combined report with genes, pathways and Gene Ontology (GO) using single nucleotide polymorphism (SNP) analysis output. The PRaDA reports not only directly associated pathways but also functionally related ones for identifying accumulated effects of low p-value SNPs. Through integrated information including indirect functional effects, user could have insights of overall disease mechanisms and markers.

질환의 원인을 규명하기 위해 전장유전체 연관분석 (GWAS; Genome-Wide Association Study) 연구가 활발히 진행되고 유전체 레벨의 단일염기다형성 (SNP; Single-nucleotide polymorphism)이 많이 밝혀지고 있다. 그러나 단일염기다형성의 연관분석을 통해 질환이 발병하는 생물학적 메카니즘을 이해하기 어렵기 때문에 유전자, 생물학적 패스웨이 및 질환 등의 연관성 분석이 이전보다 더욱 중요하다. 본 논문에서는 단일염기다형성과 관련된 유전자와 패스웨이, 질환 정보를 검색하여 통합 분석하는 서비스를 제공하는 PRaDA 웹 시스템을 제안하였다. PRaDA는 사용자로부터 입력받은 유의한 몇몇의 단일염기다형성들과 관련된 유전자 및 패스웨이 뿐만 아니라, 유의하지 않은 다수의 단일염기다형성 집합의 간접적인 영향을 파악하기 위해 기능적으로 근접한 패스웨이를 검색하고 통계적 분석을 실행한다. 사용자들은 PRaDA가 제공하는 통합된 정보를 통해 질병의 전반적인 이해를 할 수 있다.

Keywords

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