STATISTICAL GENETICS LEARNING FROM GENOME-WIDE ASSOCIATION STUDY

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  • ゲノムワイド関連研究に学ぶ遺伝統計学
  • ゲノムワイド カンレン ケンキュウ ニ マナブ イデン トウケイガク

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Abstract

A genome-wide association study (GWAS) is an approach that exhaustively explores whole genomes for the genetic variation associated with a disease, and much of the present knowledge of the genetic mechanisms for diseases was obtained from GWAS. One reason for the high-quality results being obtained from GWAS is that genomic information is controlled by the laws of inheritance, namely, the well-known Mendelian laws. A gamete including genomic information is stably inherited from parents to child and the observed phenotypic value arises from the combination of the two inherited gametes on the basis of the laws of inheritance. In this report, we introduce the concept of genomic study in the light of statistical genetics. The methods and understandings of and knowledge obtained from GWAS are explained in Sections 2 and 3, respectively. In Section 4, the approaches to GWAS data under the laws of inheritance are introduced to facilitate a literacy for GWAS data. In addition, the statistical design of GWAS is explained in Section 5, and the application to PGx of knowledge obtained from GWAS is introduced in Section 6. We hope that this report will be an aid to the reader's understanding of statistical genetics.

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