Analysis of complex disease association studies : a practical guide / edited by Eleftheria Zeggini, Andrew Morris.

Format:

Book

Contributor:

Zeggini, Eleftheria.

Morris, Andrew Paul.

Language:

English

Subjects (All):

Human genetics--Variation.

Human genetics.

Genetic disorders.

Diseases.

Physical Description:

viii, 331 pages of color plates, 11 unnumbered pages of color plates) : color illustrations ; 24 cm

Edition:

First edition.

Place of Publication:

Amsterdam ; Boston : Elsevier ; London : Academic Press, 2011.

Summary:

According to the National Institute of Health, a genome-wide association study is defined as any study of genetic variation across the entire human genome that is designed to identify genetic associations with observable traits (such as blood pressure or weight), or the presence or absence of a disease or condition. Whole genome information, when combined with clinical and other phenotype data, offers the potential for increased understanding of basic biological processes affecting human health, improvement in the prediction of disease and patient care, and ultimately the realization of the promise of personalized medicine. In addition, rapid advances in understanding the patterns of human genetic variation and maturing high-throughput, cost-effective methods for genotyping are providing powerful research tools for identifying genetic variants that contribute to health and disease. (good paragraph) This burgeoning science merges the principles of statistics and genetics studies to make sense of the vast amounts of information available with the mapping of genomes. In order to make the most of the information available, statistical tools must be tailored and translated for the analytical issues which are original to large-scale association studies. This book will provide researchers with advanced biological knowledge who are entering the field of genome-wide association studies with the groundwork to apply statistical analysis tools appropriately and effectively. With the use of consistent examples throughout the work, chapters will provide readers with best practice for getting started (design), analyzing, and interpreting data according to their research interests. Frequently used tests will be highlighted and a critical analysis of the advantages and disadvantage complimented by case studies for each will provide readers with the information they need to make the right choice for their research.

Contents:

Genetic architecture of complex diseases

Population genetics and linkage disequilibrium

Genetic association study design

Tag SNP selection

Genotype calling

Data handling

Data quality control

Single-locus tests of association for population-based studies

Effects of population structure in genome-wide association studies

Genotype imputation

Haplotype methods for population-based association studies

Gene-Gene interaction and epistasis

Copy number variant association studies

Family-based association methods

Bioinformatics approaches

Interpreting association signals

Delineating signals from association studies

A genome-wide case study on obesity

Case study on rheumatoid arthritis.

Notes:

Includes bibliographical references and index.

ISBN:

9780123751423

012375142X

OCLC:

610157476