Analysis of complex disease association studies
Subtitle: a practical guide
By: edited by Eleftheria Zeggini, Andrew Morris
Edition: 1st ed.
Publisher: Academic Press/Elsevier
Published: 2011
Place of publication: London; Burlington, MA
Language: eng
Number of pages: 331
ISBN-13: 9780123751423
Subjects: Genetic disorders; Diseases; Variation; Human genetics
Description: 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.
Notes: Includes bibliographical references and index.
Table of contents: title: Genetic architecture of complex diseases --; title: Population genetics and linkage disequilibrium --; title: Genetic association study design --; title: Tag SNP selection --; title: Genotype calling --; title: Data handling --; title: Data quality control --; title: Single-locus tests of association for population-based studies --; title: Effects of population structure in genome-wide association studies --; title: Genotype imputation --; title: Haplotype methods for population-based association studies --; title: Gene-Gene interaction and epistasis --; title: Copy number variant association studies --; title: Family-based association methods --; title: Bioinformatics approaches --; title: Interpreting association signals --; title: Delineating signals from association studies --; title: A genome-wide case study on obesity --; title: Case study on rheumatoid arthritis.