Genome-Wide Association Studies and Genomic Prediction

by Cedric Gondro (Editor), Julius van der Werf (Editor), Ben Hayes (Editor)

With the detailed genomic information that is now becoming available, we havea plethora of data that allows researchers to address questions in a variety of areas. Genome-wide association studies (GWAS) have become a vital approach to identify candidate regions associated with complex diseases in human medicine, production traits in agriculture, and variation in wild populations. Genomic prediction goes a step further, attempting to predict phenotypic variation in these traits from genomic information. "Genome-Wide Association Studies and Genomic Prediction "pulls together expert contributions to address this important area of study. The volume begins with a section covering the phenotypes of interest as well as design issues for GWAS, then moves on to discuss efficient computational methods to store and handle large datasets, quality control measures, phasing, haplotype inference, and imputation. Later chapters deal with statistical approaches to data analysis where the experimental objective is either to confirm the biology by identifying genomic regions associated to a trait or to use the data to make genomic predictions about a future phenotypic outcome (e.g. predict onset of disease). As part of the "Methods in Molecular Biology" series, chapters provide helpful, real-world implementation advice.

577 pages, Hardcover

First published June 25, 2013