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" Genome-wide association studies and genomic prediction "
edited by Cedric Gondro, The Center for Genetic Analysis and Applications, University of New England, Armidale, NSW, Australia, Julius van der Werf, School of Environmental and rural Science, University of New England, Armidale, NSW, Australia, Ben Hayes, Biosciences Research Division, Department of Primary Industries, Bundoora, VIC, Australia.
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BL
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| Record Number
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569612
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GBB381335b398831
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| Title & Author
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Genome-wide association studies and genomic prediction\ edited by Cedric Gondro, The Center for Genetic Analysis and Applications, University of New England, Armidale, NSW, Australia, Julius van der Werf, School of Environmental and rural Science, University of New England, Armidale, NSW, Australia, Ben Hayes, Biosciences Research Division, Department of Primary Industries, Bundoora, VIC, Australia.
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| Publication Statement
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New York :: Humana Press,, [2013]
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| Series Statement
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Methods of molecular biology,; 1019
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Springer protocols,
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| ISBN
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9781627034463
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: 1627034463
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9781627034470
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Includes bibliographical references and index.
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| Abstract
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"With the detailed genomic information that is now becoming available, we have a 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."--
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Molecular genetics.
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Variation (Biology)
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Genome-Wide Association Study.
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Genetic Testing.
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Genomics.
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| Added Entry
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Gondro, Cedric.
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Werf, Julius van der.
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Hayes, Ben, (Ben J.)
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