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Statistical Approaches to Gene X Environment Interactions for Complex Phenotypes (Hardcover)

Michael Windle

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ISBN 10: 0262034689 / ISBN 13: 9780262034685
Nuevos Condición: New Encuadernación de tapa dura
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Hardcover. Diverse methodological and statistical approaches for investigating the role of gene-environment interactions in a range of complex diseases and traits.Findings from the Human.Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. 304 pages. 0.534. N° de ref. de la librería 9780262034685

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Detalles bibliográficos

Título: Statistical Approaches to Gene X Environment...

Año de publicación: 2016

Encuadernación: Hardcover

Condición del libro:New

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Sinopsis:

Diverse methodological and statistical approaches for investigating the role of gene-environment interactions in a range of complex diseases and traits.

Findings from the Human Genome Project and from Genome-Wide Association (GWA) studies indicate that many diseases and traits manifest a more complex genomic pattern than previously assumed. These findings, and advances in high-throughput sequencing, suggest that there are many sources of influence -- genetic, epigenetic, and environmental. This volume investigates the role of the interactions of genes and environment (G × E) in diseases and traits (referred to by the contributors as complex phenotypes) including depression, diabetes, obesity, and substance use.

The contributors first present different statistical approaches or strategies to address G × E and G × G interactions with high-throughput sequenced data, including two-stage procedures to identify G × E and G × G interactions, marker-set approaches to assessing interactions at the gene level, and the use of a partial-least square (PLS) approach. The contributors then turn to specific complex phenotypes, research designs, or combined methods that may advance the study of G × E interactions, considering such topics as randomized clinical trials in obesity research, longitudinal research designs and statistical models, and the development of polygenic scores to investigate G × E interactions.

Contributors
Fatima Umber Ahmed, Yin-Hsiu Chen, James Y. Dai, Caroline Y. Doyle, Zihuai He, Li Hsu, Shuo Jiao, Erin Loraine Kinnally, Yi-An Ko, Charles Kooperberg, Seunggeun Lee, Arnab Maity, Jeanne M. McCaffery, Bhramar Mukherjee, Sung Kyun Park, Duncan C. Thomas, Alexandre Todorov, Jung-Ying Tzeng, Tao Wang, Michael Windle, Min Zhang

About the Author:

Michael Windle is Professor of Public Health in the Department of Behavioral Sciences and Health Education at Emory University.

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