Statistical Approaches to Gene x Environment Interactions for Complex Phenotypes (The MIT Press)

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

ISBN 10: 0262034689 / ISBN 13: 9780262034685

Verlag: The MIT Press, 2016

Beschreibung

LIKE NEW!!! Has a red or black remainder mark on bottom/exterior edge of pages. Bestandsnummer des Verkäufers MIT-HC-LN-0262034689

Bibliografische Details

Titel: Statistical Approaches to Gene x Environment...

Verlag: The MIT Press

Erscheinungsdatum: 2016

Einband: hardcover

Zustand: As New

Auflage: 1.

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Inhaltsangabe:

Statistical Approaches To Gene X Environment Interactions For Complex Phenotypes BY Michael Windle, Mit Press, Hardcover, 2016

Reseña del editor:

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 x 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 x E and G x G interactions with high-throughput sequenced data, including two-stage procedures to identify G x E and G x 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 x 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 x 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