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Statistical Approaches to Gene X Environment Interactions for Complex Phenotypes

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Title: Statistical Approaches to Gene X Environment Interactions for Complex Phenotypes
Description: 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.ContributorsFatima 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
Authors: Michael Windle
Resource Type: eBook.
Subjects: Genotype-environment interaction--Statistical methods
Categories: SCIENCE / Bioinformatics, PSYCHOLOGY / Psychopathology / General, SCIENCE / Life Sciences / Genetics & Genomics
Database: eBook Collection (EBSCOhost)
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  Data: 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.ContributorsFatima 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
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        Scheme: ddc
        Type: prePub
    Languages:
      – Code: eng
        Text: English
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      – SubjectFull: Genotype-environment interaction--Statistical methods
        Type: general
    Titles:
      – TitleFull: Statistical Approaches to Gene X Environment Interactions for Complex Phenotypes
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            NameFull: Michael Windle
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            – D: 01
              M: 01
              Type: published
              Y: 2016
            – D: 15
              M: 07
              Type: profile
              Y: 2016
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              Value: 9780262034685
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            – TitleFull: Statistical Approaches to Gene X Environment Interactions for Complex Phenotypes
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