A general framework for the evaluation of genetic association studies using multiple marginal models

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Standard

A general framework for the evaluation of genetic association studies using multiple marginal models. / Kitsche, Andreas; Ritz, Christian; Hothorn, Ludwig A.

I: Human Heredity, Bind 81, Nr. 3, 22.12.2016, s. 150-172.

Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt

Harvard

Kitsche, A, Ritz, C & Hothorn, LA 2016, 'A general framework for the evaluation of genetic association studies using multiple marginal models', Human Heredity, bind 81, nr. 3, s. 150-172. https://doi.org/10.1159/000448477

APA

Kitsche, A., Ritz, C., & Hothorn, L. A. (2016). A general framework for the evaluation of genetic association studies using multiple marginal models. Human Heredity, 81(3), 150-172. https://doi.org/10.1159/000448477

Vancouver

Kitsche A, Ritz C, Hothorn LA. A general framework for the evaluation of genetic association studies using multiple marginal models. Human Heredity. 2016 dec. 22;81(3):150-172. https://doi.org/10.1159/000448477

Author

Kitsche, Andreas ; Ritz, Christian ; Hothorn, Ludwig A. / A general framework for the evaluation of genetic association studies using multiple marginal models. I: Human Heredity. 2016 ; Bind 81, Nr. 3. s. 150-172.

Bibtex

@article{adc5ba194ba24fdfb9010ef88651d3db,
title = "A general framework for the evaluation of genetic association studies using multiple marginal models",
abstract = "OBJECTIVE: In this study, we present a simultaneous inference procedure as a unified analysis framework for genetic association studies.METHODS: The method is based on the formulation of multiple marginal models that reflect different modes of inheritance. The basic advantage of this methodology is that no explicit formulation of the correlation between the test statistics is required. Moreover, the genotype scores are considered as a quantitative explanatory variable, i.e., regression models are used.RESULTS: The proposed approach covers a wide variety of endpoints (binary, count, quantitative, and time-to-event data). In addition, multiple endpoints of different types can be assessed simultaneously. This allows the detection of pleiotropic effects while taking the mode of inheritance into account. Moreover, multiple loci can be assessed simultaneously.CONCLUSION: The flexibility of the proposed approach is demonstrated while analyzing a variety of data examples.",
keywords = "Faculty of Science, Genetic association, Generalized linear models, Pleiotropy, Simultaneous inference",
author = "Andreas Kitsche and Christian Ritz and Hothorn, {Ludwig A.}",
note = "CURIS 2016 NEXS 372",
year = "2016",
month = dec,
day = "22",
doi = "10.1159/000448477",
language = "English",
volume = "81",
pages = "150--172",
journal = "Human Heredity",
issn = "0001-5652",
publisher = "S Karger AG",
number = "3",

}

RIS

TY - JOUR

T1 - A general framework for the evaluation of genetic association studies using multiple marginal models

AU - Kitsche, Andreas

AU - Ritz, Christian

AU - Hothorn, Ludwig A.

N1 - CURIS 2016 NEXS 372

PY - 2016/12/22

Y1 - 2016/12/22

N2 - OBJECTIVE: In this study, we present a simultaneous inference procedure as a unified analysis framework for genetic association studies.METHODS: The method is based on the formulation of multiple marginal models that reflect different modes of inheritance. The basic advantage of this methodology is that no explicit formulation of the correlation between the test statistics is required. Moreover, the genotype scores are considered as a quantitative explanatory variable, i.e., regression models are used.RESULTS: The proposed approach covers a wide variety of endpoints (binary, count, quantitative, and time-to-event data). In addition, multiple endpoints of different types can be assessed simultaneously. This allows the detection of pleiotropic effects while taking the mode of inheritance into account. Moreover, multiple loci can be assessed simultaneously.CONCLUSION: The flexibility of the proposed approach is demonstrated while analyzing a variety of data examples.

AB - OBJECTIVE: In this study, we present a simultaneous inference procedure as a unified analysis framework for genetic association studies.METHODS: The method is based on the formulation of multiple marginal models that reflect different modes of inheritance. The basic advantage of this methodology is that no explicit formulation of the correlation between the test statistics is required. Moreover, the genotype scores are considered as a quantitative explanatory variable, i.e., regression models are used.RESULTS: The proposed approach covers a wide variety of endpoints (binary, count, quantitative, and time-to-event data). In addition, multiple endpoints of different types can be assessed simultaneously. This allows the detection of pleiotropic effects while taking the mode of inheritance into account. Moreover, multiple loci can be assessed simultaneously.CONCLUSION: The flexibility of the proposed approach is demonstrated while analyzing a variety of data examples.

KW - Faculty of Science

KW - Genetic association

KW - Generalized linear models

KW - Pleiotropy

KW - Simultaneous inference

U2 - 10.1159/000448477

DO - 10.1159/000448477

M3 - Journal article

C2 - 28002824

VL - 81

SP - 150

EP - 172

JO - Human Heredity

JF - Human Heredity

SN - 0001-5652

IS - 3

ER -

ID: 170799986