Genetic Epidemiology
Springer New York
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Attention Score in Context
| Chapter title |
Multivariate Methods for Meta-Analysis of Genetic Association Studies
|
|---|---|
| Book title |
Genetic Epidemiology
|
| Published in |
Methods in molecular biology, January 2018
|
| DOI | 10.1007/978-1-4939-7868-7_11 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-7867-0, 978-1-4939-7868-7
|
| Authors |
Niki L. Dimou, Katerina G. Pantavou, Georgia G. Braliou, Pantelis G. Bagos |
| Abstract |
Multivariate meta-analysis of genetic association studies and genome-wide association studies has received a remarkable attention as it improves the precision of the analysis. Here, we review, summarize and present in a unified framework methods for multivariate meta-analysis of genetic association studies and genome-wide association studies. Starting with the statistical methods used for robust analysis and genetic model selection, we present in brief univariate methods for meta-analysis and we then scrutinize multivariate methodologies. Multivariate models of meta-analysis for a single gene-disease association studies, including models for haplotype association studies, multiple linked polymorphisms and multiple outcomes are discussed. The popular Mendelian randomization approach and special cases of meta-analysis addressing issues such as the assumption of the mode of inheritance, deviation from Hardy-Weinberg Equilibrium and gene-environment interactions are also presented. All available methods are enriched with practical applications and methodologies that could be developed in the future are discussed. Links for all available software implementing multivariate meta-analysis methods are also provided. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 50% |
| Colombia | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 50% |
| Scientists | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Greece | 1 | 6% |
| Unknown | 16 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 3 | 18% |
| Researcher | 3 | 18% |
| Other | 2 | 12% |
| Student > Bachelor | 1 | 6% |
| Professor | 1 | 6% |
| Other | 5 | 29% |
| Unknown | 2 | 12% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 7 | 41% |
| Agricultural and Biological Sciences | 2 | 12% |
| Medicine and Dentistry | 2 | 12% |
| Social Sciences | 1 | 6% |
| Mathematics | 1 | 6% |
| Other | 0 | 0% |
| Unknown | 4 | 24% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 12 June 2018.
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#18,639,173
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Outputs from Methods in molecular biology
#7,987
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Outputs of similar age from Methods in molecular biology
#950
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