Mixed Modeling with Whole Genome Data
Joint Authors
Source
Journal of Probability and Statistics
Issue
Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-16, 16 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2012-06-28
Country of Publication
Egypt
No. of Pages
16
Main Subjects
Abstract EN
Objective.
We consider the need for a modeling framework for related individuals and various sources of variations.
The relationships could either be among relatives in families or among unrelated individuals in a general population with cryptic relatedness; both could be refined or derived with whole genome data.
As with variations they can include oliogogenes, polygenes, single nucleotide polymorphism (SNP), and covariates.
Methods.
We describe mixed models as a coherent theoretical framework to accommodate correlations for various types of outcomes in relation to many sources of variations.
The framework also extends to consortium meta-analysis involving both population-based and family-based studies.
Results.
Through examples we show that the framework can be furnished with general statistical packages whose great advantage lies in simplicity and exibility to study both genetic and environmental effects.
Areas which require further work are also indicated.
Conclusion.
Mixed models will play an important role in practical analysis of data on both families and unrelated individuals when whole genome information is available.
American Psychological Association (APA)
Zhao, Jing Hua& Luan, Jian'an. 2012. Mixed Modeling with Whole Genome Data. Journal of Probability and Statistics،Vol. 2012, no. 2012, pp.1-16.
https://search.emarefa.net/detail/BIM-475356
Modern Language Association (MLA)
Zhao, Jing Hua& Luan, Jian'an. Mixed Modeling with Whole Genome Data. Journal of Probability and Statistics No. 2012 (2012), pp.1-16.
https://search.emarefa.net/detail/BIM-475356
American Medical Association (AMA)
Zhao, Jing Hua& Luan, Jian'an. Mixed Modeling with Whole Genome Data. Journal of Probability and Statistics. 2012. Vol. 2012, no. 2012, pp.1-16.
https://search.emarefa.net/detail/BIM-475356
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-475356