DocumentCode
3317408
Title
Notice of Retraction
A Comparison of Power among Analytical Methods of Gene-Environment Interactions
Author
Jie Wei ; Lianguo Fu ; Xuesen Wu
Author_Institution
Dept. of Phys., Bengbu Med. Coll., Bengbu, China
fYear
2011
fDate
10-12 May 2011
Firstpage
1
Lastpage
3
Abstract
Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
Complex diseases are multifactorial traits caused by both genetic and environmental factors. Despite a large amount of information that has been collected about both genetic and environmental risk factors, there are few examples of studies on their interactions in epidemiological literature. One reason could be the incomplete knowledge of the power of statistical methods designed to search for risk factors and their interactions in these data sets. To address this problem, a number of novel methods have been developed. In the current study, we compare the performance of five analytical approaches based on the odd ratios of risk factors to detect Gene environment interactions in a range of genetic models. Mutual information, crossover analysis, dummy variable based on crossover analysis, interaction based on the linkage disequilibrium and explicit logistic regression were compared.
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
Complex diseases are multifactorial traits caused by both genetic and environmental factors. Despite a large amount of information that has been collected about both genetic and environmental risk factors, there are few examples of studies on their interactions in epidemiological literature. One reason could be the incomplete knowledge of the power of statistical methods designed to search for risk factors and their interactions in these data sets. To address this problem, a number of novel methods have been developed. In the current study, we compare the performance of five analytical approaches based on the odd ratios of risk factors to detect Gene environment interactions in a range of genetic models. Mutual information, crossover analysis, dummy variable based on crossover analysis, interaction based on the linkage disequilibrium and explicit logistic regression were compared.
Keywords
biology; diseases; environmental factors; regression analysis; statistical analysis; complex disease; crossover analysis; dummy variable; environmental risk factors; epidemiological literature; gene environment interaction; genetic models; linkage disequilibrium; logistic regression; multifactorial trait; mutual information; statistical methods; Analytical models; Diseases; Error analysis; Genetics; Logistics; Mutual information;
fLanguage
English
Publisher
ieee
Conference_Titel
Bioinformatics and Biomedical Engineering, (iCBBE) 2011 5th International Conference on
Conference_Location
Wuhan
ISSN
2151-7614
Print_ISBN
978-1-4244-5088-6
Type
conf
DOI
10.1109/icbbe.2011.5779995
Filename
5779995
Link To Document