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Large Scale Association Analysis for Drug Addiction: Results from SNP to Gene
Many genetic association studies used single nucleotide polymorphisms (SNPs) data to identify genetic variants for complex diseases. Although SNP-based associations are most common in genome-wide association studies (GWAS), gene-based association analysis has received increasing attention in underst...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Scientific World Journal
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3543790/ https://www.ncbi.nlm.nih.gov/pubmed/23365539 http://dx.doi.org/10.1100/2012/939584 |
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author | Guo, Xiaobo Liu, Zhifa Wang, Xueqin Zhang, Heping |
author_facet | Guo, Xiaobo Liu, Zhifa Wang, Xueqin Zhang, Heping |
author_sort | Guo, Xiaobo |
collection | PubMed |
description | Many genetic association studies used single nucleotide polymorphisms (SNPs) data to identify genetic variants for complex diseases. Although SNP-based associations are most common in genome-wide association studies (GWAS), gene-based association analysis has received increasing attention in understanding genetic etiologies for complex diseases. While both methods have been used to analyze the same data, few genome-wide association studies compare the results or observe the connection between them. We performed a comprehensive analysis of the data from the Study of Addiction: Genetics and Environment (SAGE) and compared the results from the SNP-based and gene-based analyses. Our results suggest that the gene-based method complements the individual SNP-based analysis, and conceptually they are closely related. In terms of gene findings, our results validate many genes that were either reported from the analysis of the same dataset or based on animal studies for substance dependence. |
format | Online Article Text |
id | pubmed-3543790 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | The Scientific World Journal |
record_format | MEDLINE/PubMed |
spelling | pubmed-35437902013-01-30 Large Scale Association Analysis for Drug Addiction: Results from SNP to Gene Guo, Xiaobo Liu, Zhifa Wang, Xueqin Zhang, Heping ScientificWorldJournal Research Article Many genetic association studies used single nucleotide polymorphisms (SNPs) data to identify genetic variants for complex diseases. Although SNP-based associations are most common in genome-wide association studies (GWAS), gene-based association analysis has received increasing attention in understanding genetic etiologies for complex diseases. While both methods have been used to analyze the same data, few genome-wide association studies compare the results or observe the connection between them. We performed a comprehensive analysis of the data from the Study of Addiction: Genetics and Environment (SAGE) and compared the results from the SNP-based and gene-based analyses. Our results suggest that the gene-based method complements the individual SNP-based analysis, and conceptually they are closely related. In terms of gene findings, our results validate many genes that were either reported from the analysis of the same dataset or based on animal studies for substance dependence. The Scientific World Journal 2012-12-27 /pmc/articles/PMC3543790/ /pubmed/23365539 http://dx.doi.org/10.1100/2012/939584 Text en Copyright © 2012 Xiaobo Guo et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Guo, Xiaobo Liu, Zhifa Wang, Xueqin Zhang, Heping Large Scale Association Analysis for Drug Addiction: Results from SNP to Gene |
title | Large Scale Association Analysis for Drug Addiction: Results from SNP to Gene |
title_full | Large Scale Association Analysis for Drug Addiction: Results from SNP to Gene |
title_fullStr | Large Scale Association Analysis for Drug Addiction: Results from SNP to Gene |
title_full_unstemmed | Large Scale Association Analysis for Drug Addiction: Results from SNP to Gene |
title_short | Large Scale Association Analysis for Drug Addiction: Results from SNP to Gene |
title_sort | large scale association analysis for drug addiction: results from snp to gene |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3543790/ https://www.ncbi.nlm.nih.gov/pubmed/23365539 http://dx.doi.org/10.1100/2012/939584 |
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