z-logo
open-access-imgOpen Access
Research strategies for the next step of genome-wide association study
Author(s) -
Cheng Quan,
Xuejun Zhang
Publication year - 2011
Publication title -
hereditas (beijing)
Language(s) - English
Resource type - Journals
ISSN - 0253-9772
DOI - 10.3724/sp.j.1005.2011.00100
Subject(s) - genome wide association study , epistasis , genetic association , biology , computational biology , genotyping , imputation (statistics) , genetics , genome , gene , single nucleotide polymorphism , computer science , genotype , missing data , machine learning
Since 2005, genome-wide association studies (GWAS) have yielded an unprecedented number of complex dis-eases/traits-associated variants. Recently, scientists have focused on performing further analysis by utilizing the genome-wide genotyping data to identify more susceptibility genes of complex diseases/traits. Many strategies and methods have been applied in the following GWAS, such as screening other new susceptibility genes/loci for complex diseases/traits, international collaboration and meta-analysis, fine mapping and resequencing, studies on shared susceptibility genes in different diseases, imputation methods, pathway analysis, gene-gene and gene-environment interaction, and epistasis study and so on. The application of these strategies and methods compensates the limitation of the traditional GWAS and provides new insights into genetics basis of complex diseases/traits. We reviewed these strategies and methods, as well as their difficulty and challenge. Meanwhile, we presented a brief framework of GWAS next step to readers.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom