alexa Gene and pathway-based second-wave analysis of genome-wide association studies.
Genetics

Genetics

Advancements in Genetic Engineering

Author(s): Peng G, Luo L, Siu H, Zhu Y, Hu P,

Abstract Share this page

Abstract Despite the great success of genome-wide association studies (GWAS) in identification of the common genetic variants associated with complex diseases, the current GWAS have focused on single-SNP analysis. However, single-SNP analysis often identifies only a few of the most significant SNPs that account for a small proportion of the genetic variants and offers only a limited understanding of complex diseases. To overcome these limitations, we propose gene and pathway-based association analysis as a new paradigm for GWAS. As a proof of concept, we performed a comprehensive gene and pathway-based association analysis of 13 published GWAS. Our results showed that the proposed new paradigm for GWAS not only identified the genes that include significant SNPs found by single-SNP analysis, but also detected new genes in which each single SNP conferred a small disease risk; however, their joint actions were implicated in the development of diseases. The results also showed that the new paradigm for GWAS was able to identify biologically meaningful pathways associated with the diseases, which were confirmed by a gene-set-rich analysis using gene expression data.
This article was published in Eur J Hum Genet and referenced in Advancements in Genetic Engineering

Relevant Expert PPTs

Relevant Speaker PPTs

Recommended Conferences

  • International Conference on Epigenetics 2017
    November 13-15, 2017 Frankfurt, Germany
  • International Conference on Genetic Counseling and Genomic Medicine
    February 12-13, 2018 Madrid, Spain

Relevant Topics

Peer Reviewed Journals
 
Make the best use of Scientific Research and information from our 700 + peer reviewed, Open Access Journals
International Conferences 2017-18
 
Meet Inspiring Speakers and Experts at our 3000+ Global Annual Meetings

Contact Us

 
© 2008-2017 OMICS International - Open Access Publisher. Best viewed in Mozilla Firefox | Google Chrome | Above IE 7.0 version
adwords