Towards constructing disease relationship networks using genome-wide association studies
Background: Genome-wide association studies (GWAS) prove to be a powerful approach to identify the genetic basis of various human diseases. Here we take advantage of existing GWAS data and attempt to build a framework to understand the complex relationships among diseases. Specifically, we examined 49 diseases from all available GWAS with a cascade approach by exploiting network analysis to study the single nucleotide polymorphisms (SNP) effect on the similarity between different diseases. Proteins within perturbation subnetwork are considered to be connection points between the disease similarity networks. Results: shared disease subnetwork proteins are consistent, accurate and sensitive to measure genetic similarity between diseases. Clustering result shows the evidence of phenome similarity. Conclusion: our results prove the usefulness of genetic profiles for evaluating disease similarity and constructing disease relationship networks.
Wenhui Huang Liqing Zhang
Department of Computer Science, Virginia Tech, 2050 Torgerson Hall, Blacksburg, VA 24061-0106, USA Department of Computer Science, Virginia Tech, 2050 Torgerson Hall, Blacksburg, VA 24061-0106, USA P
国际会议
成都
英文
1-6
2010-06-18（万方平台首次上网日期，不代表论文的发表时间）