Department of Genetics and Bioinformatics, Faculty of Arts and Sciences, Bahcesehir University, 34353, Besiktas, Istanbul, Turkey, Department of Computer Engineering, Faculty of Engineering and Natural Sciences, Abdullah Gul University, 38039, Kayseri, Turkey, Department of Computer Engineering, Faculty of Engineering and Natural Sciences, Sabanci University, 34956, Tuzla, Istanbul, Turkey and Department of Biological Sciences and Bioengineering, Faculty of Engineering and Natural Sciences, Sabanci University, 34956, Tuzla, Istanbul, Turkey.
Bioinformatics. 2014 May 1;30(9):1287-9. doi: 10.1093/bioinformatics/btt743. Epub 2014 Jan 11.
Genome-wide association studies (GWAS) have revolutionized the search for the variants underlying human complex diseases. However, in a typical GWAS, only a minority of the single-nucleotide polymorphisms (SNPs) with the strongest evidence of association is explained. One possible reason of complex diseases is the alterations in the activity of several biological pathways. Here we present a web server called Pathway and Network-Oriented GWAS Analysis to devise functionally important pathways through the identification of SNP-targeted genes within these pathways. The strength of our methodology stems from its multidimensional perspective, where we combine evidence from the following five resources: (i) genetic association information obtained through GWAS, (ii) SNP functional information, (iii) protein-protein interaction network, (iv) linkage disequilibrium and (v) biochemical pathways.
全基因组关联研究(GWAS)已经彻底改变了寻找人类复杂疾病相关变体的方法。然而,在典型的 GWAS 中,只有少数具有最强关联证据的单核苷酸多态性(SNP)得到了解释。复杂疾病的一个可能原因是几个生物途径活性的改变。在这里,我们介绍了一个名为“Pathway and Network-Oriented GWAS Analysis”的网络服务器,该服务器旨在通过识别这些途径中的 SNP 靶向基因来设计具有重要功能的途径。我们的方法的优势在于其多维视角,我们结合了以下五个资源的证据:(i)通过 GWAS 获得的遗传关联信息,(ii)SNP 功能信息,(iii)蛋白质-蛋白质相互作用网络,(iv)连锁不平衡和(v)生化途径。