A multi-layered graphical model of the relation among SNPs, genes, and pathways based on subgraph search


Thesis Type: Postgraduate

Institution Of The Thesis: Orta Doğu Teknik Üniversitesi, Graduate School of Informatics, Medical Informatics, Turkey

Approval Date: 2015

Student: GÖKHAN ERSOY

Co-Supervisor: YEŞİM AYDIN SON, TOLGA CAN

Abstract:

The analysis of Single Nucleotide Polymorphisms (SNPs) through Genome Wide Association Studies (GWAS) presents great potential for describing disease loci and gaining insight into the underlying etiology of diseases. Recently described combined p-value approach allows identification of associations at gene and pathway level. The integrated programs like METU-SNP produce simple lists of either SNP id/gene id/pathway title and their p-values and significance status or SNP id/disease id/pathway information. In this study, starting with the SNP id, we have annotated related gene ids and pathway ids consecutively. Then we have computed the intersection of these pathways, and visualized the common sub-graphs by an interactive graphical library. The tool developed in this thesis provides a visualization of the text output as graphical knowledge networks; hence, facilitates the efficient use of the information offered by the candidate SNP Biomarkers and helping discovery of SNP associated biological networks