A SENSITIVE METHOD FOR DETECTING DINUCLEOTIDE ISLANDS AND CLUSTERS THROUGH DEPTH ANALYSIS

Abstract

The field of bioinformatics is an essential asset for modern biology. In recent years, after the appearance of GWS (Genome Wide Scan) studies, powerful bioinformatics methods have been developed. In order to understand the genetic basis of various diseases, especially polygenic diseases (diabetes, obesity and vascular disease), we have implemented a dynamic method named "in-depth analysis" to detect and interpret CpG islands, CpG clusters and other dinucleotide structures. In-depth analysis is made through repeated tests with different dinucleotide thresholds. GCLUSTER is our design for "in-depth analysis". We tested GCLUSTER with randomly generated DNA sequences, multiple genes from Homo sapiens and several types of viral genomes.