CpGcluster: a distance-based algorithm for CpG-island detection

Background: Despite their involvement in the regulation of gene expression and their importance as genomic markers for promoter prediction, no objective standard exists for defining CpG islands (CGIs), since all current approaches rely on a large parameter space formed by the thresholds of length, CpG fraction and G+C content. Results: Given the higher frequency of CpG dinucleotides at CGIs, as compared to bulk DNA, the distance distributions between neighboring CpGs should differ for bulk and island CpGs. A new algorithm (CpGcluster) is presented, based on the physical distance between neighboring CpGs on the chromosome and able to predict directly clusters of CpGs, while not depending on the subjective criteria mentioned above. By assigning a p-value to each of these clusters, the most statistically significant ones can be predicted as CGIs. CpGcluster was benchmarked against five other CGI finders by using a test sequence set assembled from an experimental CGI library. CpGcluster r...

• Type: Journal
• Year: 2006
• Where: BMCBI
• Authors: Michael Hackenberg, Christopher Previti, Pedro Luis Luque-Escamilla, Pedro Carpena, José Martínez-Aroza, José L. Oliver
• Keywords: BMCBI 2006, CpG Islands, CPGs, Statistically Significant