CpG islands play an important role in genes transcription regulation, due to the fact that these islands overlap with the genes’ promoter regions, and the methylation of those CpG islands may repress the transcription of the associated genes. Previou
s studies reported that
methylation of CpG islands is an important indicator of the presence and possibility of
developing cancers. There are mainly two types of algorithms to identify CpG islands in the nucleotides sequences: distance-based and sliding-window algorithms. The outputs of these algorithms are different for the same nucleotide sequence. The aim of this study is to compare the performance of the above mentioned algorithms by using two web tools named CpGCluster and newCpGReport.
CpG islands in human chromosome 22 were identified by applying the two algorithms on this chromosome, and the variation in the number and length of the identified islands was clear.
The results also show that about 60% of both tools’ output is crossed. Moreover, the effect of the traditional parameters of CpG islands (length, C+G content and Observed/expected ratio)
on the number of the identified islands was studied. The results show that the length parameter has a great effect on the number of islands identified by newCpGReport, while it does not affect CpGCluster’s performance. The effect of making CpG islands identified by
newCpGReport start and end with CpG was also studied, due to this operation C+G content and Observed/expected ratio increased for most islands, taking into account that 25% of the islands became shorter than 200 nucleotides.
