CpGIScan: An Ultrafast Tool for CpG Islands Identification from Genome Sequence

Title:CpGIScan: An Ultrafast Tool for CpG Islands Identification from Genome Sequence

Volume: 12 Issue: 2

Author(s): Zuoyi Jian, Lianming Du, Xiuyue Zhang, Bisong Yue and Zhenxin Fan*

Affiliation:

• Sichuan Key Laboratory of Conservation Biology on Endangered Wildlife, College of Life Sciences, Sichuan University, Chengdu, 610064,China

Keywords: CpG island, prediction algorithm, genome annotation, methylation, unmethylated region, sliding window.

Abstract: Background: The CpG islands (CGIs) are clusters of CpGs in CG-rich regions, which confer a critical role in the regulation of transcription. Although multiple programs are developed for searching CGIs, but all of them have drawbacks, such as low accuracy or long running time.

Objective: The aim of this study was to develop a new CGIs search tool, namely CpGIScan (CpG Islands Scan), which improves upon previous programs.

Method: In this work, a CpG island is defined by three types of parameters: the window length, the guanine and cytosine (G + C) frequency, and the ratio of the observed over the expected CpGs (CpG o/e). The algorithm in CpGIScan is based on the sliding window method. To reduce the time required to identify CGIs, multithread technology is employed in our program. CpGIScan was compared to existing widely used tools to benchmark its performance.

Results: Evaluations on a set of test sequences show that CpGIScan has high sensitivity and specificity. In addition, CpGIScan is at least 4 times faster than existing tools. It has a large performance advantage over previous tools when searching CpG islands from the bulk genomes. CpGIScan is written in C++ and provided under the GNU CPL license. It is freely available at https://github.com/jianzuoyi/CpGIScan.

Conclusion: CpGIScan was specifically developed for ultrafast identifying CGIs in large sequences sets. It takes the advantages of previous tools and significantly improves the computational efficiency. CpGIScan will be of value to researchers for generating an initial genome-wide map of CpG islands.

Cite this article as:

Jian Zuoyi, Du Lianming, Zhang Xiuyue, Yue Bisong and Fan Zhenxin*, CpGIScan: An Ultrafast Tool for CpG Islands Identification from Genome Sequence, Current Bioinformatics 2017; 12 (2) . https://dx.doi.org/10.2174/1574893611666160907111325

DOI https://dx.doi.org/10.2174/1574893611666160907111325	Print ISSN 1574-8936
Publisher Name Bentham Science Publisher	Online ISSN 2212-392X