Literature DB >> 17907576

CpG PatternFinder: a Windows-based utility program for easy and rapid identification of the CpG methylation status of DNA.

Yi-Hua Xu1, Herbert T Manoharan, Henry C Pitot.   

Abstract

The bisulfite genomic sequencing technique is one of the most widely used techniques to study sequence-specific DNA methylation because of its unambiguous ability to reveal DNA methylation status to the order of a single nucleotide. One characteristic feature of the bisulfite genomic sequencing technique is that a number of sample sequence files will be produced from a single DNA sample. The PCR products of bisulfite-treated DNA samples cannot be sequenced directly because they are heterogeneous in nature; therefore they should be cloned into suitable plasmids and then sequenced. This procedure generates an enormous number of sample DNA sequence files as well as adding extra bases belonging to the plasmids to the sequence, which will cause problems in the final sequence comparison. Finding the methylation status for each CpG in each sample sequence is not an easy job. As a result CpG PatternFinder was developed for this purpose. The main functions of the CpG PatternFinder are: (i) to analyze the reference sequence to obtain CpG and non-CpG-C residue position information. (ii) To tailor sample sequence files (delete insertions and mark deletions from the sample sequence files) based on a configuration of ClustalW multiple alignment. (iii) To align sample sequence files with a reference file to obtain bisulfite conversion efficiency and CpG methylation status. And, (iv) to produce graphics, highlighted aligned sequence text and a summary report which can be easily exported to Microsoft Office suite. CpG PatternFinder is designed to operate cooperatively with BioEdit, a freeware on the internet. It can handle up to 100 files of sample DNA sequences simultaneously, and the total CpG pattern analysis process can be finished in minutes. CpG PatternFinder is an ideal software tool for DNA methylation studies to determine the differential methylation pattern in a large number of individuals in a population. Previously we developed the CpG Analyzer program; CpG PatternFinder is our further effort to create software tools for DNA methylation studies.

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Year:  2007        PMID: 17907576     DOI: 10.2144/000112537

Source DB:  PubMed          Journal:  Biotechniques        ISSN: 0736-6205            Impact factor:   1.993


  7 in total

Review 1.  Principles and challenges of genomewide DNA methylation analysis.

Authors:  Peter W Laird
Journal:  Nat Rev Genet       Date:  2010-03       Impact factor: 53.242

2.  BiQ Analyzer HT: locus-specific analysis of DNA methylation by high-throughput bisulfite sequencing.

Authors:  Pavlo Lutsik; Lars Feuerbach; Julia Arand; Thomas Lengauer; Jörn Walter; Christoph Bock
Journal:  Nucleic Acids Res       Date:  2011-05-11       Impact factor: 16.971

3.  MethylViewer: computational analysis and editing for bisulfite sequencing and methyltransferase accessibility protocol for individual templates (MAPit) projects.

Authors:  Carolina E Pardo; Ian M Carr; Christopher J Hoffman; Russell P Darst; Alexander F Markham; David T Bonthron; Michael P Kladde
Journal:  Nucleic Acids Res       Date:  2010-10-19       Impact factor: 16.971

4.  Methylation plotter: a web tool for dynamic visualization of DNA methylation data.

Authors:  Izaskun Mallona; Anna Díez-Villanueva; Miguel A Peinado
Journal:  Source Code Biol Med       Date:  2014-06-07

5.  GBSA: a comprehensive software for analysing whole genome bisulfite sequencing data.

Authors:  Touati Benoukraf; Sarawut Wongphayak; Luqman Hakim Abdul Hadi; Mengchu Wu; Richie Soong
Journal:  Nucleic Acids Res       Date:  2012-12-24       Impact factor: 16.971

6.  QUMA: quantification tool for methylation analysis.

Authors:  Yuichi Kumaki; Masaaki Oda; Masaki Okano
Journal:  Nucleic Acids Res       Date:  2008-05-16       Impact factor: 16.971

7.  WBSA: web service for bisulfite sequencing data analysis.

Authors:  Fang Liang; Bixia Tang; Yanqing Wang; Jianfeng Wang; Caixia Yu; Xu Chen; Junwei Zhu; Jiangwei Yan; Wenming Zhao; Rujiao Li
Journal:  PLoS One       Date:  2014-01-30       Impact factor: 3.240

  7 in total

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