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Zeitschriftenartikel

MethVisual - visualization and exploratory statistical analysis of DNA methylation profiles from bisulfite sequencing

MPG-Autoren

Zackay,  Arie
Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons50571

Steinhoff,  Christine
Dept. of Computational Molecular Biology (Head: Martin Vingron), Max Planck Institute for Molecular Genetics, Max Planck Society;

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Zackay.pdf
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Zitation

Zackay, A., & Steinhoff, C. (2010). MethVisual - visualization and exploratory statistical analysis of DNA methylation profiles from bisulfite sequencing. BMC Research Notes, 3, e337-e337. doi:10.1186/1756-0500-3-337.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0010-7C5E-D
Zusammenfassung
ABSTRACT: BACKGROUND: Exploration of DNA methylation and its impact on various regulatory mechanisms has become a very active field of research. Simultaneously there is an arising need for tools to process and analyse the data together with statistical investigation and visualisation. FINDINGS: MethVisual is a new application that enables exploratory analysis and intuitive visualization of DNA methylation data as is typically generated by bisulfite sequencing. The package allows the import of DNA methylation sequences, aligns them and performs quality control comparison. It comprises basic analysis steps as lollipop visualization, co-occurrence display of methylation of neighbouring and distant CpG sites, summary statistics on methylation status, clustering and correspondence analysis. The package has been developed for methylation data but can be also used for other data types for which binary coding can be inferred. The application of the package, as well as a comparison to existing DNA methylation analysis tools and its workflow based on two datasets is presented in this paper. CONCLUSIONS: The R package MethVisual offers various analysis procedures for data that can be binarized, in particular for bisulfite sequenced methylation data. R/Bioconductor has become one of the most important environments for statistical analysis of various types of biological and medical data. Therefore, any data analysis within R that allows the integration of various data types as provided from different technological platforms is convenient. It is the first and so far the only specific package for DNA methylation analysis, in particular for bisulfite sequenced data available in R/Bioconductor enviroment. The package is available for free at http://methvisual.molgen.mpg.de/ and from the Bioconductor Consortium http://www.bioconductor.org.