Introduction

BACKGROUND: DNA methylation is an epigenetic event that adds a methyl-group to the 5' cytosine. This epigenetic modification can significantly affect gene expression in both normal and diseased cells. Hence, it is important to study methylation signals at the single cytosine site level, which is now possible utilizing bisulfite conversion technique (i.e., converting unmethylated Cs to Us and then to Ts after PCR amplification) and next generation sequencing (NGS) technologies. Despite the advances of NGS technologies, certain quality issues remain. Some of the more prevalent quality issues involve low per-base sequencing quality at the 3' end, PCR amplification bias, and bisulfite conversion rates. Therefore, it is important to conduct quality assessment before downstream analysis. To the best of our knowledge, no existing software packages can generally assess the quality of methylation sequencing data generated based on different bisulfite-treated protocols. RESULTS: To conduct the quality assessment of bisulfite methylation sequencing data, we have developed a pipeline named MethyQA. MethyQA combines currently available open-source software packages with our own custom programs written in Perl and R. The pipeline can provide quality assessment results for tens of millions of reads in under an hour. The novelty of our pipeline lies in its examination of bisulfite conversion rates and of the DNA sequence structure of regions that have different conversion rates or coverage. CONCLUSIONS: MethyQA is a new software package that provides users with a unique insight into the methylation sequencing data they are researching. It allows the users to determine the quality of their data and better prepares them to address the research questions that lie ahead. Due to the speed and efficiency at which MethyQA operates, it will become an important tool for studies dealing with bisulfite methylation sequencing data.

Publications

  1. MethyQA: a pipeline for bisulfite-treated methylation sequencing quality assessment.
    Cite this
    Sun S, Noviski A, Yu X, 2013-01-01 - BMC bioinformatics

Credits

  1. Shuying Sun
    Developer

    Department of Epidemiology and Biostatistics, Case Western Reserve University

  2. Aaron Noviski
    Developer

  3. Xiaoqing Yu
    Investigator

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Summary
AccessionBT007038
Tool TypeApplication
Category
PlatformsLinux/Unix
TechnologiesPerl, R
User InterfaceTerminal Command Line
Download Count0
Submitted ByXiaoqing Yu