ArticleBMC bioinformatics2013
MethyQA: a pipeline for bisulfite-treated methylation sequencing quality assessment.
Article in BMC bioinformatics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Epigenetic tumor heterogeneity in the era of single-cell profiling with nanopore sequencing.Clinical epigenetics · 2022Review
- Generating Sequencing-Based DNA Methylation Maps from Low DNA Input Samples.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Urinary Nucleic Acid in Tumor: Bioinformatics Approaches.Methods in molecular biology (Clifton, N.J.) · 2021Article
- DNA methylation analysis in plants: review of computational tools and future perspectives.Briefings in bioinformatics · 2020Review
- A survey of the approaches for identifying differential methylation using bisulfite sequencing data.Briefings in bioinformatics · 2018Review
- Review
- CGmapTools improves the precision of heterozygous SNV calls and supports allele-specific methylation detection and visualization in bisulfite-sequencing data.Bioinformatics (Oxford, England) · 2018Article
- HPP1 gene promoter methylation in pancreatic cancer: correlation with carcinogenesis and clinical implication.International journal of clinical and experimental pathology · 2018Article
- Base resolution methylome profiling: considerations in platform selection, data preprocessing and analysis.Epigenomics · 2015Review
- A trimming-and-retrieving alignment scheme for reduced representation bisulfite sequencing.Bioinformatics (Oxford, England) · 2015Article
- HMPL: A Pipeline for Identifying Hemimethylation Patterns by Comparing Two Samples.Cancer informatics · 2015Article
- Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundDNA 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.
resultsTo 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.
conclusionsMethyQA 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.
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Registered trials
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