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MethGo: a comprehensive tool for analyzing whole-genome bisulfite sequencing data
BACKGROUND: DNA methylation is a major epigenetic modification regulating several biological processes. A standard approach to measure DNA methylation is bisulfite sequencing (BS-Seq). BS-Seq couples bisulfite conversion of DNA with next-generation sequencing to profile genome-wide DNA methylation a...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4682368/ https://www.ncbi.nlm.nih.gov/pubmed/26680022 http://dx.doi.org/10.1186/1471-2164-16-S12-S11 |
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author | Liao, Wen-Wei Yen, Ming-Ren Ju, Evaline Hsu, Fei-Man Lam, Larry Chen, Pao-Yang |
author_facet | Liao, Wen-Wei Yen, Ming-Ren Ju, Evaline Hsu, Fei-Man Lam, Larry Chen, Pao-Yang |
author_sort | Liao, Wen-Wei |
collection | PubMed |
description | BACKGROUND: DNA methylation is a major epigenetic modification regulating several biological processes. A standard approach to measure DNA methylation is bisulfite sequencing (BS-Seq). BS-Seq couples bisulfite conversion of DNA with next-generation sequencing to profile genome-wide DNA methylation at single base resolution. The analysis of BS-Seq data involves the use of customized aligners for mapping bisulfite converted reads and the bioinformatic pipelines for downstream data analysis. RESULTS: Here we developed MethGo, a software tool designed for the analysis of data from whole-genome bisulfite sequencing (WGBS) and reduced representation bisulfite sequencing (RRBS). MethGo provides both genomic and epigenomic analyses including: 1) coverage distribution of each cytosine; 2) global cytosine methylation level; 3) cytosine methylation level distribution; 4) cytosine methylation level of genomic elements; 5) chromosome-wide cytosine methylation level distribution; 6) Gene-centric cytosine methylation level; 7) cytosine methylation levels at transcription factor binding sites (TFBSs); 8) single nucleotide polymorphism (SNP) calling, and 9) copy number variation (CNV) calling. CONCLUSIONS: MethGo is a simple and effective tool for the analysis of BS-Seq data including both WGBS and RRBS. It contains 9 analyses in 5 major modules to profile (epi)genome. It profiles genome-wide DNA methylation in global and in gene level scale. It can also analyze the methylation pattern around the transcription factor binding sites, and assess genetic variations such as SNPs and CNVs. MethGo is coded in Python and is publically available at http://paoyangchen-laboratory.github.io/methgo/. |
format | Online Article Text |
id | pubmed-4682368 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-46823682015-12-21 MethGo: a comprehensive tool for analyzing whole-genome bisulfite sequencing data Liao, Wen-Wei Yen, Ming-Ren Ju, Evaline Hsu, Fei-Man Lam, Larry Chen, Pao-Yang BMC Genomics Research BACKGROUND: DNA methylation is a major epigenetic modification regulating several biological processes. A standard approach to measure DNA methylation is bisulfite sequencing (BS-Seq). BS-Seq couples bisulfite conversion of DNA with next-generation sequencing to profile genome-wide DNA methylation at single base resolution. The analysis of BS-Seq data involves the use of customized aligners for mapping bisulfite converted reads and the bioinformatic pipelines for downstream data analysis. RESULTS: Here we developed MethGo, a software tool designed for the analysis of data from whole-genome bisulfite sequencing (WGBS) and reduced representation bisulfite sequencing (RRBS). MethGo provides both genomic and epigenomic analyses including: 1) coverage distribution of each cytosine; 2) global cytosine methylation level; 3) cytosine methylation level distribution; 4) cytosine methylation level of genomic elements; 5) chromosome-wide cytosine methylation level distribution; 6) Gene-centric cytosine methylation level; 7) cytosine methylation levels at transcription factor binding sites (TFBSs); 8) single nucleotide polymorphism (SNP) calling, and 9) copy number variation (CNV) calling. CONCLUSIONS: MethGo is a simple and effective tool for the analysis of BS-Seq data including both WGBS and RRBS. It contains 9 analyses in 5 major modules to profile (epi)genome. It profiles genome-wide DNA methylation in global and in gene level scale. It can also analyze the methylation pattern around the transcription factor binding sites, and assess genetic variations such as SNPs and CNVs. MethGo is coded in Python and is publically available at http://paoyangchen-laboratory.github.io/methgo/. BioMed Central 2015-12-09 /pmc/articles/PMC4682368/ /pubmed/26680022 http://dx.doi.org/10.1186/1471-2164-16-S12-S11 Text en Copyright © 2015 Liao et al. http://creativecommons.org/licenses/by/4.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Liao, Wen-Wei Yen, Ming-Ren Ju, Evaline Hsu, Fei-Man Lam, Larry Chen, Pao-Yang MethGo: a comprehensive tool for analyzing whole-genome bisulfite sequencing data |
title | MethGo: a comprehensive tool for analyzing whole-genome bisulfite sequencing data |
title_full | MethGo: a comprehensive tool for analyzing whole-genome bisulfite sequencing data |
title_fullStr | MethGo: a comprehensive tool for analyzing whole-genome bisulfite sequencing data |
title_full_unstemmed | MethGo: a comprehensive tool for analyzing whole-genome bisulfite sequencing data |
title_short | MethGo: a comprehensive tool for analyzing whole-genome bisulfite sequencing data |
title_sort | methgo: a comprehensive tool for analyzing whole-genome bisulfite sequencing data |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4682368/ https://www.ncbi.nlm.nih.gov/pubmed/26680022 http://dx.doi.org/10.1186/1471-2164-16-S12-S11 |
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