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Comprehensive Evaluation of Differential Methylation Analysis Methods for Bisulfite Sequencing Data
Background: With advances in next-generation sequencing technologies, the bisulfite conversion of genomic DNA followed by sequencing has become the predominant technique for quantifying genome-wide DNA methylation at single-base resolution. A large number of computational approaches are available in...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8345583/ https://www.ncbi.nlm.nih.gov/pubmed/34360271 http://dx.doi.org/10.3390/ijerph18157975 |
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author | Piao, Yongjun Xu, Wanxue Park, Kwang Ho Ryu, Keun Ho Xiang, Rong |
author_facet | Piao, Yongjun Xu, Wanxue Park, Kwang Ho Ryu, Keun Ho Xiang, Rong |
author_sort | Piao, Yongjun |
collection | PubMed |
description | Background: With advances in next-generation sequencing technologies, the bisulfite conversion of genomic DNA followed by sequencing has become the predominant technique for quantifying genome-wide DNA methylation at single-base resolution. A large number of computational approaches are available in literature for identifying differentially methylated regions in bisulfite sequencing data, and more are being developed continuously. Results: Here, we focused on a comprehensive evaluation of commonly used differential methylation analysis methods and describe the potential strengths and limitations of each method. We found that there are large differences among methods, and no single method consistently ranked first in all benchmarking. Moreover, smoothing seemed not to improve the performance greatly, and a small number of replicates created more difficulties in the computational analysis of BS-seq data than low sequencing depth. Conclusions: Data analysis and interpretation should be performed with great care, especially when the number of replicates or sequencing depth is limited. |
format | Online Article Text |
id | pubmed-8345583 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-83455832021-08-07 Comprehensive Evaluation of Differential Methylation Analysis Methods for Bisulfite Sequencing Data Piao, Yongjun Xu, Wanxue Park, Kwang Ho Ryu, Keun Ho Xiang, Rong Int J Environ Res Public Health Article Background: With advances in next-generation sequencing technologies, the bisulfite conversion of genomic DNA followed by sequencing has become the predominant technique for quantifying genome-wide DNA methylation at single-base resolution. A large number of computational approaches are available in literature for identifying differentially methylated regions in bisulfite sequencing data, and more are being developed continuously. Results: Here, we focused on a comprehensive evaluation of commonly used differential methylation analysis methods and describe the potential strengths and limitations of each method. We found that there are large differences among methods, and no single method consistently ranked first in all benchmarking. Moreover, smoothing seemed not to improve the performance greatly, and a small number of replicates created more difficulties in the computational analysis of BS-seq data than low sequencing depth. Conclusions: Data analysis and interpretation should be performed with great care, especially when the number of replicates or sequencing depth is limited. MDPI 2021-07-28 /pmc/articles/PMC8345583/ /pubmed/34360271 http://dx.doi.org/10.3390/ijerph18157975 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Piao, Yongjun Xu, Wanxue Park, Kwang Ho Ryu, Keun Ho Xiang, Rong Comprehensive Evaluation of Differential Methylation Analysis Methods for Bisulfite Sequencing Data |
title | Comprehensive Evaluation of Differential Methylation Analysis Methods for Bisulfite Sequencing Data |
title_full | Comprehensive Evaluation of Differential Methylation Analysis Methods for Bisulfite Sequencing Data |
title_fullStr | Comprehensive Evaluation of Differential Methylation Analysis Methods for Bisulfite Sequencing Data |
title_full_unstemmed | Comprehensive Evaluation of Differential Methylation Analysis Methods for Bisulfite Sequencing Data |
title_short | Comprehensive Evaluation of Differential Methylation Analysis Methods for Bisulfite Sequencing Data |
title_sort | comprehensive evaluation of differential methylation analysis methods for bisulfite sequencing data |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8345583/ https://www.ncbi.nlm.nih.gov/pubmed/34360271 http://dx.doi.org/10.3390/ijerph18157975 |
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