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HPG-DHunter: an ultrafast, friendly tool for DMR detection and visualization
BACKGROUND: Software tools for analyzing DNA methylation do not provide graphical results which can be easily identified, but huge text files containing the alignment of the samples and their methylation status at a resolution of base pairs. There have been proposed different tools and methods for f...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7336418/ https://www.ncbi.nlm.nih.gov/pubmed/32631226 http://dx.doi.org/10.1186/s12859-020-03634-y |
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author | Fernández, Lisardo Pérez, Mariano Olanda, Ricardo Orduña, Juan M. Marquez-Molins, Joan |
author_facet | Fernández, Lisardo Pérez, Mariano Olanda, Ricardo Orduña, Juan M. Marquez-Molins, Joan |
author_sort | Fernández, Lisardo |
collection | PubMed |
description | BACKGROUND: Software tools for analyzing DNA methylation do not provide graphical results which can be easily identified, but huge text files containing the alignment of the samples and their methylation status at a resolution of base pairs. There have been proposed different tools and methods for finding Differentially Methylated Regions (DMRs) among different samples, but the execution time required by these tools is large, and the visualization of their results is far from being interactive. Additionally, these methods show more accurate results when identifying simulated DM regions that are long and have small within-group variation, but they have low concordance when used with real datasets, probably due to the different approaches they use for DMR identification. Thus, a tool which automatically detects DMRs among different samples and interactively visualizes DMRs at different scales (from a bunch to ten of millions of DNA locations) can be the key for shortening the DNA methylation analysis process in many studies. RESULTS: In this paper, we propose a software tool based on the wavelet transform. This mathematical tool allows the fast automatic DMR detection by simple comparison of different signals at different resolution levels. Also, it allows an interactive visualization of the DMRs found at different resolution levels. The tool is publicly available at https://grev-uv.github.io/, and it is part of a complete suite of tools which allow to carry out the complete process of DNA alignment and methylation analysis, creation of methylation maps of the whole genome, and the detection and visualization of DMRs between different samples. CONCLUSIONS: The validation of the developed software tool shows similar concordance with other well-known and extended tools when used with real and synthetic data. The batch mode of the tool is capable of automatically detecting the existing DMRs for half (twelve) of the human chromosomes between two sets of six samples (whose.csv files after the alignment and mapping procedures have an aggregated size of 108 Gigabytes) in around three hours and a half. When compared to other well-known tools, HPG-DHunter only requires around 15% of the execution time required by other tools for detecting the DMRs. |
format | Online Article Text |
id | pubmed-7336418 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-73364182020-07-07 HPG-DHunter: an ultrafast, friendly tool for DMR detection and visualization Fernández, Lisardo Pérez, Mariano Olanda, Ricardo Orduña, Juan M. Marquez-Molins, Joan BMC Bioinformatics Software BACKGROUND: Software tools for analyzing DNA methylation do not provide graphical results which can be easily identified, but huge text files containing the alignment of the samples and their methylation status at a resolution of base pairs. There have been proposed different tools and methods for finding Differentially Methylated Regions (DMRs) among different samples, but the execution time required by these tools is large, and the visualization of their results is far from being interactive. Additionally, these methods show more accurate results when identifying simulated DM regions that are long and have small within-group variation, but they have low concordance when used with real datasets, probably due to the different approaches they use for DMR identification. Thus, a tool which automatically detects DMRs among different samples and interactively visualizes DMRs at different scales (from a bunch to ten of millions of DNA locations) can be the key for shortening the DNA methylation analysis process in many studies. RESULTS: In this paper, we propose a software tool based on the wavelet transform. This mathematical tool allows the fast automatic DMR detection by simple comparison of different signals at different resolution levels. Also, it allows an interactive visualization of the DMRs found at different resolution levels. The tool is publicly available at https://grev-uv.github.io/, and it is part of a complete suite of tools which allow to carry out the complete process of DNA alignment and methylation analysis, creation of methylation maps of the whole genome, and the detection and visualization of DMRs between different samples. CONCLUSIONS: The validation of the developed software tool shows similar concordance with other well-known and extended tools when used with real and synthetic data. The batch mode of the tool is capable of automatically detecting the existing DMRs for half (twelve) of the human chromosomes between two sets of six samples (whose.csv files after the alignment and mapping procedures have an aggregated size of 108 Gigabytes) in around three hours and a half. When compared to other well-known tools, HPG-DHunter only requires around 15% of the execution time required by other tools for detecting the DMRs. BioMed Central 2020-07-06 /pmc/articles/PMC7336418/ /pubmed/32631226 http://dx.doi.org/10.1186/s12859-020-03634-y Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. 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 in a credit line to the data. |
spellingShingle | Software Fernández, Lisardo Pérez, Mariano Olanda, Ricardo Orduña, Juan M. Marquez-Molins, Joan HPG-DHunter: an ultrafast, friendly tool for DMR detection and visualization |
title | HPG-DHunter: an ultrafast, friendly tool for DMR detection and visualization |
title_full | HPG-DHunter: an ultrafast, friendly tool for DMR detection and visualization |
title_fullStr | HPG-DHunter: an ultrafast, friendly tool for DMR detection and visualization |
title_full_unstemmed | HPG-DHunter: an ultrafast, friendly tool for DMR detection and visualization |
title_short | HPG-DHunter: an ultrafast, friendly tool for DMR detection and visualization |
title_sort | hpg-dhunter: an ultrafast, friendly tool for dmr detection and visualization |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7336418/ https://www.ncbi.nlm.nih.gov/pubmed/32631226 http://dx.doi.org/10.1186/s12859-020-03634-y |
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