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WGBSSuite: simulating whole-genome bisulphite sequencing data and benchmarking differential DNA methylation analysis tools
Motivation: As the number of studies looking at differences between DNA methylation increases, there is a growing demand to develop and benchmark statistical methods to analyse these data. To date no objective approach for the comparison of these methods has been developed and as such it remains dif...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4495289/ https://www.ncbi.nlm.nih.gov/pubmed/25777524 http://dx.doi.org/10.1093/bioinformatics/btv114 |
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author | Rackham, Owen J. L. Dellaportas, Petros Petretto, Enrico Bottolo, Leonardo |
author_facet | Rackham, Owen J. L. Dellaportas, Petros Petretto, Enrico Bottolo, Leonardo |
author_sort | Rackham, Owen J. L. |
collection | PubMed |
description | Motivation: As the number of studies looking at differences between DNA methylation increases, there is a growing demand to develop and benchmark statistical methods to analyse these data. To date no objective approach for the comparison of these methods has been developed and as such it remains difficult to assess which analysis tool is most appropriate for a given experiment. As a result, there is an unmet need for a DNA methylation data simulator that can accurately reproduce a wide range of experimental setups, and can be routinely used to compare the performance of different statistical models. Results: We have developed WGBSSuite, a flexible stochastic simulation tool that generates single-base resolution DNA methylation data genome-wide. Several simulator parameters can be derived directly from real datasets provided by the user in order to mimic real case scenarios. Thus, it is possible to choose the most appropriate statistical analysis tool for a given simulated design. To show the usefulness of our simulator, we also report a benchmark of commonly used methods for differential methylation analysis. Availability and implementation: WGBS code and documentation are available under GNU licence at http://www.wgbssuite.org.uk/ Contact: owen.rackham@imperial.ac.uk or l.bottolo@imperial.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-4495289 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-44952892015-07-09 WGBSSuite: simulating whole-genome bisulphite sequencing data and benchmarking differential DNA methylation analysis tools Rackham, Owen J. L. Dellaportas, Petros Petretto, Enrico Bottolo, Leonardo Bioinformatics Applications Notes Motivation: As the number of studies looking at differences between DNA methylation increases, there is a growing demand to develop and benchmark statistical methods to analyse these data. To date no objective approach for the comparison of these methods has been developed and as such it remains difficult to assess which analysis tool is most appropriate for a given experiment. As a result, there is an unmet need for a DNA methylation data simulator that can accurately reproduce a wide range of experimental setups, and can be routinely used to compare the performance of different statistical models. Results: We have developed WGBSSuite, a flexible stochastic simulation tool that generates single-base resolution DNA methylation data genome-wide. Several simulator parameters can be derived directly from real datasets provided by the user in order to mimic real case scenarios. Thus, it is possible to choose the most appropriate statistical analysis tool for a given simulated design. To show the usefulness of our simulator, we also report a benchmark of commonly used methods for differential methylation analysis. Availability and implementation: WGBS code and documentation are available under GNU licence at http://www.wgbssuite.org.uk/ Contact: owen.rackham@imperial.ac.uk or l.bottolo@imperial.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online. Oxford University Press 2015-07-15 2015-03-15 /pmc/articles/PMC4495289/ /pubmed/25777524 http://dx.doi.org/10.1093/bioinformatics/btv114 Text en © The Author 2015. Published by Oxford University Press. 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 reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Applications Notes Rackham, Owen J. L. Dellaportas, Petros Petretto, Enrico Bottolo, Leonardo WGBSSuite: simulating whole-genome bisulphite sequencing data and benchmarking differential DNA methylation analysis tools |
title | WGBSSuite: simulating whole-genome bisulphite sequencing data and benchmarking differential DNA methylation analysis tools |
title_full | WGBSSuite: simulating whole-genome bisulphite sequencing data and benchmarking differential DNA methylation analysis tools |
title_fullStr | WGBSSuite: simulating whole-genome bisulphite sequencing data and benchmarking differential DNA methylation analysis tools |
title_full_unstemmed | WGBSSuite: simulating whole-genome bisulphite sequencing data and benchmarking differential DNA methylation analysis tools |
title_short | WGBSSuite: simulating whole-genome bisulphite sequencing data and benchmarking differential DNA methylation analysis tools |
title_sort | wgbssuite: simulating whole-genome bisulphite sequencing data and benchmarking differential dna methylation analysis tools |
topic | Applications Notes |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4495289/ https://www.ncbi.nlm.nih.gov/pubmed/25777524 http://dx.doi.org/10.1093/bioinformatics/btv114 |
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