ChAMP: updated methylation analysis pipeline for Illumina BeadChips

SUMMARY: The Illumina Infinium HumanMethylationEPIC BeadChip is the new platform for high-throughput DNA methylation analysis, effectively doubling the coverage compared to the older 450 K array. Here we present a significantly updated and improved version of the Bioconductor package ChAMP, which ca...

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Autores principales: Tian, Yuan, Morris, Tiffany J, Webster, Amy P, Yang, Zhen, Beck, Stephan, Feber, Andrew, Teschendorff, Andrew E
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2017
Materias:
Applications Notes
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5860089/
https://www.ncbi.nlm.nih.gov/pubmed/28961746
http://dx.doi.org/10.1093/bioinformatics/btx513
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author Tian, Yuan
Morris, Tiffany J
Webster, Amy P
Yang, Zhen
Beck, Stephan
Feber, Andrew
Teschendorff, Andrew E
author_facet Tian, Yuan
Morris, Tiffany J
Webster, Amy P
Yang, Zhen
Beck, Stephan
Feber, Andrew
Teschendorff, Andrew E
author_sort Tian, Yuan
collection PubMed
description SUMMARY: The Illumina Infinium HumanMethylationEPIC BeadChip is the new platform for high-throughput DNA methylation analysis, effectively doubling the coverage compared to the older 450 K array. Here we present a significantly updated and improved version of the Bioconductor package ChAMP, which can be used to analyze EPIC and 450k data. Many enhanced functionalities have been added, including correction for cell-type heterogeneity, network analysis and a series of interactive graphical user interfaces. AVAILABILITY AND IMPLEMENTATION: ChAMP is a BioC package available from https://bioconductor.org/packages/release/bioc/html/ChAMP.html. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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spelling pubmed-58600892018-03-23 ChAMP: updated methylation analysis pipeline for Illumina BeadChips Tian, Yuan Morris, Tiffany J Webster, Amy P Yang, Zhen Beck, Stephan Feber, Andrew Teschendorff, Andrew E Bioinformatics Applications Notes SUMMARY: The Illumina Infinium HumanMethylationEPIC BeadChip is the new platform for high-throughput DNA methylation analysis, effectively doubling the coverage compared to the older 450 K array. Here we present a significantly updated and improved version of the Bioconductor package ChAMP, which can be used to analyze EPIC and 450k data. Many enhanced functionalities have been added, including correction for cell-type heterogeneity, network analysis and a series of interactive graphical user interfaces. AVAILABILITY AND IMPLEMENTATION: ChAMP is a BioC package available from https://bioconductor.org/packages/release/bioc/html/ChAMP.html. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2017-12-15 2017-08-14 /pmc/articles/PMC5860089/ /pubmed/28961746 http://dx.doi.org/10.1093/bioinformatics/btx513 Text en © The Author 2017. 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
Tian, Yuan
Morris, Tiffany J
Webster, Amy P
Yang, Zhen
Beck, Stephan
Feber, Andrew
Teschendorff, Andrew E
ChAMP: updated methylation analysis pipeline for Illumina BeadChips
title ChAMP: updated methylation analysis pipeline for Illumina BeadChips
title_full ChAMP: updated methylation analysis pipeline for Illumina BeadChips
title_fullStr ChAMP: updated methylation analysis pipeline for Illumina BeadChips
title_full_unstemmed ChAMP: updated methylation analysis pipeline for Illumina BeadChips
title_short ChAMP: updated methylation analysis pipeline for Illumina BeadChips
title_sort champ: updated methylation analysis pipeline for illumina beadchips
topic Applications Notes
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5860089/
https://www.ncbi.nlm.nih.gov/pubmed/28961746
http://dx.doi.org/10.1093/bioinformatics/btx513
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