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 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. Contact: a.teschendorff@ucl.ac.uk or s.beck@ucl.ac.uk or a.feber@ucl.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online.

[1]  K. Hansen,et al.  Functional normalization of 450k methylation array data improves replication in large cancer studies , 2014, Genome Biology.

[2]  Jeffrey T Leek,et al.  Significance analysis and statistical dissection of variably methylated regions. , 2012, Biostatistics.

[3]  Matthew D. Young,et al.  Gene ontology analysis for RNA-seq: accounting for selection bias , 2010, Genome Biology.

[4]  A. Teschendorff,et al.  Using high-density DNA methylation arrays to profile copy number alterations , 2014, Genome Biology.

[5]  Peter W. Laird,et al.  Comprehensive characterization, annotation and innovative use of Infinium DNA methylation BeadChip probes , 2016, Nucleic acids research.

[6]  Stephan Beck,et al.  Probe Lasso: A novel method to rope in differentially methylated regions with 450K DNA methylation data , 2015, Methods.

[7]  Francesco Marabita,et al.  A beta-mixture quantile normalization method for correcting probe design bias in Illumina Infinium 450 k DNA methylation data , 2012, Bioinform..

[8]  Andrew E. Teschendorff,et al.  An Integrative Multi-scale Analysis of the Dynamic DNA Methylation Landscape in Aging , 2015, PLoS genetics.

[9]  Andrew E. Teschendorff,et al.  A systems-level integrative framework for genome-wide DNA methylation and gene expression data identifies differential gene expression modules under epigenetic control , 2014, Bioinform..

[10]  Peter L Molloy,et al.  De novo identification of differentially methylated regions in the human genome , 2015, Epigenetics & Chromatin.

[11]  M. Esteller,et al.  Validation of a DNA methylation microarray for 850,000 CpG sites of the human genome enriched in enhancer sequences , 2015, Epigenomics.

[12]  Rafael A. Irizarry,et al.  Minfi: a flexible and comprehensive Bioconductor package for the analysis of Infinium DNA methylation microarrays , 2014, Bioinform..

[13]  Devin C. Koestler,et al.  DNA methylation arrays as surrogate measures of cell mixture distribution , 2012, BMC Bioinformatics.

[14]  Andrew E. Teschendorff,et al.  ChAMP: 450k Chip Analysis Methylation Pipeline , 2014, Bioinform..