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minfi
A suite of computational tools that incorporate state-of-the-art statistical techniques for the analysis of DNAm data. minfi provides methods for preprocessing, quality assessment and detection of differentially methylated regions from the kilobase to the megabase scale. Several preprocessing algorithms are available and the infrastructure provides a convenient way for developers to easily implement their techniques as Bioconductor tools. By making SNP annotation available, users can choose to be cautious about probes that may behave unexpectedly due to the inclusion of a SNP in the probe sequence. minfi is unique in that it provides both bump hunting and block finding capabilities, and the assessment of statistical significance for the identified regions. Finally, because the package is implemented in Bioconductor, it gives users access to the countless analysis and visualization tools available in R.
CpGassoc
An R package that can efficiently perform the statistical analysis needed for increasingly large methylation datasets. CpGassoc can perform standard analyses of large datasets very quickly with no need to impute the data. It can handle mixed effects models with chip or batch entering the model as a random intercept. CpGassoc also includes tools to apply quality control filters, perform permutation tests, and create QQ plots, manhattan plots, and scatterplots for individual CpG sites.
MethylAid
Provides complete insight in the quality of each sample in a large-scale EWAS and gives the user full control on the selection of bad-quality samples that should be excluded from downstream analyses. MethylAid was specifically designed for quality control of large set of DNA methylation data. The web application produces multiple interactive diagnostic plots on the basis of the quality control probes present on the 450k array that facilitate the detection of bad-quality samples irrespective of sample size.
shinyMethyl
A Bioconductor package for interactive quality control of DNA methylation data from Illumina 450k arrays. The package summarizes 450k experiments into small exportable R objects from which an interactive interface is launched. Reactive plots allow fast and intuitive quality control assessment of the samples. In addition, exploration of the phenotypic associations is possible through coloring and principal component analysis. Altogether, the package makes it easy to perform quality assessment of large-scale methylation datasets, such as epigenome-wide association studies or the datasets available through The Cancer Genome Atlas portal.
ADMIRE / Analysis of DNA methylation in genomic regions
Allows to analyze and visualize differential methylation in genomic regions. ADMIRE is a semi-automatic pipeline that features five different normalization methods and performs two one-sided two-sample rank tests (Mann–Whitney U tests). The software features arbitrary experimental settings, quality control, automatic filtering, normalization, multiple testing, differential analyses on arbitrary genomic regions. It additionally implements a gene set enrichment procedure.
GenomeStudio
Allows visualization and analysis of data generated on Illumina array platforms. GenomeStudio is a data analysis tool that provides three modules: (1) Genotyping Module for the analysis of single nucleotide polymorphism (SNPs) and copy number variations (CNVs) data and detection of sample outliers, (2) Gene Expression Module for the detection of cytosine methylation at single-base resolution and identification of methylation signatures across the entire genome, and (3) Polyploid Genotyping Module for the analysis of polyploid organism genotyping data.
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