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IMA: an R package for high-throughput analysis of Illumina's 450K Infinium methylation data.

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TLDR
The Illumina Methylation Analyzer (IMA) is a computational package designed to automate the pipeline for exploratory analysis and summarization of site-level and region-level methylation changes in epigenetic studies utilizing the 450K DNA methylation microarray.
Abstract
Summary: The Illumina Infinium HumanMethylation450 BeadChip is a newly designed high-density microarray for quantifying the methylation level of over 450 000 CpG sites within human genome. Illumina Methylation Analyzer (IMA) is a computational package designed to automate the pipeline for exploratory analysis and summarization of site-level and region-level methylation changes in epigenetic studies utilizing the 450K DNA methylation microarray. The pipeline loads the data from Illumina platform and provides usercustomized functions commonly required to perform exploratory methylation analysis for individual sites as well as annotated regions. Availability: IMA is implemented in the R language and is freely available from http://www.rforge.net/IMA. Contact: song.liu@roswellpark.org

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Journal ArticleDOI

Minfi: A flexible and comprehensive Bioconductor package for the analysis of Infinium DNA Methylation microarrays

TL;DR: A suite of computational tools that incorporate state-of-the-art statistical techniques for the analysis of DNAm data are described that include methods for preprocessing, quality assessment and detection of differentially methylated regions from the kilobase to the megabase scale.
Journal ArticleDOI

A beta-mixture quantile normalization method for correcting probe design bias in Illumina Infinium 450 k DNA methylation data

TL;DR: A novel model-based intra-array normalization strategy for 450 k data, called BMIQ (Beta MIxture Quantile dilation), to adjust the beta-values of type2 design probes into a statistical distribution characteristic of type1 probes is proposed.
Journal ArticleDOI

A data-driven approach to preprocessing Illumina 450K methylation array data

TL;DR: It is demonstrated that quantile normalization methods produce marked improvement, even in highly consistent data, by all three metrics, and that careful selection of preprocessing steps can minimize variance and thus improve statistical power, especially for the detection of the small absolute DNA methylation changes likely associated with complex disease phenotypes.
Journal ArticleDOI

Critical evaluation of the Illumina MethylationEPIC BeadChip microarray for whole-genome DNA methylation profiling

TL;DR: The EPIC array is a significant improvement over the HM450 array, with increased genome coverage of regulatory regions and high reproducibility and reliability, providing a valuable tool for high-throughput human methylome analyses from diverse clinical samples.
Journal ArticleDOI

ChAMP: 450k Chip Analysis Methylation Pipeline

TL;DR: An integrated analysis pipeline offering a choice of the most popular normalization methods while also introducing new methods for calling differentially methylated regions and detecting copy number aberrations is presented.
References
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Journal ArticleDOI

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TL;DR: Recent advances in understanding how epigenetic alterations participate in the earliest stages of neoplasia, including stem/precursor cell contributions, are reviewed and the growing implications of these advances for strategies to control cancer are discussed.
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Epigenetic modifications and human disease

TL;DR: A comprehensive understanding of epigenetic mechanisms, their interactions and alterations in health and disease, has become a priority in biomedical research.
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The human colon cancer methylome shows similar hypo- and hypermethylation at conserved tissue-specific CpG island shores.

TL;DR: Methylation changes in cancer are at sites that vary normally in tissue differentiation, consistent with the epigenetic progenitor model of cancer, which proposes that epigenetic alterations affecting tissue-specific differentiation are the predominant mechanism by which epigenetic changes cause cancer.
Journal ArticleDOI

lumi: a pipeline for processing Illumina microarray

TL;DR: The lumi package as discussed by the authors is a Bioconductor package designed to process the Illumina microarray data, which includes data input, quality control, variance stabilization, normalization and gene annotation portions.
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