index.Rmd

---
title:  | 
  | Streamlined workflow for the quality control, normalization, and analysis of Illumina methylation array data
  | 
  
author:  | 
  | Lucy Sinke, Maarten van Iterson, Davy Cats, BIOS Consortium, Tom Kuipers, and Bas Heijmans
  | <font size=2 color=#6b6b6b>Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands</font>
---

```{r, child="_setup.Rmd"}
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<div class="DOI">
  [![DOI](data/images/zenodo.3355292.svg)](http://doi.org/10.5281/zenodo.3355292)
</div>

***

# Introduction #

`DNAmArray` is a comprehensive and modular workflow for the pre-processing, quality control, and analysis of DNA methylation (DNAm) array data, tailored for large-scale epigenome-wide association studies (EWAS). It integrates best practices in the field with in-house developed tools, and has been informed by almost a decade of research using the [Biobank-based Integrative Omics Study (BIOS) consortium](https://www.bbmri.nl/samples-images-data) data. The BIOS dataset combines blood-based DNAm and gene expression from across six Dutch biobanks and around 4,000 individuals, and has been used to extensively advance our understanding of epigenetic regulation and health<sup>1-8</sup>.

The workflow combines a series of convenient [**DNAmArray**](https://github.com/molepi/DNAmArray) functions with [BioConductor](https://www.bioconductor.org) packages, including: 

* [**minfi**](https://bioconductor.org/packages/release/bioc/html/minfi.html) for reading in IDAT files and normalization<sup>9</sup>, 
* [**MethylAid**](https://www.bioconductor.org/packages/release/bioc/html/MethylAid.html) for sample-level quality control<sup>10</sup>, 
* [**bacon**](https://bioconductor.org/packages/release/bioc/html/bacon.html) for controlling bias and inflation in EWAS test statistics<sup>11</sup>, and 
* [**omicsPrint**](https://bioconductor.org/packages/release/bioc/html/omicsPrint.html) for identifying and resolving sample mismatches<sup>12</sup>. 

While thoroughly validated on DNAm data profiled using the Illumina Infinium HumanMethylation450 and EPIC arrays, notes within this documentation also outline any changes needed to apply `DNAmArray` to Infinium MethylationEPIC v2.0 BeadChip data. In addition, any dependencies should be installed automatically, but otherwise please refer to the relevant package's documentation (and let us know by opening a GitHub [issue](https://github.com/molepi/DNAmArray/issues)!)

In conclusion, `DNAmArray` provides a scalable, reproducible, and EWAS-ready framework for DNA methylation data analysis, compatible with evolving technologies and suitable for integration with downstream follow-up analyses.

***

# Example Data #

The [example data](https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE116339)<sup>13</sup> used in this workflow is available from the [NCBI Gene Expression Omnibus](https://www.ncbi.nlm.nih.gov/geo/) (GEO), a public repository of microarray data. It contains genome-wide DNA methylation data from whole blood obtained using the Illumina Infinium MethylationEPIC BeadChip microarray. The participants consist of 679 children exposed to polybrominated biphenyl (PBB), an endocrine-disrupting compound, which was accidentally added to the food supply in Michigan in the 1970s.

***