Complete pipeline for Infinium(®) Human Methylation 450K BeadChip data processing using subset quantile normalization for accurate DNA methylation estimation.

By N. Touleimat, Jorg Tost. Epigenomics, 2012

493 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/83683004ff1ea7093a8db71e48d317bfefecac36

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Citations in the corpus

A data-driven approach to preprocessing Illumina 450K methylation array data (2013, background): “A number of research groups have developed preprocessing methods to accommodate the differences in signal between the two probe types [5-7].”
Minfi: a flexible and comprehensive Bioconductor package for the analysis of Infinium DNA methylation microarrays (2014, unknown): “Several groups have found that this procedure can be improved upon by borrowing ideas from normalization techniques developed for expression arrays (Maksimovic et al., 2012; Pidsley et al., 2013; Teschendorff et al., 2013; Touleimat and Tost, 2012; Triche et al., 2013).”
Preprocessing, normalization and integration of the Illumina HumanMethylationEPIC array with minfi (2016, methodology): “…as Illumina, SWAN normalization (Maksimovic, Gordon, and Oshlack, 2012), stratified quantile normalization as discussed in Touleimat and Tost (2012) and Aryee et al. (2014), single-sample noob background correction followed by dye bias correction (Triche et al., 2013), and functional…”
Epigenetic Signatures of Cigarette Smoking (2016, background): “recent smoking; DNA methylation signals have the potential to serve as robust biomarkers of smoking history.(9,42) Indeed, several studies have identified several of such markers.”
Analysing and interpreting DNA methylation data (2012, methodology): “It uses two different probe types with distinct experimen‑ tal characteristics, thus requiring careful normalization to minimize technical bias 44–46 .”
Tobacco Smoking Leads to Extensive Genome-Wide Changes in DNA Methylation (2013, methodology): “For data pre - processing of the Infinium Human Methylation 450K BeadChip we used the pipeline described in Touleimat & Tost 2012 with default parameter settings to avoid bias in the analysis since the assay combines two different chemistries [ 44 ] .”
A beta-mixture quantile normalization method for correcting probe design bias in Illumina Infinium 450 k DNA methylation data (2012, methodology): “Thus, BMIQ is assumption-free, as it does not require a separate normalization to be performed on selected subsets of probes that are matched for biological characteristics (e.g. CpG density), as done in SQN and SWAN.”
ChAMP: 450k Chip Analysis Methylation Pipeline (2014, methodology): “In chronological order of development, they are Peak Based Correction (PBC) (Dedeurwaerder et al., 2011), SQN (Touleimat and Tost, 2012), Subset-quantile within array normalisation (SWAN) (Maksimovic et al., 2012) and Beta-mixture quantile normalization (BMIQ) (Teschendorff et al., 2013).”