SWAN: Subset-quantile Within Array Normalization for Illumina Infinium HumanMethylation450 BeadChips

By Jovana Maksimovic, L. Gordon, Alicia Oshlack. Genome Biology, 2012

796 citations recorded by the source corpus.

DNA methylation is the most widely studied epigenetic mark and is known to be essential to normal development and frequently disrupted in disease. The Illumina HumanMethylation450 BeadChip assays the methylation status of CpGs at 485,577 sites across the genome. Here we present Subset-quantile Within Array Normalization (SWAN), a new method that substantially improves the results from this platform by reducing technical variation within and between arrays. SWAN is available in the minfi Bioconductor package.

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Citations in the corpus

Low-level processing of Illumina Infinium DNA Methylation BeadArrays (2013, methodology): “However, we did evaluate our noob and dye-bias equalization procedure in the presence of SWAN (20), a new software package that performs subset quantile normalization, and found that our method always improved the median pairwise Spearman correlation for all mixture samples and the PBL replicates.”
A Six Months Exercise Intervention Influences the Genome-wide DNA Methylation Pattern in Human Adipose Tissue (2013, unknown): “Infinium II assays have less than three underlying CpGs in the probe and only 21% are designated as CpG islands [26].”
ChAMP: 450k Chip Analysis Methylation Pipeline (2014, unknown): “The user can also select SWAN (Maksimovic et al., 2012), PBC (Dedeurwaerder et al., 2011) or no normalization.”
Genetic Drivers of Epigenetic and Transcriptional Variation in Human Immune Cells (2016, unknown): “0) Monlong et al., 2014 https://github.com/jmonlong/sQTLseekeR AStalavista 3.2 Foissac and Sammeth, 2007; Monlong et al., 2014 http://sammeth.net/confluence/display/ASTA/2+-+Download Minfi Aryee et al., 2014 https://bioconductor.org/packages/release/bioc/html/minfi.html NOOB Triche et al., 2013 http”
De novo identification of differentially methylated regions in the human genome (2015, methodology): “This complicates the preprocessing of the array data, but various normalisation methods are available [23,24] to remedy this.”
Functional normalization of 450k methylation array data improves replication in large cancer studies (2014, unknown): “, 2014], SWAN [Maksimovic et al., 2012], BMIQ [Teschendorff et al.”
Preprocessing, normalization and integration of the Illumina HumanMethylationEPIC array with minfi (2016, methodology): “The different methods are: preprocessing 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…”
A beta-mixture quantile normalization method for correcting probe design bias in Illumina Infinium 450 k DNA methylation data (2012, unknown): “Contact: a.teschendorff@ucl.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online Received on June 27, 2012; revised on October 9, 2012; accepted on November 16, 2012”