qn.bmiq: Preprocess DNA methylation data

In dswatson/biowrapr: Convenient wrappers for functions in bioinformatics analysis pipelines

Description

This function runs a QN.BMIQ preprocessing pipeline on raw .idat files.

Usage

qn.bmiq(targets, idats)

Arguments

targets	A data frame of sample information or a vector of barcodes.
idats	Path to the directory containing the relevant .idat files.

Details

qn.bmiq provides wrappers for functions from several packages that collectively form a complete preprocessing pipeline on raw DNA methylation data. It begins by filtering autosomal probes by detection p-value, beadcount, alignment redundancy, and known SNPs using the default settings of ChAMP::champ.load. It then runs color bias adjustment, background correction, and quantile normalization, using functions from the lumi package. Finally, data are normalized using beta-mixture quantile dilation as implemented by wateRmelon::BMIQ. Missing values are imputed using k-nearest neighbors with the default setting of k = 10. Zeros are replaced with a very small value to facilitate logit transformation.

Normalization procedures for methylation data are the subject of much active research. Over a dozen methods are implemented in various Bioconductor packages. The QN.BMIQ pipeline has been found to be optimal in terms of both technical reproducibility (Marabita et al., 2013) and biological comparison with gold standard whole genome bisulfite sequencing (Wang et al., 2015).

Value

A matrix of filtered and normalized beta values.

References

Morris, T.J., Butcher, L.M., Teschendorff, A.E., Chakravarthy, A.R., Wojdacz, T.K. & Beck, S. (2014). "ChAMP: 450k Chip Analysis Methylation Pipeline." Bioinformatics, 30(3): 428-430. http://doi.org/10.1093/bioinformatics/btt684

Bolstad, B.M., Irizarry, R.A. Astrand, M. & Speed, T.P. (2003). "A comparison of normalization methods for high density oligonucleotide array data based on variance and bias." Bioinformatics, 19(2): 185-193. https://www.ncbi.nlm.nih.gov/pubmed/12538238

Teschendorff, A.E., Marabita, F., Lechner, M. Bartlett, T. Tegner, J. Gomez-Cabrero, D. & Beck, S. (2012). "A beta-mixture quantile normalization method for correcting probe design bias in Illumina Infinium 450k DNA methylation data." Bioinformatics, 29(2): 189-196. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3546795/

Marabita, F. et al. (2013). "An evaluation of analysis pipelines for DNA methylation profiling using the Illumina HumanMethylation450 BeadChip platform." Epigenetics, 8(3): 333-346. https://www.ncbi.nlm.nih.gov/pubmed/23422812

Wang, T. et al. (2015). "A systematic study of normalization methods for Infinium 450k methylation data using whole-genome bisulfite sequencing data." Epigenetics, 10(7): 662-669. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4623491/

Examples

data()

dswatson/biowrapr documentation built on May 15, 2019, 4:52 p.m.