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Research Paper

An evaluation of analysis pipelines for DNA methylation profiling using the Illumina HumanMethylation450 BeadChip platform

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Pages 333-346 | Received 26 Dec 2012, Accepted 13 Feb 2013, Published online: 19 Feb 2013

References

  • Rakyan VK, Down TA, Balding DJ, Beck S. Epigenome-wide association studies for common human diseases. Nat Rev Genet 2011; 12:529 - 41; http://dx.doi.org/10.1038/nrg3000; PMID: 21747404
  • Feinberg AP. Epigenomics reveals a functional genome anatomy and a new approach to common disease. Nat Biotechnol 2010; 28:1049 - 52; http://dx.doi.org/10.1038/nbt1010-1049; PMID: 20944596
  • Petronis A. Epigenetics as a unifying principle in the aetiology of complex traits and diseases. Nature 2010; 465:721 - 7; http://dx.doi.org/10.1038/nature09230; PMID: 20535201
  • Lan X, Adams C, Landers M, Dudas M, Krissinger D, Marnellos G, et al. High resolution detection and analysis of CpG dinucleotides methylation using MBD-Seq technology. PLoS One 2011; 6:e22226; http://dx.doi.org/10.1371/journal.pone.0022226; PMID: 21779396
  • Serre D, Lee BH, Ting AH. MBD-isolated Genome Sequencing provides a high-throughput and comprehensive survey of DNA methylation in the human genome. Nucleic Acids Res 2010; 38:391 - 9; http://dx.doi.org/10.1093/nar/gkp992; PMID: 19906696
  • Borgel J, Guibert S, Weber M. Methylated DNA immunoprecipitation (MeDIP) from low amounts of cells. Methods Mol Biol 2012; 925:149 - 58; http://dx.doi.org/10.1007/978-1-62703-011-3_9; PMID: 22907495
  • Mohn F, Weber M, Schübeler D, Roloff TC. Methylated DNA immunoprecipitation (MeDIP). Methods Mol Biol 2009; 507:55 - 64; http://dx.doi.org/10.1007/978-1-59745-522-0_5; PMID: 18987806
  • Lister R, Pelizzola M, Dowen RH, Hawkins RD, Hon G, Tonti-Filippini J, et al. Human DNA methylomes at base resolution show widespread epigenomic differences. Nature 2009; 462:315 - 22; http://dx.doi.org/10.1038/nature08514; PMID: 19829295
  • Meissner A, Mikkelsen TS, Gu H, Wernig M, Hanna J, Sivachenko A, et al. Genome-scale DNA methylation maps of pluripotent and differentiated cells. Nature 2008; 454:766 - 70; PMID: 18600261
  • Irizarry RA, Ladd-Acosta C, Carvalho B, Wu H, Brandenburg SA, Jeddeloh JA, et al. Comprehensive high-throughput arrays for relative methylation (CHARM). Genome Res 2008; 18:780 - 90; http://dx.doi.org/10.1101/gr.7301508; PMID: 18316654
  • Harris RA, Wang T, Coarfa C, Nagarajan RP, Hong C, Downey SL, et al. Comparison of sequencing-based methods to profile DNA methylation and identification of monoallelic epigenetic modifications. Nat Biotechnol 2010; 28:1097 - 105; http://dx.doi.org/10.1038/nbt.1682; PMID: 20852635
  • Bibikova M, Barnes B, Tsan C, Ho V, Klotzle B, Le JM, et al. High density DNA methylation array with single CpG site resolution. Genomics 2011; 98:288 - 95; http://dx.doi.org/10.1016/j.ygeno.2011.07.007; PMID: 21839163
  • Bibikova M, Le J, Barnes B, Saedinia-Melnyk S, Zhou L, Shen R, et al. Genome-wide DNA methylation profiling using Infinium® assay. Epigenomics 2009; 1:177 - 200; http://dx.doi.org/10.2217/epi.09.14; PMID: 22122642
  • Sandoval J, Heyn HA, Moran S, Serra-Musach J, Pujana MA, Bibikova M, et al. Validation of a DNA methylation microarray for 450,000 CpG sites in the human genome. Epigenetics 2011; 6:692 - 702; http://dx.doi.org/10.4161/epi.6.6.16196; PMID: 21593595
  • Dedeurwaerder S, Defrance M, Calonne E, Denis H, Sotiriou C, Fuks F. Evaluation of the Infinium Methylation 450K technology. Epigenomics 2011; 3:771 - 84; http://dx.doi.org/10.2217/epi.11.105; PMID: 22126295
  • Maksimovic J, Gordon L, Oshlack A. SWAN: Subset-quantile within array normalization for illumina infinium HumanMethylation450 BeadChips. Genome Biol 2012; 13:R44; http://dx.doi.org/10.1186/gb-2012-13-6-r44; PMID: 22703947
  • Touleimat N, Tost J. Complete pipeline for Infinium(®) Human Methylation 450K BeadChip data processing using subset quantile normalization for accurate DNA methylation estimation. Epigenomics 2012; 4:325 - 41; http://dx.doi.org/10.2217/epi.12.21; PMID: 22690668
  • Teschendorff AE, Marabita F, Lechner M, Bartlett T, TegnEr J, Gomez-Cabrero D, et al. A Beta-Mixture Quantile Normalisation method for correcting probe design bias in Illumina Infinium 450k DNA methylation data. Bioinformatics (Oxford, England) 2012;
  • Jaffe AE, Murakami P, Lee H, Leek JT, Fallin MD, Feinberg AP, et al. Bump hunting to identify differentially methylated regions in epigenetic epidemiology studies. Int J Epidemiol 2012; 41:200 - 9; http://dx.doi.org/10.1093/ije/dyr238; PMID: 22422453
  • Reinius LE, Acevedo N, Joerink M, Pershagen G, Dahlén S-E, Greco D, et al. Differential DNA methylation in purified human blood cells: implications for cell lineage and studies on disease susceptibility. PLoS One 2012; 7:e41361; http://dx.doi.org/10.1371/journal.pone.0041361; PMID: 22848472
  • Sun Z, Chai HS, Wu Y, White WM, Donkena KV, Klein CJ, et al. Batch effect correction for genome-wide methylation data with Illumina Infinium platform. BMC Med Genomics 2011; 4:84; http://dx.doi.org/10.1186/1755-8794-4-84; PMID: 22171553
  • Qu Y, Tan M, Kutner MH. Random effects models in latent class analysis for evaluating accuracy of diagnostic tests. Biometrics 1996; 52:797 - 810; http://dx.doi.org/10.2307/2533043; PMID: 8805757
  • Hui SL, Zhou XH. Evaluation of diagnostic tests without gold standards. Stat Methods Med Res 1998; 7:354 - 70; http://dx.doi.org/10.1191/096228098671192352; PMID: 9871952
  • Du P, Zhang X, Huang C-C, Jafari N, Kibbe WA, Hou L, et al. Comparison of Beta-value and M-value methods for quantifying methylation levels by microarray analysis. BMC Bioinformatics 2010; 11:587; http://dx.doi.org/10.1186/1471-2105-11-587; PMID: 21118553
  • Schmidl C, Klug M, Boeld TJ, Andreesen R, Hoffmann P, Edinger M, et al. Lineage-specific DNA methylation in T cells correlates with histone methylation and enhancer activity. Genome Res 2009; 19:1165 - 74; http://dx.doi.org/10.1101/gr.091470.109; PMID: 19494038
  • Ernst J, Kheradpour P, Mikkelsen TS, Shoresh N, Ward LD, Epstein CB, et al. Mapping and analysis of chromatin state dynamics in nine human cell types. Nature 2011; 473:43 - 9; http://dx.doi.org/10.1038/nature09906; PMID: 21441907
  • Illingworth RS, Bird AP. CpG islands--‘a rough guide’. FEBS Lett 2009; 583:1713 - 20; http://dx.doi.org/10.1016/j.febslet.2009.04.012; PMID: 19376112
  • Jones PA. Functions of DNA methylation: islands, start sites, gene bodies and beyond. Nat Rev Genet 2012; 13:484 - 92; http://dx.doi.org/10.1038/nrg3230; PMID: 22641018
  • Irizarry RA, Ladd-Acosta C, Wen B, Wu Z, Montano C, Onyango P, et al. The human colon cancer methylome shows similar hypo- and hypermethylation at conserved tissue-specific CpG island shores. Nat Genet 2009; 41:178 - 86; http://dx.doi.org/10.1038/ng.298; PMID: 19151715
  • Doi A, Park I-H, Wen B, Murakami P, Aryee MJ, Irizarry R, et al. Differential methylation of tissue- and cancer-specific CpG island shores distinguishes human induced pluripotent stem cells, embryonic stem cells and fibroblasts. Nat Genet 2009; 41:1350 - 3; http://dx.doi.org/10.1038/ng.471; PMID: 19881528
  • Hansen KD, Timp W, Bravo HC, Sabunciyan S, Langmead B, McDonald OG, et al. Increased methylation variation in epigenetic domains across cancer types. Nat Genet 2011; 43:768 - 75; http://dx.doi.org/10.1038/ng.865; PMID: 21706001
  • Rideout WM 3rd, Coetzee GA, Olumi AF, Jones PA. 5-Methylcytosine as an endogenous mutagen in the human LDL receptor and p53 genes. Science 1990; 249:1288 - 90; http://dx.doi.org/10.1126/science.1697983; PMID: 1697983
  • Ley TJ, Ding L, Walter MJ, McLellan MD, Lamprecht T, Larson DE, et al. DNMT3A mutations in acute myeloid leukemia. N Engl J Med 2010; 363:2424 - 33; http://dx.doi.org/10.1056/NEJMoa1005143; PMID: 21067377
  • Turcan S, Rohle D, Goenka A, Walsh LA, Fang F, Yilmaz E, et al. IDH1 mutation is sufficient to establish the glioma hypermethylator phenotype. Nature 2012; 483:479 - 83; http://dx.doi.org/10.1038/nature10866; PMID: 22343889
  • Dawson MA, Kouzarides T. Cancer epigenetics: from mechanism to therapy. Cell 2012; 150:12 - 27; http://dx.doi.org/10.1016/j.cell.2012.06.013; PMID: 22770212
  • Heichman KA, Warren JD. DNA methylation biomarkers and their utility for solid cancer diagnostics. Clin Chem Lab Med 2012; 50:1707 - 21; http://dx.doi.org/10.1515/cclm-2011-0935; PMID: 23089699
  • Heyn H, Esteller M. DNA methylation profiling in the clinic: applications and challenges. Nat Rev Genet 2012; 13:679 - 92; http://dx.doi.org/10.1038/nrg3270; PMID: 22945394
  • Laird PW. Principles and challenges of genomewide DNA methylation analysis. Nat Rev Genet 2010; 11:191 - 203; http://dx.doi.org/10.1038/nrg2732; PMID: 20125086
  • Leek JT, Storey JD. Capturing heterogeneity in gene expression studies by surrogate variable analysis. PLoS Genet 2007; 3:1724 - 35; http://dx.doi.org/10.1371/journal.pgen.0030161; PMID: 17907809
  • Du P, Kibbe WA, Lin SM. lumi: a pipeline for processing Illumina microarray. Bioinformatics 2008; 24:1547 - 8; http://dx.doi.org/10.1093/bioinformatics/btn224; PMID: 18467348
  • Beath K. randomLCA: Random Effects Latent Class Analysis. 2011. http://CRAN.R-project.org/package=randomLCA