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Items: 1 to 20 of 152

1.

Batch effect correction for genome-wide methylation data with Illumina Infinium platform.

Sun Z, Chai HS, Wu Y, White WM, Donkena KV, Klein CJ, Garovic VD, Therneau TM, Kocher JP.

BMC Med Genomics. 2011 Dec 16;4:84. doi: 10.1186/1755-8794-4-84.

3.

Considerations for normalization of DNA methylation data by Illumina 450K BeadChip assay in population studies.

Yousefi P, Huen K, Aguilar Schall R, Decker A, Elboudwarej E, Quach H, Barcellos L, Holland N.

Epigenetics. 2013 Nov;8(11):1141-52. doi: 10.4161/epi.26037. Epub 2013 Aug 19.

PMID:
23959097
4.

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

Marabita F, Almgren M, Lindholm ME, Ruhrmann S, Fagerström-Billai F, Jagodic M, Sundberg CJ, Ekström TJ, Teschendorff AE, Tegnér J, Gomez-Cabrero D.

Epigenetics. 2013 Mar;8(3):333-46. doi: 10.4161/epi.24008. Epub 2013 Feb 19.

5.

Analysis of genome-wide DNA methylation profiles by BeadChip technology.

Lin Q, Wagner W, Zenke M.

Methods Mol Biol. 2013;1049:21-33. doi: 10.1007/978-1-62703-547-7_3.

PMID:
23913206
6.

A systematic study of normalization methods for Infinium 450K methylation data using whole-genome bisulfite sequencing data.

Wang T, Guan W, Lin J, Boutaoui N, Canino G, Luo J, Celedón JC, Chen W.

Epigenetics. 2015;10(7):662-9. doi: 10.1080/15592294.2015.1057384.

7.

SWAN: Subset-quantile within array normalization for illumina infinium HumanMethylation450 BeadChips.

Maksimovic J, Gordon L, Oshlack A.

Genome Biol. 2012 Jun 15;13(6):R44. doi: 10.1186/gb-2012-13-6-r44.

8.

A systematic assessment of normalization approaches for the Infinium 450K methylation platform.

Wu MC, Joubert BR, Kuan PF, Håberg SE, Nystad W, Peddada SD, London SJ.

Epigenetics. 2014 Feb;9(2):318-29. doi: 10.4161/epi.27119. Epub 2013 Nov 15.

9.

A coherent approach for analysis of the Illumina HumanMethylation450 BeadChip improves data quality and performance in epigenome-wide association studies.

Lehne B, Drong AW, Loh M, Zhang W, Scott WR, Tan ST, Afzal U, Scott J, Jarvelin MR, Elliott P, McCarthy MI, Kooner JS, Chambers JC.

Genome Biol. 2015 Feb 15;16:37. doi: 10.1186/s13059-015-0600-x. Erratum in: Genome Biol. 2016;17:73.

10.

Comparison of different normalization assumptions for analyses of DNA methylation data from the cancer genome.

Wang D, Zhang Y, Huang Y, Li P, Wang M, Wu R, Cheng L, Zhang W, Zhang Y, Li B, Wang C, Guo Z.

Gene. 2012 Sep 10;506(1):36-42. doi: 10.1016/j.gene.2012.06.075. Epub 2012 Jul 4.

PMID:
22771920
11.

Evaluation of the Infinium Methylation 450K technology.

Dedeurwaerder S, Defrance M, Calonne E, Denis H, Sotiriou C, Fuks F.

Epigenomics. 2011 Dec;3(6):771-84. doi: 10.2217/epi.11.105.

12.

Discovery of cross-reactive probes and polymorphic CpGs in the Illumina Infinium HumanMethylation450 microarray.

Chen YA, Lemire M, Choufani S, Butcher DT, Grafodatskaya D, Zanke BW, Gallinger S, Hudson TJ, Weksberg R.

Epigenetics. 2013 Feb;8(2):203-9. doi: 10.4161/epi.23470. Epub 2013 Jan 11.

13.

Genome-wide DNA methylation analysis of archival formalin-fixed paraffin-embedded tissue using the Illumina Infinium HumanMethylation27 BeadChip.

Thirlwell C, Eymard M, Feber A, Teschendorff A, Pearce K, Lechner M, Widschwendter M, Beck S.

Methods. 2010 Nov;52(3):248-54. doi: 10.1016/j.ymeth.2010.04.012. Epub 2010 Apr 29. Review.

PMID:
20434562
14.

A data-driven approach to preprocessing Illumina 450K methylation array data.

Pidsley R, Y Wong CC, Volta M, Lunnon K, Mill J, Schalkwyk LC.

BMC Genomics. 2013 May 1;14:293. doi: 10.1186/1471-2164-14-293.

15.

Genome-wide DNA methylation differences between late-onset Alzheimer's disease and cognitively normal controls in human frontal cortex.

Bakulski KM, Dolinoy DC, Sartor MA, Paulson HL, Konen JR, Lieberman AP, Albin RL, Hu H, Rozek LS.

J Alzheimers Dis. 2012;29(3):571-88. doi: 10.3233/JAD-2012-111223.

16.

missMethyl: an R package for analyzing data from Illumina's HumanMethylation450 platform.

Phipson B, Maksimovic J, Oshlack A.

Bioinformatics. 2016 Jan 15;32(2):286-8. doi: 10.1093/bioinformatics/btv560. Epub 2015 Sep 30.

PMID:
26424855
17.

A beta-mixture quantile normalization method for correcting probe design bias in Illumina Infinium 450 k DNA methylation data.

Teschendorff AE, Marabita F, Lechner M, Bartlett T, Tegner J, Gomez-Cabrero D, Beck S.

Bioinformatics. 2013 Jan 15;29(2):189-96. doi: 10.1093/bioinformatics/bts680. Epub 2012 Nov 21.

18.

Base resolution methylome profiling: considerations in platform selection, data preprocessing and analysis.

Sun Z, Cunningham J, Slager S, Kocher JP.

Epigenomics. 2015 Aug;7(5):813-28. doi: 10.2217/epi.15.21. Epub 2015 Sep 14. Review.

19.

An evaluation of two-channel ChIP-on-chip and DNA methylation microarray normalization strategies.

Adriaens ME, Jaillard M, Eijssen LM, Mayer CD, Evelo CT.

BMC Genomics. 2012 Jan 25;13:42. doi: 10.1186/1471-2164-13-42.

20.

Normalization of Illumina Infinium whole-genome SNP data improves copy number estimates and allelic intensity ratios.

Staaf J, Vallon-Christersson J, Lindgren D, Juliusson G, Rosenquist R, Höglund M, Borg A, Ringnér M.

BMC Bioinformatics. 2008 Oct 2;9:409. doi: 10.1186/1471-2105-9-409.

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