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Items: 1 to 20 of 107

1.

How to make DNA methylome wide association studies more powerful.

Lin X, Barton S, Holbrook JD.

Epigenomics. 2016 Aug;8(8):1117-29. doi: 10.2217/epi-2016-0017. Epub 2016 Apr 7. Review.

3.

Cell-type deconvolution in epigenome-wide association studies: a review and recommendations.

Teschendorff AE, Zheng SC.

Epigenomics. 2017 May;9(5):757-768. doi: 10.2217/epi-2016-0153. Epub 2017 Mar 14. Review.

4.

Correcting for Sample Heterogeneity in Methylome-Wide Association Studies.

Zou JY.

Methods Mol Biol. 2017;1589:107-114. doi: 10.1007/7651_2015_266.

PMID:
26246354
5.

Epigenome-wide association studies for common human diseases.

Rakyan VK, Down TA, Balding DJ, Beck S.

Nat Rev Genet. 2011 Jul 12;12(8):529-41. doi: 10.1038/nrg3000. Review.

6.

Contrasting the effects of intra-uterine smoking and one-carbon micronutrient exposures on offspring DNA methylation.

Richmond RC, Joubert BR.

Epigenomics. 2017 Mar;9(3):351-367. doi: 10.2217/epi-2016-0135. Epub 2017 Feb 17. Review.

7.

EWAS: epigenome-wide association study software 2.0.

Xu J, Zhao L, Liu D, Hu S, Song X, Li J, Lv H, Duan L, Zhang M, Jiang Q, Liu G, Jin S, Liao M, Zhang M, Feng R, Kong F, Xu L, Jiang Y.

Bioinformatics. 2018 Aug 1;34(15):2657-2658. doi: 10.1093/bioinformatics/bty163.

8.

Increased correlation between methylation sites in epigenome-wide replication studies: impact on analysis and results.

Popovic M, Fasanelli F, Fiano V, Biggeri A, Richiardi L.

Epigenomics. 2017 Dec;9(12):1489-1502. doi: 10.2217/epi-2017-0073. Epub 2017 Nov 6.

PMID:
29106300
9.

An epigenome-wide association study in whole blood of measures of adiposity among Ghanaians: the RODAM study.

Meeks KAC, Henneman P, Venema A, Burr T, Galbete C, Danquah I, Schulze MB, Mockenhaupt FP, Owusu-Dabo E, Rotimi CN, Addo J, Smeeth L, Bahendeka S, Spranger J, Mannens MMAM, Zafarmand MH, Agyemang C, Adeyemo A.

Clin Epigenetics. 2017 Sep 21;9:103. doi: 10.1186/s13148-017-0403-x. eCollection 2017.

10.

Epigenetics, heritability and longitudinal analysis.

Nustad HE, Almeida M, Canty AJ, LeBlanc M, Page CM, Melton PE.

BMC Genet. 2018 Sep 17;19(Suppl 1):77. doi: 10.1186/s12863-018-0648-1.

11.

The repeatability of DNA methylation measures may also affect the power of epigenome-wide association studies.

Dugué PA, English DR, MacInnis RJ, Joo JE, Jung CH, Milne RL.

Int J Epidemiol. 2015 Aug;44(4):1460-1. doi: 10.1093/ije/dyv189. Epub 2015 Sep 5. No abstract available.

PMID:
26342585
13.

Guidance for DNA methylation studies: statistical insights from the Illumina EPIC array.

Mansell G, Gorrie-Stone TJ, Bao Y, Kumari M, Schalkwyk LS, Mill J, Hannon E.

BMC Genomics. 2019 May 14;20(1):366. doi: 10.1186/s12864-019-5761-7.

14.

Measuring epigenetics as the mediator of gene/environment interactions in DOHaD.

Ong ML, Lin X, Holbrook JD.

J Dev Orig Health Dis. 2015 Feb;6(1):10-6. doi: 10.1017/S2040174414000506. Epub 2014 Oct 15. Review.

PMID:
25315715
15.

Epigenome-wide association studies (EWAS): past, present, and future.

Flanagan JM.

Methods Mol Biol. 2015;1238:51-63. doi: 10.1007/978-1-4939-1804-1_3. Review.

16.

Recommendations for the design and analysis of epigenome-wide association studies.

Michels KB, Binder AM, Dedeurwaerder S, Epstein CB, Greally JM, Gut I, Houseman EA, Izzi B, Kelsey KT, Meissner A, Milosavljevic A, Siegmund KD, Bock C, Irizarry RA.

Nat Methods. 2013 Oct;10(10):949-55. doi: 10.1038/nmeth.2632. Review.

PMID:
24076989
17.

Is cellular heterogeneity merely a confounder to be removed from epigenome-wide association studies?

Holbrook JD, Huang RC, Barton SJ, Saffery R, Lillycrop KA.

Epigenomics. 2017 Aug;9(8):1143-1150. doi: 10.2217/epi-2017-0032. Epub 2017 Jul 27.

18.

Genome-wide DNA methylome variation in two genetically distinct chicken lines using MethylC-seq.

Li J, Li R, Wang Y, Hu X, Zhao Y, Li L, Feng C, Gu X, Liang F, Lamont SJ, Hu S, Zhou H, Li N.

BMC Genomics. 2015 Oct 23;16:851. doi: 10.1186/s12864-015-2098-8.

19.

Mining cancer methylomes: prospects and challenges.

Stirzaker C, Taberlay PC, Statham AL, Clark SJ.

Trends Genet. 2014 Feb;30(2):75-84. doi: 10.1016/j.tig.2013.11.004. Epub 2013 Dec 21. Review.

PMID:
24368016
20.

Methylome-wide association study of schizophrenia: identifying blood biomarker signatures of environmental insults.

Aberg KA, McClay JL, Nerella S, Clark S, Kumar G, Chen W, Khachane AN, Xie L, Hudson A, Gao G, Harada A, Hultman CM, Sullivan PF, Magnusson PK, van den Oord EJ.

JAMA Psychiatry. 2014 Mar;71(3):255-64. doi: 10.1001/jamapsychiatry.2013.3730.

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