A data-driven approach to preprocessing Illumina 450K methylation array data
Ruth Pidsley,Chloe C. Y. Wong,Manuela Volta,Katie Lunnon,Jonathan Mill,Jonathan Mill,Leonard C. Schalkwyk +6 more
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TLDR
It is demonstrated that quantile normalization methods produce marked improvement, even in highly consistent data, by all three metrics, and that careful selection of preprocessing steps can minimize variance and thus improve statistical power, especially for the detection of the small absolute DNA methylation changes likely associated with complex disease phenotypes.Abstract:
As the most stable and experimentally accessible epigenetic mark, DNA methylation is of great interest to the research community. The landscape of DNA methylation across tissues, through development and in disease pathogenesis is not yet well characterized. Thus there is a need for rapid and cost effective methods for assessing genome-wide levels of DNA methylation. The Illumina Infinium HumanMethylation450 (450K) BeadChip is a very useful addition to the available methods for DNA methylation analysis but its complex design, incorporating two different assay methods, requires careful consideration. Accordingly, several normalization schemes have been published. We have taken advantage of known DNA methylation patterns associated with genomic imprinting and X-chromosome inactivation (XCI), in addition to the performance of SNP genotyping assays present on the array, to derive three independent metrics which we use to test alternative schemes of correction and normalization. These metrics also have potential utility as quality scores for datasets. The standard index of DNA methylation at any specific CpG site is β = M/(M + U + 100) where M and U are methylated and unmethylated signal intensities, respectively. Betas (βs) calculated from raw signal intensities (the default GenomeStudio behavior) perform well, but using 11 methylomic datasets we demonstrate that quantile normalization methods produce marked improvement, even in highly consistent data, by all three metrics. The commonly used procedure of normalizing betas is inferior to the separate normalization of M and U, and it is also advantageous to normalize Type I and Type II assays separately. More elaborate manipulation of quantiles proves to be counterproductive. Careful selection of preprocessing steps can minimize variance and thus improve statistical power, especially for the detection of the small absolute DNA methylation changes likely associated with complex disease phenotypes. For the convenience of the research community we have created a user-friendly R software package called wateRmelon, downloadable from bioConductor, compatible with the existing methylumi, minfi and IMA packages, that allows others to utilize the same normalization methods and data quality tests on 450K data.read more
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Classification of large DNA methylation datasets for identifying cancer drivers
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Epigenome-Wide Association Study Indicates Hypomethylation of MTRNR2L8 in Large-Artery Atherosclerosis Stroke.
Yupei Shen,Chen Peng,Chen Peng,Qingke Bai,Ying Ding,Ying Ding,Xin Yi,Huihui Du,Lin He,Daizhan Zhou,Xu Chen,Xu Chen +11 more
TL;DR: Findings demonstrate that DNA methylation plays an important role in large-artery atherosclerotic stroke and that methylation of MTRNR2L8 is a potential therapeutic target and diagnostic biomarker for stroke.
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Cumulative lifetime maternal stress and epigenome-wide placental DNA methylation in the PRISM cohort.
Kelly J. Brunst,Nicole Tignor,Allan C. Just,Zhonghua Liu,Xihong Lin,Michele R. Hacker,Michele R. Hacker,Michelle Bosquet Enlow,Robert O. Wright,Pei Wang,Andrea A. Baccarelli,Rosalind J. Wright +11 more
TL;DR: Investigation of epigenome-wide placental DNA methylation in relation to maternal experiences of traumatic and non-traumatic stressors over her lifetime assessed using the Life Stressor Checklist-Revised (LSC-R) survey found lysine degradation to be the most significant pathway associated with maternal lifetimes stress exposure.
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DNA methylation and inflammation marker profiles associated with a history of depression
Bethany Crawford,Zoe Craig,Georgina Mansell,Isobel White,Adam Smith,Steve Spaull,Jennifer Imm,Eilis Hannon,Andrew R. Wood,Hanieh Yaghootkar,Yingjie Ji,Niamh Mullins,Cathryn M. Lewis,Jonathan Mill,Therese M. Murphy +14 more
TL;DR: In this article, the authors assessed genome-wide patterns of DNA methylation in whole blood-derived DNA obtained from individuals with and without a self-reported history of depression using the Illumina 450K microarray and identified six significant (Sidak corrected P < 0.05) depression-associated differentially methylated regions (DMRs).
Journal ArticleDOI
Methylomic markers of persistent childhood asthma: a longitudinal study of asthma-discordant monozygotic twins.
Therese M. Murphy,Chloe C. Y. Wong,Louise Arseneault,Joe Burrage,Ruby Macdonald,Eilis Hannon,Helen L. Fisher,Antony Ambler,Terrie E. Moffitt,Terrie E. Moffitt,Avshalom Caspi,Avshalom Caspi,Jonathan Mill,Jonathan Mill +13 more
TL;DR: The data suggest that differences in DNA methylation associated with childhood asthma which persists into early adulthood are distinct from those associated with asthma which remits.
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