scholarly journals Report on the Infinium 450k Methylation Array Analysis Workshop

Epigenetics ◽  
2012 ◽  
Vol 7 (8) ◽  
pp. 961-962 ◽  
Author(s):  
Tiffany Morris ◽  
Robert Lowe
Keyword(s):  
Array Analysis ◽  
Methylation Array ◽  
450K Methylation

scholarly journals Discovery and Validation of Methylation Biomarkers for Ulcerative Colitis Associated Neoplasia

2018 ◽  
Vol 24 (7) ◽  
pp. 1503-1509 ◽  
Author(s):  
Andrew D Beggs ◽  
Jonathan James ◽  
Germaine Caldwell ◽  
Toby Prout ◽  
Mark P Dilworth ◽  
...  
Keyword(s):  
Ulcerative Colitis ◽  
Validation Cohort ◽  
Chronic Colitis ◽  
Array Analysis ◽  
Methylation Array ◽  
Illumina 450K ◽  
Colonic Biopsy ◽  
Potential Biomarker ◽  
Targeted Biopsies ◽  
450K Methylation

Abstract Background and aims Ulcerative colitis (UC) is associated with a higher background risk of dysplasia and/or neoplasia due to chronic inflammation. There exist few biomarkers for identification of patients with dysplasia, and targeted biopsies in this group of patients are inaccurate in reliably identifying dysplasia. We aimed to examine the epigenome of UC dysplasia and to identify and validate potential biomarkers Methods Colonic samples from patients with UC-associated dysplasia or neoplasia underwent epigenome-wide analysis on the Illumina 450K methylation array. Markers were validated by bisulphite pyrosequencing on a secondary validation cohort and accuracy calculated using logistic regression and receiver-operator curves. Results Twelve samples from 4 patients underwent methylation array analysis and 6 markers (GNG7, VAV3, KIF5C, PIK3R5, TUBB6, and ZNF583) were taken forward for secondary validation on a cohort of 71 colonic biopsy samples consisting of normal uninflamed mucosa from control patients, acute and chronic colitis, “field” mucosa in patients with dysplasia/neoplasia, dysplasia, and neoplasia. Methylation in the beta-tubulin TUBB6 correlated with the presence of dysplasia (P < 0.0001) and accurately discriminated between dysplasia and nondysplastic tissue, even in the apparently normal field mucosa downstream from dysplastic lesions (AUC 0.84, 95% CI 0.81–0.87). Conclusions Methylation in TUBB6 is a potential biomarker for UC- associated dysplasia. Further validation is needed and is ongoing as part of the ENDCAP-C study.

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

BMC Genomics ◽  
2013 ◽  
Vol 14 (1) ◽  
pp. 293 ◽  
Author(s):  
Ruth Pidsley ◽  
Chloe C Y Wong ◽  
Manuela Volta ◽  
Katie Lunnon ◽  
Jonathan Mill ◽  
...  
Keyword(s):  
Data Driven ◽  
Methylation Array ◽  
Array Data ◽  
Illumina 450K ◽  
Data Driven Approach ◽  
450K Methylation

scholarly journals DNA methylation array analysis identifies breast cancer associated RPTOR, MGRN1 and RAPSN hypomethylation in peripheral blood DNA

Oncotarget ◽  
2016 ◽  
Vol 7 (39) ◽  
pp. 64191-64202 ◽  
Author(s):  
Qiuqiong Tang ◽  
Tim Holland-Letz ◽  
Alla Slynko ◽  
Katarina Cuk ◽  
Frederik Marme ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Dna Methylation ◽  
Peripheral Blood ◽  
Array Analysis ◽  
Methylation Array ◽  
Dna Methylation Array

scholarly journals CopyNumber450kCancer: baseline correction for accurate copy number calling from the 450k methylation array

2015 ◽  
Vol 32 (7) ◽  
pp. 1080-1082 ◽  
Author(s):  
Nour-al-dain Marzouka ◽  
Jessica Nordlund ◽  
Christofer L. Bäcklin ◽  
Gudmar Lönnerholm ◽  
Ann-Christine Syvänen ◽  
...  
Keyword(s):  
Copy Number ◽  
Baseline Correction ◽  
Methylation Array ◽  
450K Methylation

scholarly journals Determination of Zygosity in Adult Chinese Twins Using the 450K Methylation Array versus Questionnaire Data

PLoS ONE ◽  
2015 ◽  
Vol 10 (4) ◽  
pp. e0123992 ◽  
Author(s):  
Biqi Wang ◽  
Wenjing Gao ◽  
Canqing Yu ◽  
Weihua Cao ◽  
Jun Lv ◽  
...  
Keyword(s):  
Questionnaire Data ◽  
Methylation Array ◽  
Chinese Twins ◽  
450K Methylation

scholarly journals Functional normalization of 450k methylation array data improves replication in large cancer studies

2014 ◽  
Vol 15 (11) ◽  
Author(s):  
Jean-Philippe Fortin ◽  
Aurélie Labbe ◽  
Mathieu Lemire ◽  
Brent W Zanke ◽  
Thomas J Hudson ◽  
...  
Keyword(s):  
Methylation Array ◽  
Array Data ◽  
Cancer Studies ◽  
450K Methylation

scholarly journals Genome-wide methylation data mirror ancestry information

2016 ◽  
Author(s):  
Elior Rahmani ◽  
Liat Shenhav ◽  
Regev Schweiger ◽  
Paul Yousefi ◽  
Karen Huen ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Genetic Data ◽  
Data Sets ◽  
Methylation Data ◽  
Methylation Array ◽  
Information Signal ◽  
Genome Wide ◽  
Public Data ◽  
Dna Methylation Analysis ◽  
450K Methylation

AbstractGenetic data are known to harbor information about human demographics, and genotyping data are commonly used for capturing ancestry information by leveraging genome-wide differences between populations. In contrast, it is not clear to what extent population structure is captured by whole-genome DNA methylation data. We demonstrate, using three large cohort 450K methylation array data sets, that ancestry information signal is mirrored in genome-wide DNA methylation data, and that it can be further isolated more effectively by leveraging the correlation structure of CpGs with cis-located SNPs. Based on these insights, we propose a method, EPISTRUCTURE, for the inference of ancestry from methylation data, without the need for genotype data. EPISTRUCTURE can be used to infer ancestry information of individuals based on their methylation data in the absence of corresponding genetic data. Although genetic data are often collected in epigenetic studies of large cohorts, these are typically not made publicly available, making the application of EPISTRUCTURE especially useful for anyone working on public data. Implementation of EPISTRUCTURE is available in GLINT, our recently released toolset for DNA methylation analysis at: http://glint-epigenetics.readthedocs.io.

scholarly journals Functional normalization of 450k methylation array data improves replication in large cancer studies

2014 ◽  
Author(s):  
Jean-Philippe Fortin ◽  
Aurélie Labbe ◽  
Mathieu Lemire ◽  
Brent W. Zanke ◽  
Thomas J. Hudson ◽  
...  
Keyword(s):  
Microarray Platform ◽  
The Cancer Genome Atlas ◽  
Methylation Array ◽  
Illumina 450K ◽  
Normalization Methods ◽  
Cancer Genome Atlas ◽  
Cancer Studies ◽  
Control Study ◽  
Large Case ◽  
450K Methylation

AbstractWe propose an extension to quantile normalization which removes unwanted technical variation using control probes. We adapt our algorithm, functional normalization, to the Illumina 450k methylation array and address the open problem of normalizing methylation data with global epigenetic changes, such as human cancers. Using datasets from The Cancer Genome Atlas and a large case-control study, we show that our algorithm outperforms all existing normalization methods with respect to replication of results between experiments, and yields robust results even in the presence of batch effects. Functional normalization can be applied to any microarray platform, provided suitable control probes are available.

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