Article title: Patterns of reliability: Assessing the reproducibility and integrity of DNA methylation measurement Authors: Karen Sugden, Ph.D*, Eilis J. Hannon, Ph.D, Louise Arseneault, Ph.D, Daniel W. Belsky, Ph.D, David L. Corcoran, Ph.D, Helen L. Fisher, Ph.D, Renate M. Houts, Ph.D, Radhika Kandaswamy, Ph.D, Terrie E. Moffitt, Ph.D, Richie Poulton, Ph.D, Joseph A Prinz, B.A, Line J.H. Rasmussen, Ph.D, Benjamin S. Williams, B.Sc, Chloe C. Y. Wong, Ph.D, Jonathan Mill, Ph.D, Avshalom Caspi, Ph.D Article link: TBD DNA methylation plays an important role in both normal human development and risk of disease. The most utilized method of assessing DNA methylation uses BeadChips, generating an epigenome-wide ‘snapshot’ of >450,000 observations (probe measurements) per assay. However, the reliability of each of these measurements is not equal, and little consideration is paid to consequences for research. We correlated repeat measurements of the same DNA samples using the Illumina HumanMethylation450K and the Infinium MethylationEPIC BeadChips in 350 blood-DNA samples. Probes that were reliably measured were more heritable, and showed consistent associations with environmental exposures, gene expression, and greater cross-tissue concordance. Unreliable probes were less replicable and generated an unknown volume of false negatives. This serves a lesson for working with DNA methylation data, but the lessons are equally applicable to working with other data: as we advance towards generating increasingly greater volumes of data, failure to document reliability risks harming reproducibility. Supplemental file: Within the ‘Files’ section is a supplemental results file named ‘Sugden_MethylationReliability_Data_S1.xlsx’. This file is also available with the published article. The table includes details of reliability, mean and SD of β level, and annotations for the ~440,000 probes in the 450K–EPIC comparison. To interact with the file effectively, we recommend downloading and opening in Microsoft Excel (WARNING: file size is ~47MB and might take a long time to download on slow internet connections). Once open in excel, we have included filter/sort options for each column; the option is available via the filter button included in each column header. To apply a filter option, select the button in the appropriate column and select a filter or sort criterion from the drop-down menu (e.g. increasing P-value sort, text string filter for gene name). To deselect a currently applied filter, select ‘clear filter’ option from the drop-down menu.