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Identifying mislabeled and contaminated DNA methylation microarray data: an extended quality control toolset with examples from GEO.
Heiss, Jonathan A; Just, Allan C.
Afiliación
  • Heiss JA; Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1057, New York, 10029 NY USA.
  • Just AC; Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1057, New York, 10029 NY USA.
Clin Epigenetics ; 10: 73, 2018.
Article en En | MEDLINE | ID: mdl-29881472
Background: Mislabeled, contaminated or poorly performing samples can threaten power in methylation microarray analyses or even result in spurious associations. We describe a set of quality checks for the popular Illumina 450K and EPIC microarrays to identify problematic samples and demonstrate their application in publicly available datasets. Methods: Quality checks implemented here include 17 control metrics defined by the manufacturer, a sex check to detect mislabeled sex-discordant samples, and both an identity check for fingerprinting sample donors and a measure of sample contamination based on probes querying high-frequency SNPs. These checks were tested on 80 datasets comprising 8327 samples run on the 450K microarray from the GEO repository. Results: Nine hundred forty samples were flagged by at least one control metric and 133 samples from 20 datasets were assigned the wrong sex. In a dataset in which a subset of samples appear contaminated with a single source of DNA, we demonstrate that our measure based on outliers among SNP probes was strongly correlated (> 0.95) with another independent measure of contamination. Conclusions: A more complete examination of samples that may be mislabeled, contaminated, or have poor performance due to technical problems will improve downstream analyses and replication of findings. We demonstrate that quality control problems are prevalent in a public repository of DNA methylation data. We advocate for a more thorough quality control workflow in epigenome-wide association studies and provide a software package to perform the checks described in this work. Reproducible code and supplementary material are available at 10.5281/zenodo.1172730.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Metilación de ADN / Análisis de Secuencia por Matrices de Oligonucleótidos / Bases de Datos Genéticas Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Clin Epigenetics Año: 2018 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Metilación de ADN / Análisis de Secuencia por Matrices de Oligonucleótidos / Bases de Datos Genéticas Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Clin Epigenetics Año: 2018 Tipo del documento: Article