德纳姆
DNA甲基化
CpG站点
计算生物学
甲基化
生物
背景(考古学)
遗传学
假阳性悖论
差异甲基化区
亚硫酸氢盐测序
表观遗传学
计算机科学
DNA
胞嘧啶
表观遗传学
照明菌甲基化试验
基因
人工智能
基因表达
古生物学
作者
Evan Gatev,Nicole Gladish,Sara Mostafavi,Michael S. Kobor
出处
期刊:Bioinformatics
[Oxford University Press]
日期:2020-05-01
卷期号:36 (9): 2675-2683
被引量:24
标识
DOI:10.1093/bioinformatics/btaa049
摘要
Abstract Motivation High-dimensional DNA methylation (DNAm) array coverage, while sparse in the context of the entire DNA methylome, still constitutes a very large number of CpG probes. The ensuing multiple-test corrections affect the statistical power to detect associations, likely contributing to prevalent limited reproducibility. Array probes measuring proximal CpG sites often have correlated levels of DNAm that may not only be biologically meaningful but also imply statistical dependence and redundancy. New methods that account for such correlations between adjacent probes may enable improved specificity, discovery and interpretation of statistical associations in DNAm array data. Results We developed a method named Co-Methylation with genomic CpG Background (CoMeBack) that estimates DNA co-methylation, defined as proximal CpG probes with correlated DNAm across individuals. CoMeBack outputs co-methylated regions (CMRs), spanning sets of array probes constructed based on all genomic CpG sites, including those not measured on the array, and without any phenotypic variable inputs. This approach can reduce the multiple-test correction burden, while enhancing the discovery and specificity of statistical associations. We constructed and validated CMRs in whole blood, using publicly available Illumina Infinium 450 K array data from over 5000 individuals. These CMRs were enriched for enhancer chromatin states, and binding site motifs for several transcription factors involved in blood physiology. We illustrated how CMR-based epigenome-wide association studies can improve discovery and reduce false positives for associations with chronological age. Availability and implementation https://bitbucket.org/flopflip/comeback. Supplementary information Supplementary data are available at Bioinformatics online.
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