recountmethylation enables flexible analysis of public blood DNA methylation array data.

recountmethylation enables flexible analysis of public blood DNA methylation array data.
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DOI:
10.1093/bioadv/vbad020
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发表时间:
2023
期刊:
Bioinformatics advances
影响因子:
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其他
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基因表达综合库 (GEO) 上公开提供了数千个来自人类血液的 DNA 甲基化 (DNAm) 阵列样本,但它们在实验规划、复制以及交叉研究和跨平台分析方面仍未得到充分利用。为了促进这些任务,我们在 GEO 上添加了 12 537 个统一处理的 EPIC 和 HM450K 血液样本以及一些新功能,从而增强了重新计数甲基化 R/Bioconductor 包。我们随后在几项说明性分析中使用了更新后的软件包,发现 (i) 研究 ID 偏差调整增加了由生物和人口统计学变量解释的变异,(ii) 常染色体 DNAm 的大多数变异由遗传血统和 CD4+ T 细胞分数解释,以及 (iii) 检测差异甲基化的功效对样本量的依赖性对于每种外周血单核细胞 (PBMC)、全血和脐带血都是相似的。最后,我们使用 PBMC 和全血进行独立验证,并从之前发表的两项表观基因组范围关联研究中回收了 38-46% 的性别间差异甲基化探针。重现主要结果的源代码可在 GitHub 上找到(存储库:recountmethylation_flexible-blood-analysis_manuscript;网址:https://github.com/metamaden/recountmethylation_flexible-blood-analysis_manuscript)。所有数据都是公开的,并可从基因表达综合库 (https://www.ncbi.nlm.nih.gov/geo/) 下载。分析的公共数据的汇编可以从网站 recount.bio/data 访问(预处理的 HM450K 阵列数据:https://recount.bio/data/remethdb_h5se-gm_epic_0-0-2_1589820348/;预处理的 EPIC 阵列数据: https://recount.bio/data/remethdb_h5se-gm_epic_0-0-2_1589820348/)。 补充数据可在生物信息学进展在线获取。
Thousands of DNA methylation (DNAm) array samples from human blood are publicly available on the Gene Expression Omnibus (GEO), but they remain underutilized for experiment planning, replication and cross-study and cross-platform analyses. To facilitate these tasks, we augmented our recountmethylation R/Bioconductor package with 12 537 uniformly processed EPIC and HM450K blood samples on GEO as well as several new features. We subsequently used our updated package in several illustrative analyses, finding (i) study ID bias adjustment increased variation explained by biological and demographic variables, (ii) most variation in autosomal DNAm was explained by genetic ancestry and CD4+ T-cell fractions and (iii) the dependence of power to detect differential methylation on sample size was similar for each of peripheral blood mononuclear cells (PBMC), whole blood and umbilical cord blood. Finally, we used PBMC and whole blood to perform independent validations, and we recovered 38–46% of differentially methylated probes between sexes from two previously published epigenome-wide association studies. Source code to reproduce the main results are available on GitHub (repo: recountmethylation_flexible-blood-analysis_manuscript; url: https://github.com/metamaden/recountmethylation_flexible-blood-analysis_manuscript). All data was publicly available and downloaded from the Gene Expression Omnibus (https://www.ncbi.nlm.nih.gov/geo/). Compilations of the analyzed public data can be accessed from the website recount.bio/data (preprocessed HM450K array data: https://recount.bio/data/remethdb_h5se-gm_epic_0-0-2_1589820348/; preprocessed EPIC array data: https://recount.bio/data/remethdb_h5se-gm_epic_0-0-2_1589820348/). Supplementary data are available at Bioinformatics Advances online.
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