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用于分析 Illumina Infinium HumanMethylation450 BeadChip 中 DNA 甲基化数据的框架。

A framework for analyzing DNA methylation data from Illumina Infinium HumanMethylation450 BeadChip.

机构信息

School of Computer Science and Technology, Harbin Institute of Technology, Harbin, 150001, China.

出版信息

BMC Bioinformatics. 2018 Apr 11;19(Suppl 5):115. doi: 10.1186/s12859-018-2096-3.

Abstract

BACKGROUND

DNA methylation has been identified to be widely associated to complex diseases. Among biological platforms to profile DNA methylation in human, the Illumina Infinium HumanMethylation450 BeadChip (450K) has been accepted as one of the most efficient technologies. However, challenges exist in analysis of DNA methylation data generated by this technology due to widespread biases.

RESULTS

Here we proposed a generalized framework for evaluating data analysis methods for Illumina 450K array. This framework considers the following steps towards a successful analysis: importing data, quality control, within-array normalization, correcting type bias, detecting differentially methylated probes or regions and biological interpretation.

CONCLUSIONS

We evaluated five methods using three real datasets, and proposed outperform methods for the Illumina 450K array data analysis. Minfi and methylumi are optimal choice when analyzing small dataset. BMIQ and RCP are proper to correcting type bias and the normalized result of them can be used to discover DMPs. R package missMethyl is suitable for GO term enrichment analysis and biological interpretation.

摘要

背景

DNA 甲基化已被广泛认为与复杂疾病有关。在用于分析人类 DNA 甲基化的生物平台中,Illumina Infinium HumanMethylation450 BeadChip(450K)已被认为是最有效的技术之一。然而,由于广泛存在的偏差,该技术产生的 DNA 甲基化数据的分析存在挑战。

结果

我们提出了一个用于评估 Illumina 450K 阵列数据分析方法的通用框架。该框架考虑了成功分析的以下步骤:导入数据、质量控制、阵列内标准化、纠正类型偏差、检测差异甲基化探针或区域以及生物学解释。

结论

我们使用三个真实数据集评估了五种方法,并提出了针对 Illumina 450K 阵列数据分析的表现更好的方法。当分析小数据集时,Minfi 和 methylumi 是最佳选择。BMIQ 和 RCP 适合纠正类型偏差,并且它们的标准化结果可用于发现 DMPs。R 包 missMethyl 适用于 GO 术语富集分析和生物学解释。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/732f/5907140/10dd53a258d8/12859_2018_2096_Fig1_HTML.jpg

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