RnBeads 2.0: comprehensive analysis of DNA methylation data
文章链接：https://genomebiology.biomedcentral.com/articles/10.1186/s13059-019-1664-9
RnBeads包的scripts在biocnductor：https://bioconductor.org/packages/release/bioc/html/RnBeads.html
生词
WGBS：（Whole-genome bisulfite sequencing）全基因组重亚硫酸盐测序,用于全基因组DNA甲基化检测
RRBS：（Reduced Representation Bisulfite Sequencing）是一种准确且高性价比的DNA甲基化研究方法，在大规模临床样本的研究中有着广泛的应用。RRBS通过限制性内切酶对基因组进行酶切，富集启动子及CpG岛区域，再进行Bisulfite转化，用较小的数据量得到包含最多CpG位点甲基化信息的单碱基精度的甲基化图谱。
背景
DNA甲基化
DNA methylation at CpG dinucleotides is a widely studied epigenetic mark that is involved in the regulation of cell state and relevant for a broad range of diseases. Changes in DNA methylation at promoters and enhancers have been associated with cell differentiation, developmental processes, cancer development, and regulation of the immune system.
介绍在WGBS的应用情况
WGBS requires deep sequencing of the entire genome (which is a significant cost factor), while shallow sequencing leads to poor sensitivity for detecting small differences in DNA methylation.
介绍在 RRBS的应用情况
RRBS is particularly useful for studying DNA methylation heterogeneity, which profits from deep sequencing coverage and from analyzing many samples using a sequencing-based assay [5,6,7,8]. Target-capture bisulfite sequencing enables the analysis of a defined set of genomic regions in large numbers of samples at low cost per sample, but with high setup cost.
介绍 microarray-based Infinium DNA methylation assays
The microarray-based Infinium DNA methylation assays—including the MethylationEPIC BeadChip (EPIC) and its predecessor, the HumanMethylation450 BeadChip (450k)—facilitate standardized, high-throughput DNA methylation profiling of a pre-defined subset of CpGs in large sample cohorts.
结果
概述
RnBeads includes modules for data import, quality control, filtering and normalization (“preprocessing”), export of processed data (“tracks and tables”), covariate inference (e.g., predicting epigenetic age and cell type heterogeneity from DNA methylation data), exploratory analysis (e.g., dimension reduction, global distribution of DNA methylation levels, hierarchical clustering), and differential DNA methylation analysis
image-20200127204235759
在这个2019版之前作者已经出版了2014版，在这篇文章中作者说着重强调四点
1.可以整合不同平台的数据，包括：EPIC, 450k, and 27k microarrays as well as WGBS and RRBS
原文描述为New data types and cross-platform analysis facilitates DNA methylation meta-analyses that combine several data sources into a single set of results.
2.可以对数据进行质控和缺失值也有相应的处理
原文描述为Extended analysis and inference methods: We added new functionality for handling incomplete data and missing values, for detecting genetic evidence of sample contamination or low data quality, for quantifying DNA methylation heterogeneity, and for DNA methylation-based inference of phenotypic information.
3.友好的用户界面
原文描述为New user-friendly interface: Together with RnBeads’ interactive and self-explanatory HTML reports, this new interface makes RnBeads analyses more readily accessible for users with limited R/Bioconductor knowledge.
4.效率提升
重点
作者用了四个例子四张图片来举例说明他们开发的这个R包的棒点，分别从Fig.2到Fig.5进行展示。
Case 1
Analyzing DNA methylation in a large cohort of peripheral blood samples.
image-20200127204507509
image-20200127204650322
Case 2
Dissecting the DNA methylation landscape of human hematopoiesis
image-20200127204618670
image-20200127204626549
Case 3
Quantifying DNA methylation heterogeneity in a childhood cancer cohort
image-20200127205406510
image-20200127205427763
Case 4
Analyzing DNA methylation data across different assay platforms
image-20200127204711778
image-20200127204742683
收获
文章中的几个case都是来自已经发表文章中的数据，作者利用以往的几个平台的数据进行了重新分析。这几个case正好表明了这个软件可以分析的内容 。不过，文章虽然阅读完了，也大概知道了这个软件的用处，不过如果不真正分析甲基化的数据的话，收获就仅仅限于知道、了解有这样一个软件了。所以，可以暂时先做为前期的一个探索，包的具体用法，如果能用的话，是一定要去探索的了。
网友评论