Shulou(Shulou.com)06/02 Report--

This article focuses on "how to use TCGAbiolinks for methylation and transcriptome data association", interested friends may wish to take a look. The method introduced in this paper is simple, fast and practical. Let's let the editor learn how to use TCGAbiolinks for methylation and federation of transcriptome data.

As an important epigenetic marker, DNA methylation plays an important role in the regulation of gene expression. Studies have shown that methylation in the promoter region can inhibit gene expression. Combined with methylation data and gene expression profile data, the regulatory function of methylation can be better analyzed.

TCGAbiolinks can be used to analyze not only certain types of data, but also multi-group data. The joint analysis process of DNA methylation and gene expression profile data is as follows.

1. Methylation chip data

Taking adrenocortical carcinoma as an example, the data of 450K methylation chip was downloaded from TCGA database, and the differential methylation sites were obtained after analysis.

The volcano map of differential methylation sites is as follows

two。 Gene expression profile data

First download the data

Then carry on the difference analysis, the code is as follows

The drawing code of the differential gene volcano map is as follows

The effect picture is as follows

3. Joint analysis

Starburst plot is the most commonly used visualization method for joint analysis. The code is as follows

The resulting effect picture is as follows

Here, the FDR value of difference analysis is used to draw the picture, and other articles also use fold change to draw the picture, because it is better to judge the trend of differential expression according to the size of fold change, according to the FDR value can only judge whether there is a significant difference.

In the joint analysis of DNA methylation and gene expression profile, in view of the idea that DNA methylation inhibits gene expression, we usually pay attention to the sites with negative correlation between them, that is, methylation down-regulation and gene up-regulation, methylation-down-regulation gene up-regulation. In the image above, the sites with significant differences and negative correlation are marked with circles.

The joint analysis of DNA methylation and gene expression profile data can be easily realized by TCGAbiolinks, but the disadvantage is that its starburst plot is not drawn by the commonly used fold change.

At this point, I believe you have a deeper understanding of "how to use TCGAbiolinks for methylation and transcriptome data association". You might as well do it in practice. Here is the website, more related content can enter the relevant channels to inquire, follow us, continue to learn!

Welcome to subscribe "Shulou Technology Information " to get latest news, interesting things and hot topics in the IT industry, and controls the hottest and latest Internet news, technology news and IT industry trends.