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RnBeads

Tutorial

This site contains instructions and material for the workshop on "Analyzing Methylome Data using RnBeads" that was presented at the Epigenomics 2016 meeting. To get R and RnBeads set up for the tutorial and to retrieve the example data, please follow steps 1, 2 and 3 described below. Afterwards, feel free to experiment with the code contained in the downloaded data directory.

The presentation slides from the workshop are available here.

1. Download the Tutorial Scripts and Datasets

Download and extract the following file for the tutorial:

If you don't want to download the entire data package at once, you can also download the files individually:

2. Install R

Visit the CRAN website and download the version of R corresponding to your platform. Install R using the downloaded executable.

3. Install RnBeads and Ghostscript

You can find detailed instructions on how to install RnBeads and ghostscript following this link.

4. Analyze Your Methylome Data Using RnBeads

Follow the instructions provided in the presentation.

Example Reports

Reports for the examples discussed in the tutorial are available here:

Age Prediction Using RnBeads

Here, we provide instructions for how to use the epigenetic age prediction tool MethylAger. MethylAger was created as an RnBeads module and is therefore applicable to all DNA methylation assays operating at single base pair resolution. MethylAger contains several predefined predictors that were extensively evaluated for the most frequently used DNA methylation assays (e.g. 27K, 450K and RRBS). Depending on the type of the input data set, MethylAger decides which of these predictors is applicable. Additionally, a custom predictor can be created from the provided data set. Similar to the tutorial described above, an installation of R is needed. Then follow the instructions and enjoy the functions of the epigenetic age prediction tool MethylAger.

1. Download R Tutorial and Data Set

The data package, including the R tutorial and an example data set can be downloaded here (187 MB).

2. Use MethylAger

Follow the instructions provided in the R tutorial and analyze the example data set to get used to MethylAger.

Additional Information