Using ENCODE methylation data (RRBS) in R

[This article was first published on Recipes, scripts and genomics, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

ENCODE project has generated reduced-representation bilsulfite sequencing data for multiple cell lines. The data is organized in an extended bed format with additional columns denoting % methylation and coverage per base. Luckily, this sort of generic % methylation information can be read in by R package methylKit, which is a package for analyzing basepair resolution 5mC and 5hmC data.

The code snippets below show how to read RRBS bed file produced by ENCODE. But, let’s first download the files.


Unfortunately, methylKit currently can not read them directly because the track definition line causes a problem. It should be deleted from each bed file. Ideally, methylKit should be able to skip over lines (this issue should be fixed in later versions)
For now, we have to use some unix tools to remove the first lines from the bed files. You run the code below in your terminal. This set of commands will delete the first line from every *.gz file in the directory so be careful.
for files in *.gz
  gzip -dc "$files" | tail +2 | gzip -c > "$files".tmp
  if [ "$?" -eq 0 ]; then
    mv "$files".tmp "$files"
Now we can read the files using methylKit. The pipeline argument defines which columns in the file are corresponding to chr,start,end,strand, percent methylation and coverage:
You can also read multiple files at a time:

Since we have read the files and now they are methylKit objects, we can use all of the methylKit functionality on these objects. For example, the code below plots the distribution of methylation % for covered bases.
getMethylationStats(obj[[1]], plot = TRUE)
You can check the methylKit vignette and the website for the rest of the functionality and details.

To leave a comment for the author, please follow the link and comment on their blog: Recipes, scripts and genomics. offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)