Update - 3-24-15

Update 3/24/15:

• I have now finished running Bismark on all my data (genome prep, read mapping, and methylation extractor). I had some issues last week, since the program failed and I wasn't able to find out for several days, since it takes quite a while for it to begin running after being submitted. However, I was able to get everything run through iPlant. Finally.

• Based on the output of the methylation extractor script I'm having a hard time conceptualizing how to parse the output to get what I want, regions of hypermethylation. Most discussion I've found online regards finding hypomethylation. It's probably a good idea to load the file into a genome browser of some sort and check some individual loci. Advice would be appreciated.

• I suppose the most important thing I can do is find a way to find differential methylation. I think that writing a Python script to parse the output of Bismark is a bit beyond my abilities right now. One thing I did find, however, was this R package called Methylkit.

To-do This Week

1. Figure out how to load this data into some sort of genome browser (parse the methylation extractor output and find %methyl-C at each C - python or R). Due date: 3/27/15
2. Install Methylkit in R. Due date: 3/26/15
3. Download all my analyzed data from the iPlant data store to use with Methylkit. Due date: 3/25/15
4. Run Methylkit and find hypermethylated regions. Tentative Due date: 3/31/15