More RADMeth strangeness: I finished…

More RADMeth strangeness:

I finished the Day 135 samples in methcounts and ran them through the RADMeth program a few different ways. First (not really, it just happened to be faster) I looked at DMRs in Low vs Super Low pH treatments. The results were… even stranger than yesterday’s for Day 10 stuff.

Day135-lowvslow

That’s the one DMR between the two samples. With… 0 methylation in all samples? I read a ton of messages on the methpipe boards and no one has encountered a similar experience, but it looked like most of them were doing mouse/human stuff with super robust genomes to reference, so maybe that’s our issue? Something like RADMeth assuming chromosomes in the genome and maybe large swaths of methylation to compare against. Just an idea? Still trying to figure out how to look at/display the pre-merged DML data from RADMeth.

I also looked at hypomethylation in the Day135 samples. Bed and IGV XML files are found here.

Might be some interesting results here, I’m working on a good way to compare Day10 and Day135 samples, Maybe just by scaffold, since in all likelihood there won’t be overlap reliable.

Day135-hypometh

Will update this with the R notebook once the Day 135 Ambient/Non-Ambient samples are finished running in RADMeth.

Kaitlyn’s Notebook: Moving on to Jupyter

I’ve been working with Bash the last couple of days. I’m running Bash on my Windows (which is capable of running a Linux based shell with the latest Windows update). There are definitely still some challenges. I found out you must change your home directory due to Windows file organization, but I am able to navigate my PC through Bash fairly effectively. I can now create directories and delete files, however I am still confused about utilizing pipes and filters in Bash so I’m still attempting to understand/work through this on Bash as well as opening files through the terminal. Most functions transfer over well from Linux to Windows except opening files. There is a patch from Windows as well as a few workarounds including running cbwin (another terminal) which runs through Bash. While it is a lot of work, running linux through Windows seems like the better option once I figure out these bugs because of the ability to use linux based commands which permits more actions.

While continuing to manage Bash, I’ve also downloaded Anaconda3 which includes Python 3.6 and Jupyter. I’m familiarizing myself with Jupyter (which I open through the GUI system until I figure out Bash). Once I am more comfortable with Jupyter, I will move onto running Blast so that I can run the oyster proteomics data through Blast and hopefully identify some proteins!