Last week, I hopped over to Rhode Island for the Functional Re-annotation of Oyster Genomes with Epigenetic Resources (FROGER) workshop. Our goals were to 1) use epigenetic resources to annotate the C. virginica genome and 2) compare whole genome bisulfite sequencing (WGBS), reduced representation bisulfite sequencing (RRBS), and MBD-BS methods for a single C. virginica sample. We expected to write a methods comparison paper while we were there, but data turned out to be really poor-quality for making any useful comparisons.
To contribute to the first goal, I created a long non-coding RNA track with associated exons. I used code I’d been working with for my own analyses and created this Github-friendly Markdown document with my code. Once I created the lncRNA track, I helped the groups calculating CpGoe ratios for genes, coding sequences, exons, chromatin-associated proteins, 1000 kb windows throughout the genome. I worked with the code this Markdown document and in this
gannet directory. I was able to test the different code chunks and run most of the pipeline with all five categories. At one point, I ran into an issue trying to use
join functions not available on OSX. Sam suggested I download Homebrew and specify
gjoin. This worked!…but it also caused an issue with
gawk as I was generating sample-specific CpGoe counts for genes and windows while testing the concatenation code with the CAP tracks. I wrestled with this for a full day until I realized the code still worked when I changed
awk! Shelly suggested I run the concatenation code with the CAP tracks on
mox, so she set that up for me. Hopefully, I can finish the rest of the concatenation on
mox in before I leave for Friday Harbor.
While I was toying with CpGoe code, I was also able to participate in discussions about genome feature tracks and
methylKit parameters. Jon Puritz posted his code for creating genome feature tracks here. He used
intersectBed to create an intron track, which is what Sam suggested in this issue. I’m going to use his code to finalize my C. virginica tracks. When mapping the data we did have to the C. virginica genome, Mac pointed out that the alignment stringency I set for my samples was potentially too loose. She explained that looking at CHC and CHG methylation rates was important in addition to mapping efficiency. Shelly and I tried to figure out why we both decided on
L,0,-1.2 instead of
L,0,-0.6 (what FROGER used for mapping), but we couldn’t remember our conversations. We’re going to bring this up at the next lab meeting.
I’ve never been a part of a working group before, so FROGER was a great experience! It was interesting to see how other people approach similar analyses and learn from a group of experts. I’m looking forward to getting more data and continuing a virtual FROGER working group to conduct the method comparisons.