Differential Methylation in the Kitchen Finally re-getting around to examing our MBD-array data in the context of RNA-seq data. Briefly we have three oysters that were heat shocked with samples taken prior to, and following. An MBD-array experiment was carried out where for each oyster we have information on 50bp genome features (selected probes on the array) whether the region was hypomethylated, hypermethylated or did not change. Following heat shock approximately 10k differentially methylated features (value >/= 1.8) were identified in all oysters. For all oysters a majority of the features were hypomethylated. Specifically, for oysters #2, #4, and #6 the number of hypomethylated features was 7224, 6560, and 7645, respectively. When only features were considered where at least 3 adjacent probes were also differentially methylated the number of features (merged) for oysters #2, #4, and #6 was 112, 58, and 62, respectively. A majority of these features were hypomethylated (108, 48, and 53, respectively) Oyster | Hypo-methylated | Hyper-methylated | Hypo-3plus-merged | Hypo-3plus-merged --- | --- | --- | --- | --- 2 | 7224 | 2803 | 108 | 4 4 | 6560 | 3587 | 48 | 10 6 | 7645 | 4044 | 53 | 9 The files with differentially methylated region (DMRs) as defined by value >/= 1.8 are name as `2014.07.02.6M_sig.bedGraph` and have the following format (ie `head` output) ``` track type=bedGraph name="6M_sig" description="6M_sig" visibility=full color=100,100,0 altColor=0,100,200 priority=20 scaffold1 54599 54654 -1.38187662416007 scaffold1 162129 162191 1.85685479189849 scaffold1 163536 163586 -1.15032035523765 scaffold1 172654 172714 1.33561271440876 scaffold1 174287 174343 -1.62903936976887 scaffold1 178075 178128 1.42323539316231 scaffold1 178685 178740 1.30886296151914 scaffold1 184271 184330 -1.20699853451878 scaffold1 184661 184715 -1.61107459826899 ``` As part of the data provided by the core facility we also obtained genome feature files where there were three or more adjacent signficant probes. The naming structure is `2014.07.02.4M_Hypo_3plusAdjactentProbes.gff` with the file format: ``` scaffold100 804406 804960 scaffold1018 367127 367319 scaffold1018 367618 367674 scaffold1077 401205 401534 scaffold12 244080 244376 scaffold1324 356489 356781 ``` To merge these adjacent features I ran `bedtools merge`. For example ``` bedtools merge -d 100 -i \ ./data/2014.07.02.colson/genomeBrowserTracks/threeOrMoreAdjacentSigProbes/2014.07.02.2M_Hypo_3plusAdjactentProbes.gff \ > ./analyses/2M_3plusmerge_Hypo.gff wc -l ./analyses/2M_3plusmerge_Hypo.gff ``` These values are refered to in the above table as Hypo(Hyper)-3plus-merged and the file format: ``` scaffold1737 485256 485565 scaffold1894 222981 223032 scaffold1894 223601 223653 scaffold1894 224777 224838 scaffold392 326519 326818 scaffold433 204898 205194 scaffold544 44676 44853 scaffold544 45028 45086 scaffold854 353009 353316 ``` filenames: `6M_3plusmerge_Hypo.bed` This screenshot shows the different file types IGV_1A97B149.png It is important to not that the `plusAdjactentProbes.gff` files were identified scrictly based on adjacent prove regardless of distance, where the `merged` files are spatially constrained. For now I will treat the 6 bed files shown above as the canonical DMRs, for analysis purposes, but I imagine this will change. Hopefully if my IPython notebooks are set up right, this should not be a problem. These 9 files are available [here](http://owl.fish.washington.edu/halfshell/index.php?dir=2015-02-dmr-canonical%2F) ``` 2014.07.02.2M_sig.bedGraph 4M_3plusmerge_Hyper.bed 2014.07.02.4M_sig.bedGraph 4M_3plusmerge_Hypo.bed 2014.07.02.6M_sig.bedGraph 6M_3plusmerge_Hyper.bed 2M_3plusmerge_Hyper.bed 6M_3plusmerge_Hypo.bed 2M_3plusmerge_Hypo.bed ``` IPython notebooks used to get here [are here](http://nbviewer.ipython.org/github/sr320/paper-Temp-stress/tree/master/ipynb/).