After a meeting on this project yesterda, we decided to try a few things to continue with various approaches to assessing the metagenome. One of the approaches is to run BLASTx on the individual water sample MEGAHIT assemblies from 20190327 and obtain taxonomy info for them, so that’s what I did here.
Earlier today, we received the additional G.gigas sequencing data from Genewiz. Wanted to run through FastQC again and get an updated report for each data set. Admittedly, it probably won’t look much different from the initial FastQC run on 20190415, due to the fact that the additional sequencing was simply appended to the previous data. Since FastQC examines a subset of the data in each file, I’d fully expect the FastQC report to look the same. However, we’ll have a greater number of sequences in each file. This should, in turn, increase the number of reads retained after quality trimming.
The FastQC analysis of the intitial data we received from Genewiz (on 20190408)showed consistent failures in the “Per Tile Sequence Quality” for all of Roberto’s Crassostrea gigas sequencing. After discussing with Genewiz, they offered to generate an additional 25% reads for each of those libraries.
After the success we had isolating RNA using the Quick-DNA/RNA Microprep Plus Kit (ZymoResearch), Steven had me isolate RNA from a list of ~117 samples. Of that list, I was able to find 66 crab hemolymph pelleted RNAlater samples. The “missing” samples were most likely previosly used by Grace during our various attempts to get some usable RNA out these.
A while ago, Steven tasked me with assessing some questions related to the sequencing coverage we get doing MBD-BSseq in this GitHub issue. At the heart of it all was really to try to get an idea of how much usable data we actually get when we do an MBD-BSseq project. Yaamini happened to have done an MBD-BSseq project relatively recently, and it’s one she’s actively working on analyzing, so we went with that data set.
Nearing the end of this quick metagenomics comparison of taxonomic differences between the two pH treatments (pH=7.1 and pH=8.2). Previously ran:
Continuing with a relatively quick comparison of pH treatments (pH=7.1 vs. pH=8.2), I wanted to run gene prediction on the MEGAHIT assemblies I made yesterday. I ran MetaGeneMark on the two pH-specific assemblies on Mox. This should be a very fast process (I’m talking, like a couple of minutes fast), so it enhances the annotation with very little effort and time.