Continuing working on the manuscript for this data, Emma wanted the number of reads aligned to each gene. I previously created and assembly with genes/proteins using MetaGeneMark on 20190103, but the assemby process didn’t output any sort of stastics on read counts.
Shelly asked that I re-run the primer design pipeline that Kaitlyn had previously run to design a set of reproduction-related qPCR primers. Unfortunately, Kaitlyn’s Jupyter Notebook wasn’t backed up and she accidentally deleted it, I believe, so there’s no real record of how she designed the primers. However, I do know that she was unable to run the EMBOSS primersearch tool, which will check your primers against a set of sequences for any other matches. This is useful for confirming specificity.
Ran some qPCRs on some other primers on 20200723 and then Shelly has asked me to test some additional qPCR primers that might have acceptable melt curves and be usable as normalizing genes.
Can’t remember where it was discussed (probably lab meeting), but I created a GitHub Issue to add all of geoduck RNAseq data to NCBI Short Read Archive (SRA). Anyway, got all the remaining RNAseq data uploaded to the NCBI SRA and organized into the correct BioSamples and BioProjects.
Decided to finally take the time to methodically extract data from our metagenomics project so that I have the tables handy when I need them and I can easily share them with other people. Previously, I hadn’t done this due to limitations on looking at the data remotely. I finally downloaded all of the RMA6 files from 20191014 after being fed up with the remote desktop connection and upgrading the size of my hard drive (5 of the six RMA6 files are >40GB in size).