Hi,

Thanks a lot for the info. I assumed as much for the taxonomic metadata (I've observed differences at the genus level even between sequence names and GB entries). I'm actually looking to iteratively search the entirety of the refseq_genomic DB. I devised a hacky workaround using a python script. I pulled all of the sequences for refseq from genbank and and split them into individual files named by sequence name. Then I os.listdir()'d all the sequences and selected only those that fit my criteria for subspecies (regex'd from the filename). Then I made a blastable db from this list of sequences (after compiling them back to a single .fsa file) that I then used for querying.

Probably not the most comprehensive way to do it, but it yielded a lot more usable data from a much smaller data set than I was previously working with. I'm going to have to go through the results of my data-crunching to ensure I used the right sequences, but I was able to shorten the number of sequences I was working through from >6000 (mitochondrial sequences only) to <300.