I have encountered an obstacle while training the Greengenes classifier to more accurately predict taxonomy of my sequencing reads. Any help would be highly appreciated, thanks !
So, I realize that in the “qiime feature-classifier extract-reads” command, I need to provide the forward and reverse primer (without fluidigm or barcodes; only the biological sequence). I enquired this info from the sequencing centre-they send me a list of 515f/806r primers, but they use a staggered primer sequences. They have, in total, 4 sets of primers.
So here is what I have thought: I generate a ref-seqs.qza file individually for all 4 sets, and then merge the .qza files to create a composite .qza file which I train using the Native Bayesian approach.
Am I correct in my thinking? Or is there an easier alternate way? Thanks!