I’m currently working on the analysis of arbuscular mycorrhizal fungi (AMF) using the 18S rRNA gene region (primers AMV4.5NF and AMDGR). I have already completed denoising with DADA2 and obtained my ASV representative sequences. I would now like to assign taxonomy using the MaarjAM database, which is specific to AMF.
However, I’m having trouble locating a QIIME2-compatible version of the MaarjAM database. Specifically, I’m looking for:
A reference sequence FASTA file
A corresponding taxonomy mapping file
Or ideally, a pre-trained .qza classifier for use with qiime feature-classifier classify-sklearn
I’ve searched the MaarjAM website (http://maarjam.botany.ut.ee/) but couldn’t find clear download options for the full reference database in a format suitable for QIIME2.
Questions:
Is there a QIIME2-compatible version of the MaarjAM database available for public use?
Has anyone successfully trained a classifier using this database for AMF taxonomy assignment?
If not, could someone kindly guide me through the process of converting the MaarjAM database into QIIME2 format?
You can download the MaarjAM databases in QIIME2-compatible formats from here. After downloading, you'll need to import the sequences and taxonomy files into QIIME2, then train a classifier. Your commands will look something like this:
I tried using this database once for a test sequencing run, but ran into some issues with the primers, so I didn’t get very far. Still, I hope this is helpful for you!
I’ve followed your instructions and it seems everything worked well. I was able to assign taxonomy to about 28K features using the 18S rDNA QIIME release (2021) from MaarjAM. While no species-level assignments came through (only up to genus level), everything else looks perfect.
However, one thing that’s been bothering me is the speed—the entire taxonomy assignment step finished within a minute, which felt unusually fast. Below are the exact commands I used:
Zooming out a little, every Qiime2 command should tell you if it fails. I also inspect the output files with view.qiime2.org to see more information about how the command ran.