I have Illumina 2x150bp paired end sequences .fastq sequences. These are not joined. These sequences are already ready to go, they are denoised, quality filtered, etc. I need to by-pass the Dada2/Deblur steps bc this isn’t necessary. What I am trying to do is eventually get taxonomic information using the SILVA_132 database.
In Qiime1 I used to run the following command:
pick_open_reference_otus.py -i seqs.fna -p SILVA_123_db.parameters.txt -r SILVA_128_QIIME_release/rep_set/rep_set_all/97/97_otus.fasta -o M40A_silva123_out
I am trying to run the equivalent in Qiime2
I followed this for import: https://docs.qiime2.org/2017.12/tutorials/importing/#fastq-manifest-formats
following the prompts under: “Fastq manifest” formats"
Here is my command:
qiime tools import --type SampleData[PairedEndSequencesWithQuality] --input-path manifest_test.txt --output-path demux.test.qza --source-format PairedEndFastqManifestPhred33
This generated a demux.test.qza.
From here, I found this suggestion to by-pass DADA2:
This was the ‘general’ CLI suggestion:
qiime vsearch dereplicate-sequences
But - as you can see, I need a ‘table’ to pass to the --o-dereplicated-table command as it gives me an ‘Error: Missing option: --o-dereplicated-table’ if I don’t pass this flag. Only way I seem to find to create this table is to go through the DADA2 steps, which is unnecessary for my data set.
May I ask if there are any other options on how to generate a rep-seqs.qza?
Next, I wanted to then run the following command after I generate the rep-seqs.qza:
qiime feature-classifier classify-sklearn
-I found the silva-132-99-nb-classifier.qza here: Silva 132 classifiers
From here, I can attempt to move forward.
Many thanks for your advice!!