How can I set the parameters of feature-classifier extract-reads ?

Hi all,

I set the denoise-paired parameters as follows according to qc plot.

qiime dada2 denoise-paired
--i-demultiplexed-seqs Sample1_Results/Trimming/Sample1_trimmed_adapters.qza
--p-trunc-len-f 290
--p-trunc-len-r 255
--p-trim-left-r 55
--p-n-threads 24
--o-representative-sequences Sample1_Results/Denoising/Sample1-rep-seqs.qza
--o-table Sample1_Results/Denoising/Sample1-table.qza
--o-denoising-stats Sample1_Results/Denoising/Sample1-stats.qza

Then, I try to set the parameters of qiime feature-classifier extract-reads for SILVA database. HOwever, I dont clearly understand how can I set these parameters. FOr example, I used SILVA database and set its paramters as follows:
qiime feature-classifier extract-reads
--i-sequences Sample1_Results/Import_Database/Sample1_99_otus.qza
--p-trunc-len 255
--p-trim-left 55
--p-min-length 200
--p-max-length 800
--o-reads Sample1_Results/Import_Database/Sample1-ref-seqs.qza

While my minimum amplicon length is 200 maximum amplicon length is 800. I used V3_f and V4_r for f-primer and r-primer parameters. But I am not sure how to be trunc-len and trim-left parameters. I know that the minimum amplicon length should be equal or less than (trunc-len - trim-left). During dada2 denoise-paired, I set the parameters to 290, 255 and 55 for trunc-len-f, trunc-len-r and trim-left-r 55, respectively. Now, during qiime feature-classifier extract-reads command, How should I set trunc-len and trim-left parameters?

Hi @elifi,
What is your goal of running qiime feature-classifier extract-reads?
I currently am not quite sure the goals of your analysis. Are your sequences longer then the v3-v4 region? When you were preparing the data for sequencing, which region did you target?

1 Like