Double comfirm with the usage of Deblur -p-trim-length

[angelrica_kuan]

Hi, professional. I obtained the Demultiplexed file from sequencing company (Fastq.gz). I still a freshman in using QIIME2. Then, I would like to ask some questions in below:

Type: 16S amplicon sequencing rDNA
Primer: V3-V4 region, 341F - 805R

First, I have make a file in .tsv format according to instruction:

Second, I use the join-pairs method to join the reads and generate summary in below:
qiime vsearch join-pairs
--i-demultiplexed-seqs demux.qza \
--o-joined-sequences demux-joined.qza

Third, I use the Deblur method to denoise my sequences, trimming length is about 350. Is it reasonable for this length?
qiime deblur denoise-16S
--i-demultiplexed-seqs demux-joined-filtered.qza
--p-trim-length 350
--p-sample-stats
--o-representative-sequences rep-seqs.qza
--o-table table.qza
--o-stats deblur-stats.qza

Fourth, I curious that the calculation and process on table summary. Total frequency is calculated from which value? And, is it reasonable value for number of features (600) in my dataset.

qiime feature-table summarize
--i-table table.qza
--o-visualization table.qzv
--m-sample-metadata-file file-manifest14.tsv

Thank you for helping~~

[thermokarst]

Hi @angelrica_kuan!

@angelrica_kuan

Is it reasonable for this length?

Your primer pair is targeting a region that is ~460 nts long, so you are trimming off about 100 nts, which might impact taxonomic analysis.

@angelrica_kuan

Total frequency is calculated from which value

It is the total number of feature counts found across all samples. Let's use this feature table as an example:

The total frequency of features counts found here would be:

(84+24+11+0)+(1+2+0+0)+(73+44+10+25)+(198+176+30+2)+(2+1+0+0) == 683

Put another way, 5 features were found in 4 samples 683 times.

Hope that helps!

[angelrica_kuan]

Thanks for your help!! Its easy to understand !!