I am new to qiime. I have 2 NGS runs of 50 and 43 human stool samples respectively. In one of the run (43 samples), after trimming primers, adaptors etc. I ran DADA2. However, I can retain ~60-80% of my reads per sample (which are flagged as non-chimeric). I have read different posts in this forum and realise that 60-80% is not that low, but should I play a bit with the --p-min-fold-parent-over-abundance parameters or continue with the retained reads? I am getting ~2300 sequence features from DADA2
You're right, 60%-80% is generally considered pretty good. Are you losing the majority of reads at the chimeric filtering step? Instead of adjusting the --p-min-fold-parent-over-abundance parameter, have you tried adjusting the trim and truncate parameters? These can significantly alter your % retained without tweaking the algorithm in a way that might light true positive chimeras through.
Hi Colin!
Yes! I am losing those reads in the chimera filtration step
I have used the following command
qiime dada2 denoise-paired
--i-demultiplexed-seqs NGS1mod-paired-end-demux-trimmedprimers.qza
--p-trunc-len-f 260
--p-trunc-len-r 220
--o-representative-sequences NGS1modtrimmed-rep-seqs-dada2.qza
--o-table NGS1modtrimmed-table-dada2.qza
--o-denoising-stats NGS1modtrimmed-stats-dada2.qza
And here is the qzv showing the the read quality after trimming of primers NGS1mod-paired-end-demux-trimmedprimers.qzv (319.8 KB)
Are my truncating parameters too strict?
I might give a try of classifying the sequences taxonomically with these 60-80% non-chimeric sequences and see the result, then decide accordingly. What do you think?
If you're losing all of the lost reads at the chimera filtering step then adjusting trim and trunc won't make a difference.
I might give a try of classifying the sequences taxonomically with these 60-80% non-chimeric sequences and see the result, then decide accordingly. What do you think?