Dada2 while comparing microbiome in highly and low areas of enrichment?

My apologies in advance - I am new to bioinformatics and QIIME2 (v2023.2).

I am working on a project where I am trying to compare and correlate microbiomes from highly enriched regions such as feces/intestines to regions with much low levels of the microbiome (think lungs, certain tumors, etc.). I performed MiSeq 2x250bp for the V4 region.

I performed primer trims and truncated low quality regions of the sequences, but I am getting super low frequencies.

QZV after Demultiplexing:
paired-end-demux0.qzv (319.2 KB)

QZV after Trimming Primers (505F and 806R):
primer-trimmed-demux0.qzv (325.6 KB)
Primertrimming.txt (243.3 KB)

Post DADA2:
denoising_stats.qzv (1.2 MB)
table.qzv (418.1 KB)
rep_seq.qza (24.9 KB)

I performed DADA2 denoising on q2galaxy server because of a slow computer, but my truncation length was F: 230 and R: 160.

What would be your suggestions for this sort of data analyses? A lot of my samples of interest (H1, H2, H3, H4) have 0 frequencies. Any help would be appreciated. Thanks!

Hello @macrobiome,

There is a lot going on here, but the quickest bang for your buck will be to adjust your forward truncation length lower. From the interactive quality plot tab you can see that the median forward read length is 230 nts. Setting your forward truncation length to 230 thus discards 50% of your reads right off the bat. Try 225 or so.

It also looks like you are safe to extend the reverse truncation cutoff to about 220. Try changing these parameters and rerunning, and we can discuss from there.



Thank you so much! These are the results I got. I think they look much better?
rep-seqs-dada2-ec2.qzv (347.4 KB)

Hello @macrobiome,

If you also share the denoising stats file we'll be better able to tell how things went this time. But glad to hear that things are looking better!

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Yes! Please find below. Appreciate your insight and help!

stats-dada2-ec2.qzv (1.2 MB)

Hello @macrobiome,

These look like solid results to me, you're safe to move forward with these outputs.

Please note that, unfortunately, around half of your samples got sequenced with little depth. There is nothing you can do about this (except re-sequence), but don't expect great things from those analysis wise.


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