Thank you so much for the fantastic QIIME2 pipline, it brings me to amplicon world.
My name is Yilang Wang, a current PD. fellow of CAS, IUE, China.
I'm now working on some environmental bacterial amplicon data amplified by different primer sets (V3-V4, V4, V4-V5).
Previously, I have processed these data respectively under pipeline like: "primer removing" >> "PE data joining" >> "quality-filter q-score" >> "denoising via deblur"; After denoising, I merged the rep-seqs and feature-tables, finally I got about 55000 ASVs and got about 5000 unique taxonomic assignments via silva database.
At this step, I realized that there must be some ASVs that may biologically amplified by DNA templates of the same specie/organism though amplified by different primer sets. The feature-table merging was not able to really merge ASVs from the same specie/organism, and may even bring spurious alpha diversity and fake beta diversity on ASVs level, regardless of effects of different primer-sets, sampling methods, library construction, sequencing method/depth & etc.
Therefore, I am puzzled to know if I can go to further analysis with the merge feature-table on ASVs level. Or I just can go further with table on a taxonomic level (a merged feature-table collapsed on species level under the same silva database assignment).
Now, I also puzzled if two assumed feature-tables, which are amplified with the same primer-set, such as V4(515F/806F), but denoising with different deblur parameters, such as one table with --p-trim-length 130 and --p-left-trim-len 0 and the other one with --p-trim-length 120 and --p-left-trim-len 10, will give me the really merged ASVs from the same species/organisms.
Qiime2 website (Fecal microbiota transplant (FMT) study: an exercise — QIIME 2 2022.2.0 documentation' ) declares that "
denoise-single are directly comparable (in this case, the feature id is the md5 hash of the sequence defining the feature)."
I did some web searches, benjjneb suggested to merge the feature-table after normal DADA2 denoising pipline following by ASVs sequences trimming by primer-set of shared amplified region (Comparing data from two Illumina chemistries (16S amplicon sequencing) · Issue #509 · benjjneb/dada2 · GitHub). joey711 raised a warning (merge_phyloseq of two different phyloseq objects (non matching OTU labels) · Issue #508 · joey711/phyloseq · GitHub).
Now, I am switching to use cutadapt to cut the shared amplified region (V4 by 515F/806R for V3-V4, V4, V4-V5), before deblur denoising. However, I run into another problem that about a half of q-score artifacts seemed to have a 0-246/253/254nt trim length, the other seemed to have longer (>254nt) trim length. And I don't know if the cutadapt step gives the right shared amplified V4 rigeon. And I am also concerned if further denoising and merging will give the truely merged ASVs.
fdp.02s.qza.qzv (301.4 KB)
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fdp.16pjs.qza.qzv (307.6 KB)
fdp.23s.qza.qzv (302.3 KB)
(I choose deblur as it does not require pool sequencing data, while DADA2 does)
I hope to receive some advice or comment from you.