Cutadapt and sequence classification.

Hello. Long time unregistered reader, first time poster.

I hope i chose the most appropriate category. Also, i`m only asking these questions because if failed to find the answers elsewhere online.

  1. Can the ‘qiime cutadapt trim-paired’ plugin handle degenerate primer bases. For example: can i provide the whole 341F primer (CCTACGGGNGGCWGCAG) for the ‘–p-adapter-f’ parameter or should i only provide the part with no degenerate bases (CCTACGGG)?

  2. Kind of a similar question the the first one. Can the ‘qiime feature-classifier extract-reads’ plugin handle primers with degenerate bases in them or should i provide only the part of the primer with no degenerate bases? Extracting from ‘SILVA 132’ database.

  3. Should one cluster the feature table to ‘–p-perc-identity 97/99’ using ‘qiime vsearch cluster-features-de-novo’ before using the ‘qiime feature-classifier classify-sklearn’ plugin? What could be the advantages/disadvanges of doing so? Feature table prepared with ‘DADA2’.

Thank you in advance!

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Welcome @rsak-384!

Sure — here are some relevant parameters for you:

  --p-error-rate PROPORTION Range(0, 1, inclusive_end=True)
                          Maximum allowed error rate.           [default: 0.1]
  --p-match-read-wildcards / --p-no-match-read-wildcards
                          Interpret IUPAC wildcards (e.g., N) in reads.
                                                              [default: False]
  --p-match-adapter-wildcards / --p-no-match-adapter-wildcards
                          Interpret IUPAC wildcards (e.g., N) in adapters.
                                                               [default: True]

Yes, see here:

If you’ve used dada2 to denoise, there is no need to cluster into OTUs. I recommend checking out the “overview” tutorials at tutorials.qiime2.org for some notes on advantages and disadvantages, and even better is probably the community discussions… see some OTU + denoising topics here:
Frequent Questions and "Best of the QIIME 2 Forum"

I hope that helps!

2 Likes

Thank you very much!

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