Migrating reads QC pipeline from QIIME 1.9 to QIIME 2

Hi,

I’m Restu, a Ph.D. student from UQ, also a newbie in microbiome analysis. Hopefully, this question is valid.

Currently, I’m still using QIIME 1.9, but I’m planning to to migrate my pipeline to QIIME 2 per this forum suggested. (al so interested to try DADA2)

Just a little bit confused when in the QC steps. OK this is my data:

my data is demultiplexed cassava paired end :
I guess I’ve read how to import it in the importing tutorials, but the problem is, the imported files still don’t have the sample name…

I usually do this in qiime 1:
split_libraries_fastq.py -i J612_S48_L001/fastqjoin.join.fastq -o sample_reads/R0078 --sample_ids R0078 -q 19 --barcode_type ‘not-barcoded’

is there any way to assign the sample name during the “import” like split_libraries_fastq.py’s --sample_ids ???
And how to make the imported file ready for DADA2 ?

Thank you very much,

Restu

Hi @Restuadi!

Welcome to the QIIME 2 Forum! Since it sounds like you’re new to QIIME 2, I highly recommend working through the Getting Started guide first, which will show you how to import data and get started with analyses such as denoising with DADA2.

In order to import your paired-end demultiplexed Illumina data and denoise with DADA2, you’ll want to perform the following steps:

  1. Avoid joining your paired-end reads prior to denoising with DADA2. DADA2 works best with unjoined reads, and it will join the reads for you while denoising. The following steps assume that you have not already joined your reads (this is different from the typical QIIME 1 workflow for paired-end data).

  2. Import your unjoined paired-end sequence data using one of the “fastq manifest formats” described in this section of the Importing Tutorial. For your data, you’ll likely want to use the PairedEndFastqManifestPhred33 format, assuming your sequence quality scores are encoded as Phred 33 (if not, there is a corresponding fastq manifest format for Phred 64 quality scores).

    By using one of the “fastq manifest formats”, this is your opportunity to tell QIIME 2 what your sample names are!

  3. After importing your paired-end reads into a .qza file (this is a QIIME 2 Artifact), you can use qiime dada2 denoise-paired to denoise and join your sequence data. You’ll want to use qiime demux summarize on that .qza file first in order to inspect the quality scores and choose appropriate parameters for dada2 denoise-paired. Once denoise-paired is finished, you’ll have a feature table and representative sequences, which you can use for downstream analyses such as alpha/beta diversity.

Let us know how it goes!

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Thank you very much, its working…

Still waiting for any result, DADA2 certainly takes some time…

Great to hear!

Have you tried running DADA2 in multi-threaded mode? The --p-n-threads option controls the number of threads, and by default only a single thread is used.

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