PacBio hifi reads data analysis through qimme2


I wanted to know can we use the QIIME2 pipeline to runPacBio hifi reads data. I have received the data files in following format: demultiplex.bc1005--bc1033.hifi_reads.fastq.gz

Where can I find the command line to run this project using QIIME2 (via Terminal Mac). I did look at denoise-ccs: Denoise and dereplicate single-end Pacbio CCS — QIIME 2 2022.2.0 documentation but unable to locate tutorial and command line.


Hi @rr220,

Thanks for reaching out!

We don't have a designated tutorial for this specific method, but the documentation that you linked is exactly what I'd recommend reading over in order to better understand how this method works. It has details on the input type, required parameters, and what your expected output should be.

I would give that another look over, and let us know if you have any specific questions regarding running that or any issues you run into along the way!

Cheers :lizard:

Thank you so much for your response. I have following questions:

  1. Is this integrated with QIIME2? or can only be done in R?
  2. Can I use regular QIIME2 pipeline with PacBio for get diversity output?

Thank you so much!

I have one more query: I found this link which mentions QIMME2 can be used for Pacbio reads. Is this information accurate.

Hi @rr220,

The original link that you provided is from our documentation - what this means is that the command qiime denoise-ccs is available for use within the QIIME 2 Framework. So as long as you have QIIME 2 installed on your machine, you will be able to utilize this command on single end Pacbio CCS reads.

Yes - from the documentation linked above, you'll see that the input type for qiime denoise-ccs is single-end demultiplexed PacBio CCS sequences, and the output types will be as follows:

  --o-table ARTIFACT FeatureTable[Frequency]
                         The resulting feature table.
  --o-representative-sequences ARTIFACT FeatureData[Sequence]
                         The resulting feature sequences. Each feature in the
                         feature table will be represented by exactly one
  --o-denoising-stats ARTIFACT SampleData[DADA2Stats]

Hopefully this helps provide some clarification - let us know if you have any additional questions!

Cheers :lizard: