Cutadapt trim iontorrent data

[bahti_yil (Bahtiyar Yilmaz)]

Dear Matthew,

I have an Iontorrent 16S data within a single fastq file for 72 samples. I followed the @shwane' s advice and managed to come until the generation of trimmed-seqs.gza file and here are the command line that I have run since the beginning.

qiime tools import --type MultiplexedSingleEndBarcodeInSequence --input-path WildMice_Chip1.fastq.gz --output-path multiplexed-seqs.qza

qiime cutadapt demux-single --i-seqs multiplexed-seqs.qza --m-barcodes-file shwanesample-metadata.tsv --m-barcodes-column BarcodesSequence --p-error-rate 0 --o-per-sample-sequences demultiplexed-seqs.qza --o-untrimmed-sequences untrimmed.qza --verbose

qiime cutadapt trim-single --i-demultiplexed-sequences demultiplexed-seqs.qza --p-front ATTAGATACCCYGGTAGTCC --p-error-rate 0 --o-trimmed-sequences trimmed-seqs.qza --verbose

qiime demux summarize --i-data trimmed-seqs.qza --o-visualization trimmed-seqs.qzv (Please see the gzv file in attachment)

I'd like to generate the rep-seqs.qza and table.gza that I can carry out with analysis. However, I couldn't figure it out from the command line. Can you guide me for me that?

Thanks a lot.

Best,
Bahti

trimmed-seqs.qzv (299.0 KB)

[bahti_yil (Bahtiyar Yilmaz)]

Actually I managed to follow on analysis with following commands until the taxonomy part. Here is I need help to create taxonomy.gza file.

First when I run qiime feature-classifier classify-sklearn --i-classifier gg-13-8-99-nb-classifier.qza --i-reads rep-seqs_120.qza --o-classification taxonomy.qza

It says ValueError: gg-13-8-99-nb-classifier.qza was created by ‘QIIME 2019.1.0’. The currently installed framework cannot interpret archive version ‘5’. That’s fine because I am using qiime2-2018.8-1 and assuming that this is the problem.

Then I decided to create gza file myself from 97% OTU GG database.

singularity exec /software/singularity/containers/qiime2-2018.8-1.debian9.simg qiime tools import
–type ‘FeatureData[Sequence]’
–input-path 97_otus.fasta
–output-path 97_otus.qza

singularity exec /software/singularity/containers/qiime2-2018.8-1.debian9.simg qiime tools import
–type ‘FeatureData[Taxonomy]’
–input-path 97_otu_taxonomy.txt
–output-path ref-taxonomy.qza

It says
There was a problem importing 97_otu_taxonomy.tsv:
** 97_otu_taxonomy.tsv is not a(n) TSVTaxonomyFormat file**.

And it doesn’t accept the –source-format HeaderlessTSVTaxonomyFormat to be added into commands as shown here https://docs.qiime2.org/2017.7/tutorials/feature-classifier/.

Basically I need create classifier to run qiime feature-classifier classify-sklearn commands. My sequence is from Iontorrent and it is for V5-V6 region.

Thank you very much for your help.

Best wishes,
Bahti

[Nicholas_Bokulich]

@bahti_yil

It says ValueError: gg-13-8-99-nb-classifier.qza was created by ‘QIIME 2019.1.0’. The currently installed framework cannot interpret archive version ‘5’. That’s fine because I am using qiime2-2018.8-1 and assuming that this is the problem.

I recommend installing the latest version of QIIME 2. It looks like you are using different old versions of the software and even older versions of the documentation.

@bahti_yil

And it doesn’t accept the –source-format HeaderlessTSVTaxonomyFormat to be added into commands as shown here Training feature classifiers with q2-feature-classifier — QIIME 2 2017.7.0 documentation.

That's because you are looking at an archived version of the documentation that is almost 2 years old. That parameter is now called --input-format I believe.

@bahti_yil

Basically I need create classifier to run qiime feature-classifier classify-sklearn commands. My sequence is from Iontorrent and it is for V5-V6 region.

If you have version 2019.1 installed, you can use one of the full-length 16S classifiers from the QIIME 2 site.

@bahti_yil

There was a problem importing 97_otu_taxonomy.tsv:
** 97_otu_taxonomy.tsv is not a(n) TSVTaxonomyFormat file**.

Try using the updated parameter name I mentioned above — if that does not work you should manually inspect the file to see what the problem is.

Good luck!

[bahti_yil (Bahtiyar Yilmaz)]

Thanks a lot Nicholas. I did as you said and it worked beautifully. Cheers,
Bahti