Demux Error: No sequences were mapped to samples


I am just starting to figure out QIIME2 and I am running into some problems with processing some older data (sequenced in 2014). I have fastq files for the barcodes and sequences as well as a map that was originally used to process the data in QIIME. When I try to demutiplex the files using the following code,

qiime demux emp-single \
> --i-seqs emp-single-end-sequences.qza \
> --m-barcodes-file map.txt \
> --m-barcodes column BarcodeSequence \
> --o-per-sample-sequences demux.qza \
> --o-error-correction-details demux-details.qza

I get the following error (which shows up in this forum post),

Plugin error from demux:

  No sequences were mapped to samples. Check that your barcodes are in the correct orientation (see the rev_comp_barcodes and/or rev_comp_mapping_barcodes options).

Debug info has been saved to /tmp/qiime2-q2cli-err-9zkbol2u.log

In the other post about this error, the user had their sequences and barcodes mixed up, but I do not think that is the case with this data. If it is some sort of formatting issue with my files, how can I fix it? I have put the .qza file and the map in the google drive link below:

If anyone can help with this I would be grateful!

Hi @MartinEarle,
How did you originally process these data with qiime 1? As the message recommends, you should try the rev_comp_barcodes and/or rev_comp_mapping_barcodes options.

Also use the --p-no-golay-error-correction option if your barcodes are not Golay barcodes.

Try unzipping your barcodes fastq data and searching for some of your barcodes directly to make sure they are in the orientation and position you expect.

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Hi @Nicholas_Bokulich,

It took me a few days to get around to this as I only have access to QIIME2 from a certain computer, but it turns out that the barcodes are not GOLAY, thanks for suggesting this! In the future I will spend more time trying different options with the import commands!

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Hey @MartinEarle, just stumbled on this post:

I love the “go-get-it” attitude - thanks! In general, I think this is a great strategy, but, in the case of “raw” data, I just want to caution you that often it is best to just ask the sequencing center, rather than guessing. Sometimes your guesses might look like they are working, but in fact, contain some fatal flaw. Just my two cents, not an “official” opinion.


Thanks for the advice! With future data I will be sure to get this information before starting analysis.

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