How do I import interleaved fastq files?

I am starting with pared-end interleaved fastq files that are demultiplexed (so, 1 file per sample with forward and reverse reads in 1 file). How would I go about importing this data to use with dada2 or deblur? The tutorials only seem to cover paired-end reads that are in separate r1 and r2 files.

Hey @gho,

Sorry for the delayed response!

Would you be able to provide a sample of the first couple of sequences in one of your fastq files?

Are your reads like this:


Or is there something else that lets us disambiguate forward from reverse reads?

In either case, we don’t have a way to import that data at the moment, so you may need to find a tool that can convert it, or a colleague who’s good with scripting things. But if you can tell use more about the format, we should be able to create an issue to support it in the future!

Hi @eboylen,

First off, I hardly think a response within 2 business days is delayed. Thanks for getting back so quickly-

P26_2011_06_10m_head100.fastq.txt (16.4 KB)

Attached is the first 100 lines of a sample fastq file.

In Illumina, there's a number for forward (1) and reverse (2) and the sequencing centre (DOE JGI) has put the matching paired-end reads one after another like this:

@MISEQ08:431:000000000-AT00H:1:1102:27794:11214 1:N:0:TCTGGAACGCT
@MISEQ08:431:000000000-AT00H:1:1102:27794:11214 2:N:0:TCTGGAACGCT

I've seen some perl scripts floating around to separate them into two R1/R2 files but it just feels like a waste of disk space and time to convert, so it would be great to have support for interleaved files in the future. Our workflow before had been to merge forward and reverse reads with FLASH and it had an option to work with interleaved files, and from there we worked in qiime1 with merged fastq files that read in the forward direction.


Thanks so much for all that information!

I’ve created an issue to track this format. This corresponds to in QIIME 1, so there’s a fair chance we’ll have this in the next few months as we work towards feature-parity with QIIME 1.

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