Help importing paired-end reads

I secuenced the endophytic metagenome of a plant with a company and i want to analyze the data with qiime (didn´t like the company report).
My data was sequenced by paired-end reads, came without adaptors and i paired the archives with the RPD pipeline tool, but i can’t find the right way to import my fastq file to qiime, any idea? i tried the casava and EMP method and nothing.

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Hi @Francisco,
Are your reads multiplexed or demultiplexed? Are these fasta or fastq after merging? The EMP import is very specific to the EMP protocol, you might be better off importing using the manifest import option instead.
On another note, what analysis are you going to be doing in Qiime2? If you plan on using a tool like DADA2, you’ll need to import raw fastq file without merging since this is done by the plugin itself. In fact, unless you have a specific reason to import merged reads I would just import unmerged reads and do this in qiime2, that way the provenance can keep track of all the workflow for 100% reproducibility.


Hi Mehrbod,

i want to classify and compare my data, im working on the tutorials already but while reading about importing data i didn’t know wich way to use.
I dont need to use the merged data (fastq) i can import the R1 and R1 fastq files for both data sets and merge them on qiime (im going to use the manifest import option)

I believe my data is demultiplexed, i have two sets of R1 and r2 archives and each one refers to one sample, for example, i have all the sequences of sample 1 in one fastq set file and al the sequences of sample 2 in another set.


Hi @Francisco,
Sounds good, carrying on everything in Qiime2 is a much better option than fragmenting them across Q1 and Q2.
Sounds like your files are already demultiplexed that makes it even easier, you can just follow those tutorials into the next step which is denoising. Good luck!

Thanks for your help, Mehrbod!

You answered some other few questions i had about the process without asking.
I marked your replys as the solution, and thanks again!

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