Great, I am unfamiliar w/ the format, but it appears to be a 454 pyrosequencing format. You can try to import it that way, can you screenshot the series of files? Ben
You could import using all your barcodes, than after that you could choose to merge samples.
I would encourage you to keep all your samples separate.
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I would encourage as @colinbrislawn has said to not merge the samples. There is no straightforward way without manipulation of the files (e.g., editing from a *txt file -> adding sequence counts). This is unsupported and discouraged that you do this.
My question for you: Why do you want to merge these files? Are there some features that are found in each file individually? Do you need to examine the merge file for this reason? There is a way to do this. but again, highly discouraged as this is manipulating the actual data. Ben
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Dear @ben
As i have number of samples and i have to compare the three sets of data. so we try to make it simpler and easier through merge the files.
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I'm going to apologize, but I am going to assume to put these samples into one QIIME artifact (.qza) file?
Can I see how the files look as fastq? You want to import multiple files that were Pyrosequencing -> Fastq -> QIIME2 artifact?
Once you made the fastq files it looks like you should do what this user did:
- gzip the entire fastq folder into a fastq.gz
- import it using a manifest method
Ben
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i also have import the qza file
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even i am not able to this steps. i had convert sff file to fastq file and then merged the replicates. then make it as a single file that is casava-18-single end
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Dear @Nis_12,
sorry to jump in, but I would suggest you to think harder at pro and cons on merging the replicates as you are trying to do. You will have less file to handle at this point, that is only the importing step because after import would not make any real difference, but on the cons side you are loosing the flexibility to investigate if samples replicate behave similarly, ie you wont be able to remove outliers when analysing alpha/beta- diversity. So it is worthy to make your life easy now but potentially much harder at analysis time where you want to focus on identify differences among groups?
If you importing with a manifest file, the barcode is not a problem because they won’t compare in any file, you can remove them form the metadata file if you have in there because they are simply redundant with the unique sample/group identifier.
Best wishes
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go to: view.qiime2.org
drag the *.qzv file into the web browser.
You should be able toe. view the demux file that way.
Ben
dear ben as i have completed my analysis. as what results are major used for publication and my last question is how to generate alpha rarefration curve through r.
Congratulations! 
This depends on the biological question. You should talk to your PI about your results and see what they think is most interesting. You can tell us about your biological question too! 
“Moving Pictures” tutorial — QIIME 2 2019.10.0 documentation
Why do this in R and not Qiime 2?
See the rarecurve() function on this page: An introduction to the downstream analysis with R and phyloseq — micca 1.7.0 documentation
Colin
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i had generated through qiime2 but that graph is based on only bardode based on sample based. as i want that the curve shows the results on sample-id based not in barcode. here i have attach my result
even i am not able to retrieve the result in svg and png format
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Have you tried changing the value of the Sample Metadata Column drop down box? What other options are in that drop down box, and does it includes sample-id?
no there is no option for sample-id.
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Hi @Nis_12,
yes you are right, the rarefaction plug in exclude the sample-id column from the output.
Now the question is on the metadata file you used, there is any column that contain unique value, that could be used as alternative to sample-id?
An example, if in your metadata you have, eg:
sample-id barcode
sample1 bc1
sample2 bc2
sample3 bc3
In this case, visualising the rarefaction curve using the ‘barcode’ category in the drop-down list will be the same as using ‘sample-id’.
If you have the sample with same barcode (as I suspect because you merged the samples), you probably have to repeat the rarefaction step, adding a further column in the metadata file that reflect the sample-id (the name of the column does not really matter as long as is not reserved, eg, ‘unique-id’ should work if my memory is not failing me), such as:
sample-id barcode unique-id
sample1 bc1 sample1
sample2 bc2 sample2
After visualising the file, you should be able to switch the plot to visualise the ‘unique-id’ category.
Luca
PS this is something that happens only with the rarefaction plug-in, because the visualiser for the diversity plug ins will show the data for the ‘sample-id’ category.
Luca
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as i am finding the transgenic and non transgenic difference between the soil samples…So we have seen the bacterial taxonomy in the soil samples.
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