Picrust input data

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Mohsen EmamJomeh

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Jun 20, 2021, 2:47:23 PM6/20/21
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hello everyone,
I couldn't find a tutorial for the input file in picrust?
could you please help me with this?
thank you

Gavin Douglas

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Jun 21, 2021, 9:42:47 AM6/21/21
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Hi there,

The input files are described at the beginning of this tutorial (https://github.com/picrust/picrust2/wiki/PICRUSt2-Tutorial-(v2.4.1)). Is this what you were looking for?


Cheers,

Gavin

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Mohsen EmamJomeh

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Jun 22, 2021, 3:14:13 AM6/22/21
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thank you for your response. I couldn't install the picrust so I tried to use it on the galaxy server but there is no tutorial for that. could you please help me with that? 

Gavin Douglas

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Jun 22, 2021, 8:33:39 AM6/22/21
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Hi there,

The galaxy server is actually for PICRUSt1, so it’s a little different. You would need to perform reference based OTU picking against the Greengenes database to use that tool.

To use PICRUSt2 with the QIIME 2 output (and without using the QIIME 2 plugin for PICRUSt2) you would need to export the QZA representative sequence and sequence abundance tables to be FASTA and BIOM files. You can do this with the “qiime tools export” command.


Hopefully that helps,

Gavin

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Mohsen EmamJomeh

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Jun 22, 2021, 1:13:06 PM6/22/21
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thank you for your great information. I did it on qiime2 but unfortunately, I cannot figure out how to interpret the outputs? what is the next step after we get the results. there is 3 files, ec_metagenome, ko_metagenome, and pathway_abundance. what should we do with each of them?
thank you and sorry for the many questions

Gavin Douglas

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Jun 23, 2021, 9:19:15 AM6/23/21
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Hi there,

Those are profiles of the predicted abundance of each type of function across each sample. So within each sample it gives you relative breakdown for each functional abundance across all ASVs. Those tables are three types of functional data types.

There isn’t any single use for this data and it really depends on what hypothesis you want to test. Users often perform differential abundance tests to see which functions differ between sample groups. Note however if you do this that you should appreciate that this is prediction data and so the data itself is imperfect and also that often times differential abundance tests on microbiome data can produce inconsistent results (e.g., see Fig 2 of the PICRUSt2 paper).


Cheers,

Gavin


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