Determining relative abundance of KO values

[mashu...@gmail.com]

Hi Everyone,

I am working in Qiime-2-Picrust.

I want to determine the relative abundance of KO values  to find which genes/enzymes /proteins are different among groups. How could it be correlated with microbiome data?

And also how can I determine the gene category level 1, 2, or 3?

I have ko_metagenome.qzv,  ec_metagenome.qzv, rarefied_table.qzv, table.qzv, feature-table.tsv and other related files (eg., jaccard emperor, bray curtis emperor) at hand.

Do you have any idea about  how to proceed for these analysis?

Thanks in advance.

[mashu...@gmail.com]

Can anybody suggest me the way, please?

I have learned that this type of analysis was available in picrust1.

Thanks 

[Gavin Douglas]

Hey there,

You can’t generate pathways just like in PICRUSt1 with PICRUSt2, but you can get them in R with soem custom code. See the FAQ here and please not the important caveats about interpreting these pathways as well: https://github.com/picrust/picrust2/wiki/Frequently-Asked-Questions#how-can-i-run-categorize_by_functionpy-like-in-picrust1

Cheers,

Gavin

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[Mashuk Siddiquee]

Thank you very much, Gavin. :)

Regards

Mashuk

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-------------------------------------------------------

Regards

Mashuk Siddiquee

E-mail: mashu...@gmail.com  

[Mashuk Siddiquee]

Thanks a lot!

Regards

Mashuk

On Wed, Feb 10, 2021 at 2:31 PM dasi...@gmail.com <dasi...@gmail.com> wrote:

Hi there

If you have Picrust2 output for pathways (i.e., path_abun_unstrat.tsv.gz), you can easily classify the pathways in four organization levels. 

Different from other databases, like SEED subsystem, MetaCyc does not have a well-defined subclassification of the pathways (i.e., some pathways can be collapsed into four levels, while others can be classified at six,...ten levels). However, we have prepared a template with all the pathways in MethaCyc, classifying them into four main  organization  levels, for example:

pathway (from Picrust2) | description | Level3 | Level2 | Level1

CALVIN-PWY | Calvin-Benson-Bassham cycle | Calvin-Benson-Bassham cycle | Sugar Biosynthesis | Carbohydrate Biosynthesis 

CENTFERM-PWY | pyruvate fermentation to butanoate | pyruvate fermentation to butanoate I Fermentation of Pyruvate | Fermentation

FAO-PWY | fatty acid &beta;-oxidation I | fatty acid β-oxidation I | Fatty Acid Degradation | Fatty Acid and Lipid | Degradation

You can use this template (excel file) to classify your patways manually, using excel's "vlookup" function.

You can find this template (Supplementary Material S1) in our paper: https://www.researchgate.net/publication/346032442_Behind_Taxonomic_Variability_The_Functional_Redundancy_in_the_Tick_Microbiome

Good luck,

Dasiel

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[mashu...@gmail.com]

Hi all, I have been trying this repeatedly but could not find a good way!

I have checked the following qiime2forum links too: https://forum.qiime2.org/t/analysis-of-qiime2-picrust2-plugin-output/13392 

I have tried some of the steps shown here (attachment: Q2PA_pluginAnalysis.docx page4) :

 Steps Shown in the link:

qiime tools export
–input-path $FILTER/rep-seqs-dada2.qza
–output-path $FILTER/export

Then
module avail picrust2

Then
module load picrust2/2.3.0

Then
picrust2_pipeline.py
-s $FILTER/export/rep-seqs-dada2.fasta
-i $FILTER/exported-feature-table_biom/feature-table.biom
-o $PIC2/picrust2_out_pipeline
-p 1

Then
add_descriptions.py -i $PIC2/picrust2_out_pipeline/EC_metagenome_out/pred_metagenome_unstrat.tsv.gz -m EC
-o $PIC2/picrust2_out_pipeline/EC_metagenome_out/pred_metagenome_unstrat_descrip.tsv.gz

add_descriptions.py -i $PIC2/picrust2_out_pipeline/KO_metagenome_out/pred_metagenome_unstrat.tsv.gz -m KO
-o $PIC2/picrust2_out_pipeline/KO_metagenome_out/pred_metagenome_unstrat_descrip.tsv.gz

add_descriptions.py -i $PIC2/picrust2_out_pipeline/pathways_out/path_abun_unstrat.tsv.gz -m METACYC
-o $PIC2/picrust2_out_pipeline/pathways_out/path_abun_unstrat_descrip.tsv.gz

My problem:

While working with picrust2 in Qiime2 plugin, I did not find any placed_seqs.tre, 16S_predicted.tsv.gz, KO_predicted.tsv.gz, EC_predicted.tsv.gz files which showed to be created during the step2 of analysis.  (Attachment :issues_qiime2-picrust2.docx)

I do not have any  rep-seqs-dada2.qza file ( I have started analysis with metadata.tsv, rep-seq.qza and table.qza files only).

Maybe, I am not getting the right point of analysis or missing some conceptual thing!

Any suggestions regarding this analysis will be highly appreciated.

Regards

Mashuk

[mashu...@gmail.com]

Another attachment is here, I missed it.