Picrust2 output interpretation and relative abundance calculation

[Katy Faulkner]

Hello,

I have run Picrust2 analysis and I would like to confirm my interpretation of the output in the 'pred_metagenome_unstrat.tsv' file is correct. Have these EC abundances been normalised for ASV read depth and predicted 16S copy number already?

Would I therefore calculate relative abundance directly from this table ('pred_metagenome_unstrat.tsv') by dividing the EC abundance of interest per sample by the sum of all EC abundances per sample, and then multiplying by 100?

Many thanks in advance for your help.

Best wishes,

Katy

[Gavin Douglas]

Hi Katy,

They have been normalized by 16S copy number (by default, unless that option is turned off). They are not normalized by ASV read depth, which is why you would need to convert the data to relative abundance, or use a tool that could handle the compositionality of the data.

Yes that’s how you would convert the table to relative abundances.

Cheers,

Gavin

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[Nisa]

Hello,

I am new to PICRUST2. After running the q2 PICRUST2, got the following output files.  pathways-path_abun_unstrat_descrip.tsv,  EC metagenome-path_metagenome_unstrat_descrip.tsv,  KO metagenome -pred_metagenome_unstrat.tsv. (after decompression). Is the relative abundance calculation applies to all? I am interested in the pathways and thinking of using STAMP. 
Thank you in advance!

Nisarga

[Gavin Douglas]

Hi Nisarga,

No they are not converted to relative abundance, so you would need to make sure to do that yourself if you wanted to analyze the data in that format.

Cheers,

Gavin

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[Nisa]

Thank you, Gavin. 

I have more questions. From the pathway (MetaCyC) output, is there any technique/tool we can categorize the pathways according to function? As we get hundreds of pathways in the output file. Like basic metabolic pathways.  

Also, I know it's really basic, but I am not sure how to calculate the relative abundance. 

Thank you so much

Nisarga  

[Gavin Douglas]

Hi Nisarga,

I don’t know of a tool or script to do that for you, but I know I have seen on the Metacyc website a few years ago that they are gathered into several larger categories. I don’t have this information myself though, but hopefully it’s available on their website!

Relative abundance can be calculated by summing up all the features (in this case pathways) per sample and then dividing each feature’s abundance by that sum. This converts the abundances to proportions across each sample (which are often multiplied by 100 to create a percentage).

All the best,

Gavin

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[Nisa]

Thank you! Got it. I will go through the MetaCyc website.

Nisarga