Using mp_diff_analysis for FAPROTAX functional data and visualization

[MizaR108]

Dear MicrobiotaProcess development Team,

I am currently working with functional data generated from a FAPROTAX analysis and am seeking guidance on using the mp_diff_analysis function from your package for differential analysis. I aim to visualize the results using the ggdiffbox function, but I've encountered several issues and uncertainties about the correct approach and handling of such data.

Here is a brief overview of the data structure I am working with:

otu.function.table[1:10, 1:10]
ACA1.1.lag ACA1.2.lag ACA2.1.lag ACA2.2.lag ACA1.1.log ACA1.2.log ACA2.1.log ACA2.2.log
methanotrophy 0 0 0 0 0 0 0 0
methanol_oxidation 460 163 46 129 315 81 299 114
methylotrophy 460 163 46 129 315 81 299 114
...

str(otu.function.table)
'data.frame': 62 obs. of 72 variables:
$ ACA1.1.lag: int 0 460 460 0 20 0 0 0 197 197 ...
...

I have attempted to use the mp_diff_analysis with various parameters, but I face errors indicating issues with data handling and compatibility, especially regarding the non-typical structure of FAPROTAX output which does not directly fit typical microbial community datasets expected by MicrobiotaProcess.

Could you provide any recommendations or guidelines on how to properly configure the analysis pipeline for this type of data? Furthermore, are there specific considerations or modifications required within the mp_diff_analysis or visualization functions to handle functional data effectively?

Thank you for your assistance.

Best regards,

Joohwan

function.table.csv
metadata.csv