pathway_daa(): There are no statistically significant biomarkers about ggpicrust2 HOT 4 OPEN

Here is a snippet of my code;
metadata <-

• read_delim(

• "C:/Users/hp/Desktop/COPD_analysis/new classification/Extracted/OMV_COPD_metadata_Dada2.txt",
  

• delim = "\t",
  

• escape_double = FALSE, trim_ws = TRUE)
  

kegg_abundance <-

• ko2kegg_abundance(

• "C:/Users/hp/Desktop/Picrust_COPD/picrust input/picrust2_out_pipeline/KO_metagenome_out/pred_metagenome_unstrat.tsv")
  

daa_results_list <-

• ggpicrust2(

• file = "C:/Users/hp/Desktop/Picrust_COPD/picrust input/picrust2_out_pipeline/KO_metagenome_out/pred_metagenome_unstrat.tsv",
  

• metadata = metadata,
  

• group = "cohort",
  

• pathway = "KO",
  

• daa_method = "LinDA",
  

• p_values_bar = TRUE,
  

• p.adjust = "BH",
  

• ko_to_kegg = TRUE,
  

• order = "cohort",
  

• select = NULL,
  

• reference = "1"
  

The kegg pathway with zero abundance in all the different samples has been removed.
0 features are filtered!
The filtered data has 76 samples and 225 features will be tested!
Warning: Some features have less than 3 nonzero values!
They have virtually no statistical power. You may consider filtering them in the analysis!
Imputation approach is used.
Fit linear models ...
Completed.
Error in ggpicrust2(file = "C:/Users/hp/Desktop/Picrust_COPD/picrust input/picrust2_out_pipeline/KO_metagenome_out/pred_metagenome_unstrat.tsv", :
There are no statistically significant biomarkers

Note: I get the same error when I follow the step-by-step process on your tutorial. Attached is my metadata file and picrust2 abundance output file.
Thank you very much for your insightful picrust2 output downstream analysis package
ggpicrust2_input.zip

from ggpicrust2.

Hi there,

Thank you for reaching out. Based on the code snippet you provided, I can see that the error message you received is not actually an error, but rather a result of the statistical test performed by the ggpicrust2 package. The message indicates that there is no statistically significant difference in the pathway abundance between the two groups you are comparing.

Therefore, this means that there is no evidence of differential signal pathway activity between the groups. Please note that the warning message about features with less than 3 nonzero values also suggests that some of the features may have very little statistical power and may need to be filtered in your analysis.

I hope this clarifies things for you. If you have any further questions or concerns, please don't hesitate to ask.

Best regards.

from ggpicrust2.

from ggpicrust2.

You can try other differential abundance methods to see if there are different biomarker with statistically significance.

from ggpicrust2.