Error of visualization of picrust functional prediction results on RStudio

[Alejandro Rosas Lopez]

Hi everyone.

I'm new in this magical worl. 

I've peformed a pipeline of Picrust for functional prediction, i'm analysing an intestinal microbiome of mices...  so, i made the taxonomic classification whit Qiime2 and then, exported my data to Picrust. 

At the end, i got mi " pred_metagenome_unstrat.tsv " archive and a " path_abun_unstrat_descrip.tsv ".

I tried to visualize it in RStudio with the following script: 

metadata <-
  read_delim(
    BalbC_Qiime_metadata,
    delim = "\t",
    escape_double = FALSE,
    trim_ws = TRUE
  )

metadata

group <- "Enviroment"
daa_results_list <-
  ggpicrust2(
    file = "pred_metagenome_unstrat.tsv",
    metadata = metadata,
    group = "Enviroment",
    pathway = "KO",
    daa_method = "LinDA",
    order = "pathway_class",
    ko_to_kegg = TRUE,
    x_lab = "pathway_name",
    p.adjust = "BH",
    select = NULL,
    reference = NULL
  )

But,  got this ...

Starting the ggpicrust2 analysis... Converting KO to KEGG... Loading data from file... Rows: 1813 Columns: 18 ── Column specification ──────────────────────────────────────────────────────────────────────────────── Delimiter: "\t" chr (1): function dbl (17): CH1, CH2, CH3, CM1, CM2, CM3, DH1, DH2, DM1, DM2, DM3, EH1, EH2, EH3, EM1, EM2, EM3 ℹ Use `spec()` to retrieve the full column specification for this data. ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message. Loading KEGG reference data. This might take a while... Performing KO to KEGG conversion. Please be patient, this might take a while... |==============================================================================================| 100% KO to KEGG conversion completed. Time elapsed: 1.73 seconds. Removing KEGG pathways with zero abundance across all samples... KEGG abundance calculation completed successfully. Performing pathway differential abundance analysis... Sample names extracted. Identifying matching columns in metadata... Matching columns identified: NA . This is important for ensuring data consistency. Using all columns in abundance. Converting abundance to a matrix... Reordering metadata... Error in `metadata[, matching_columns]`: ! Can't subset columns with `matching_columns`. ✖ Subscript `matching_columns` can't contain missing values. ✖ It has a missing value at location 1.

This is my metadata file

https://drive.google.com/file/d/1WRk_BXbTAzNTHjKvpwlZvDitMkbvQmBR/view?usp=drive_link


and this is my tsv file 

https://drive.google.com/file/d/10tfwtUC-6xZjOPZ2-T8b1LTHRdEQWWZ7/view?usp=sharing

Any idea of how i can fix it? :c 

Or may be i chose a bad method to visualize jeje 

Is there a better way to do this? Thanks!