uemechebe
commented
2 months ago Getting the same error. Any luck in this @freemutation @cafferychen777
Open freemutation opened 2 months ago
uemechebe
commented
2 months ago Getting the same error. Any luck in this @freemutation @cafferychen777
AbbiHern
commented
2 weeks ago Any update on this? I have code that used to work beautifully and now when I run the same code, I get all sorts of errors, including this one!
I've run the unique() function to see what is contained in the $group1 and $group2 columns, and they both clearly only have one thing.
Mine is also now saying that there is more than one thing in the method column and saying there are no significant features, but there are!
Describe the Bug Wnen I use ggpicrust2 function, it always generates the error. Any help would be greatly appreciated.
Here's my dataset including the "pred_metagenome_unstart.tsv" file and "metadata.txt" file. pred_metagenome_unstrat.tsv.gz metadata.txt
Reproducible Example Here is my code:
library(ggpicrust2) library(readr) library(tibble) library(tidyverse) library(ggprism) library(patchwork) library(ggh4x)
abundance_file <- paste(funcpath,"/pred_metagenome_unstrat.tsv", sep = "") abundance_data <- read_delim(abundance_file, delim = "\t", col_names = TRUE, trim_ws = TRUE)
metadata = phyloseq::sample_data(ps) %>% as_tibble() metadata$Group = factor(metadata$Group,levels =c("FHC","FCEP","FREP"))
metadata_com = metadata[metadata$Group %in% c("FHC", "FCEP"),] abundance_data_com = abundance_data[,c("function", metadata_com$SampleID)]
results_data_input <- ggpicrust2( data = abundance_data_com, metadata = metadata_com, group = "Group", pathway = "KO", daa_method = "LinDA", p_values_bar = TRUE, p.adjust = "none", ko_to_kegg = TRUE, order = "pathway_class", select = NULL, reference = NULL)
Actual Behavior I got an error below:
Starting the ggpicrust2 analysis...
Converting KO to KEGG...
Processing provided data frame... 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: 38.24 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: SampleID . This is important for ensuring data consistency. Using all columns in abundance. Converting abundance to a matrix... Reordering metadata... Converting metadata to a matrix and data frame... Extracting group information... Running LinDA analysis... Performing LinDA analysis... 0 features are filtered! The filtered data has 27 samples and 212 features will be tested! Pseudo-count approach is used. Fit linear models ... Completed. Processing LinDA results... LinDA analysis is complete. Success: Found 22 statistically significant biomarker(s) in the dataset. Annotating pathways...
Starting pathway annotation... DAA results data frame is not null. Proceeding... KO to KEGG is set to TRUE. Proceeding with KEGG pathway annotations... We are connecting to the KEGG database to get the latest results, please wait patiently.
Processing pathways in chunks...
|==============================================================================================================================| 100% Finished processing chunks. Time taken: 1.91 seconds.
Finalizing pathway annotations...
|================= | 14% Finished finalizing pathway annotations. Time taken: 0.02 seconds.
Returning DAA results filtered annotation data frame... Creating pathway error bar plots...
The following pathways are missing annotations and have been excluded: ko00281 You can use the 'pathway_annotation' function to add annotations for these pathways. The 'method' column in the 'daa_results_df' data frame contains more than one method. Please filter it to contain only one method. The 'group1' or 'group2' column in the 'daa_results_df' data frame contains more than one group. Please filter each to contain only one group. Error in pathway_errorbar(abundance = abundance, daa_results_df = daa_sub_method_results_df, : Visualization with 'pathway_errorbar' cannot be performed because there are no features with statistical significance. For possible solutions, please check the FAQ section of the tutorial. In addition: Warning message: In MicrobiomeStat::linda(abundance, LinDA_metadata_df, formula = "~Group_groupnonsense", : Some features have less than 3 nonzero values! They have virtually no statistical power. You may consider filtering them in the analysis!
Environment Information:
Additional Context Add any other context about the problem here, e.g., is this issue sporadic or consistent? Did it work in previous versions?