curl_fetch_memory

[mccannpeter]

Hi, I am having an issue in the pathway annotation in ggpicrust2. I have tried the other workflow with the same results. I'm not behind a firewall or proxy, I can access the url on my browser and have everything up to date including ssl certificates. Any help would be greatly appreciated. TIA

results_file_input <- ggpicrust2(file = abundance_file, metadata = metadata, group = "infection", # For example dataset, group = "Environment" pathway = "KO", daa_method = "LinDA", ko_to_kegg = TRUE, order = "pathway_class", p_values_bar = TRUE, x_lab = "pathway_name") Starting the ggpicrust2 analysis...

Converting KO to KEGG...

Loading data from file... Rows: 7600 Columns: 11 ── Column specification ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────── Delimiter: "\t" chr (1): #NAME dbl (10): NMRI_SNAIL_NAIVE_1, NMRI_SNAIL_INFECTED_1, NMRI_SNAIL_NAIVE_2, NMR...

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: 7.17 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: sample_name . 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 10 samples and 237 features will be tested! Imputation approach is used. Fit linear models ... Completed. Processing LinDA results... LinDA analysis is complete. Success: Found 28 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...

| | 0% Error in curl::curl_fetch_memory(url, handle = handle) : OpenSSL SSL_read: error:0A000126:SSL routines::unexpected eof while reading, errno 0