Error mSET ORA via - Failed to connect - MetaboAnalystR locally

When performing an enrichment analysis locally with MetaboAnalystR, today i had an error running the same code that executed perfectly the last week.

This is the code that worked until last week:

mSet<-InitDataObjects(“conc”, “msetora”, FALSE)
cmpd.vec<-differentiated_metabolites #This is just an R vector with the list of HMDB_IDs of the compounds
mSet<-Setup.MapData(mSet, cmpd.vec);
mSet<-CrossReferencing(mSet, “hmdb”);
mSet<-SetMetabolomeFilter(mSet, F);
mSet<-SetCurrentMsetLib(mSet, “kegg_pathway”, 2);
mSet<-PlotORA(mSet, ora_title, “net”, “png”, 300, width=NA) #This line gives the final error below
mSet<-PlotEnrichDotPlot(mSet, “ora”, enrichdot_title, “png”, 300, width=NA)

The output warnings and errors recieved are:

[1] “Loaded files from MetaboAnalyst web-server.”
[1] “1”
[2] “Name matching OK, please inspect (and manual correct) the results then proceed.”
[1] “Loaded files from MetaboAnalyst web-server.”
[1] “Loaded files from MetaboAnalyst web-server.”
[1] “Failed to connect to the API Server!”
[1] “Error! Mset ORA via unsuccessful!”

After this last warning, the next error occurs:
Error: $ operator is invalid for atomic vectors

Is it something wrong with my code? Was there an update that made something not working? Is the API server running fine?(I am correctly connected to internet). I’ll be checking if more info is needed. Thanks!

Expanding on this:

When I changed the database to “smpdb_pathway” in the SetCurrentMsetLib, the code performed correctly and about the same as it always has, but the error still occurs when setting the “kegg_pathway” parameter.

For extra info, my output running sessionInfo() is:

R version 4.0.5 (2021-03-31)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 22621)

Matrix products: default

[1] LC_COLLATE=Spanish_Chile.1252 LC_CTYPE=Spanish_Chile.1252 LC_MONETARY=Spanish_Chile.1252 LC_NUMERIC=C
[5] LC_TIME=Spanish_Chile.1252

attached base packages:
[1] stats graphics grDevices utils datasets methods base

other attached packages:
[1] httr_1.4.2 MetaboAnalystR_3.3.0 EnhancedVolcano_1.8.0 ggrepel_0.9.1 magrittr_2.0.1 readxl_1.3.1
[7] ggpubr_0.4.0 forcats_0.5.1 stringr_1.4.0 dplyr_1.0.7 purrr_0.3.4 readr_2.0.0
[13] tidyr_1.1.3 tibble_3.1.3 ggplot2_3.3.5 tidyverse_1.3.1

loaded via a namespace (and not attached):
[1] utf8_1.2.2 tidyselect_1.1.1 htmlwidgets_1.5.4 RSQLite_2.2.8 grid_4.0.5 BiocParallel_1.24.1
[7] Rtsne_0.15 pROC_1.18.0 munsell_0.5.0 codetools_0.2-18 future_1.22.1 withr_2.4.2
[13] colorspace_2.0-2 Biobase_2.50.0 phyloseq_1.34.0 ggalt_0.4.0 knitr_1.36 rstudioapi_0.13
[19] stats4_4.0.5 ggsignif_0.6.3 Rttf2pt1_1.3.8 listenv_0.8.0 labeling_0.4.2 effsize_0.8.1
[25] bit64_4.0.5 farver_2.1.0 rhdf5_2.34.0 parallelly_1.28.1 vctrs_0.3.8 generics_0.1.0
[31] ipred_0.9-12 xfun_0.24 fastcluster_1.2.3 R6_2.5.1 ggbeeswarm_0.6.0 locfit_1.5-9.4
[37] bitops_1.0-7 rhdf5filters_1.2.1 microbiome_1.12.0 cachem_1.0.6 fgsea_1.16.0 assertthat_0.2.1
[43] scales_1.1.1 nnet_7.3-16 beeswarm_0.4.0 gtable_0.3.0 ash_1.0-15 Cairo_1.5-12.2
[49] globals_0.14.0 timeDate_3043.102 rlang_0.4.11 splines_4.0.5 lazyeval_0.2.2 rstatix_0.7.0
[55] extrafontdb_1.0 ModelMetrics_1.2.2.2 impute_1.64.0 broom_0.7.9 yaml_2.2.1 reshape2_1.4.4
[61] abind_1.4-5 modelr_0.1.8 backports_1.4.1 caret_6.0-90 extrafont_0.19 tools_4.0.5
[67] lava_1.6.10 ellipsis_0.3.2 gplots_3.1.1 biomformat_1.18.0 RColorBrewer_1.1-2 BiocGenerics_0.36.1
[73] siggenes_1.64.0 Rcpp_1.0.7 plyr_1.8.6 zlibbioc_1.36.0 rpart_4.1-15 S4Vectors_0.28.1
[79] haven_2.4.1 cluster_2.1.2 fs_1.5.0 data.table_1.14.0 openxlsx_4.2.4 reprex_2.0.1
[85] pcaMethods_1.82.0 stringfish_0.15.4 hms_1.1.1 qs_0.25.1 evaluate_0.14 rio_0.5.27
[91] IRanges_2.24.1 gridExtra_2.3 compiler_4.0.5 maps_3.4.0 KernSmooth_2.23-20 crayon_1.4.1
[97] htmltools_0.5.1.1 mgcv_1.8-36 tzdb_0.1.2 RcppParallel_5.1.4 lubridate_1.7.10 DBI_1.1.1
[103] RApiSerialize_0.1.0 dbplyr_2.1.1 proj4_1.0-10.1 MASS_7.3-54 Matrix_1.3-4 ade4_1.7-22
[109] car_3.0-11 permute_0.9-5 cli_3.0.1 parallel_4.0.5 gower_0.2.2 igraph_1.2.6
[115] pkgconfig_2.0.3 foreign_0.8-81 plotly_4.10.0 recipes_0.1.17 crmn_0.0.21 xml2_1.3.2
[121] foreach_1.5.1 vipor_0.4.5 multtest_2.46.0 XVector_0.30.0 prodlim_2019.11.13 rvest_1.0.2
[127] scrime_1.3.5 digest_0.6.27 vegan_2.5-7 Biostrings_2.58.0 rmarkdown_2.11 cellranger_1.1.0
[133] fastmatch_1.1-3 edgeR_3.32.1 curl_4.3.2 gtools_3.9.2 lifecycle_1.0.1 nlme_3.1-152
[139] glasso_1.11 jsonlite_1.7.2 Rhdf5lib_1.12.1 carData_3.0-4 viridisLite_0.4.0 limma_3.46.0
[145] fansi_0.5.0 pillar_1.6.4 lattice_0.20-44 ggrastr_0.2.3 fastmap_1.1.0 survival_3.2-11
[151] glue_1.4.2 zip_2.2.0 iterators_1.0.13 bit_4.0.4 class_7.3-19 stringi_1.7.3
[157] blob_1.2.2 caTools_1.18.2 memoise_2.0.0 future.apply_1.8.1 ape_5.7-1