Issue running integrated pathway analysis with metaboanalystR package

Good day,

Thank you for creating this tool. I recently installed the latest version of metaboanalystR package via

devtools::install_github(“xia-lab/MetaboAnalystR”, build = TRUE, build_vignettes = TRUE, build_manual =T,force = TRUE)

However I am having issues running the integrated pathway analysis step.

Here are links to a sample dataset I am using - Gene FC file

and

Metabolite FC file

I can run this on the web application just fine, on reusing the generated R script - the
mSet<-PerformIntegPathwayAnalysis(mSet, “dc”, “hyper”, “integ”, “query”);
step fails - giving this error message -

[1] “Loaded files from MetaboAnalyst web-server.”
[1] “Joint Pathway Analysis via api.metaboanalyst.ca successful!”
Error in my.integ.kegg() : object ‘impMat’ not found

Here is the code generated by the web application, which I then tried in rstudio and faced the error above -
R code

I have gone through previous error messages on github and this forum and I am sure my qs, curl and httr packages are updated and the metaboanalystR package can work with them - since the earlier steps of PerformGeneMapping & PerformCmpdMapping work fine.

Any help with this is appreciated!
Sid

P.S: I had earlier reported a possible error on github with the PerformIntegCmpdMapping & PerformIntegGeneMapping not being found in the latest version - on checking the web app generated R code, i realized these functions were changed so was able to solve this earlier issue.

Good day,

expanding on my issue - I get this error message as well sometimes, in addition to the one above -

[1] “Loaded files from MetaboAnalyst web-server.”
Error in curl::curl_fetch_memory(url, handle = handle) : **
** Timeout was reached: [api.xialab.ca] Connection timeout after 10013 ms

Here is my session info as well -

sessionInfo()
R version 4.2.1 (2022-06-23 ucrt)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 19045)

Matrix products: default

locale:
[1] LC_COLLATE=English_United States.utf8 LC_CTYPE=English_United States.utf8 LC_MONETARY=English_United States.utf8
[4] LC_NUMERIC=C LC_TIME=English_United States.utf8

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

other attached packages:
[1] httr_1.4.5 RSQLite_2.3.1 stringr_1.5.0 MetaboAnalystR_3.3.0 curl_5.0.0

loaded via a namespace (and not attached):
[1] nlme_3.1-162 bitops_1.0-7 lubridate_1.9.2 bit64_4.0.5 RColorBrewer_1.1-3
[6] tools_4.2.1 utf8_1.2.3 R6_2.5.1 rpart_4.1.19 KernSmooth_2.23-20
[11] lazyeval_0.2.2 DBI_1.1.3 BiocGenerics_0.42.0 colorspace_2.1-0 nnet_7.3-18
[16] withr_2.5.0 tidyselect_1.2.0 gridExtra_2.3 bit_4.0.5 compiler_4.2.1
[21] cli_3.6.1 Biobase_2.56.0 Cairo_1.6-0 plotly_4.10.1 stringfish_0.15.7
[26] caTools_1.18.2 scales_1.2.1 digest_0.6.31 siggenes_1.70.0 htmltools_0.5.5
[31] pkgconfig_2.0.3 scrime_1.3.5 parallelly_1.35.0 fastmap_1.1.1 limma_3.54.2
[36] htmlwidgets_1.6.2 rlang_1.1.0 rstudioapi_0.14 impute_1.70.0 generics_0.1.3
[41] RApiSerialize_0.1.2 jsonlite_1.8.4 crmn_0.0.21 BiocParallel_1.30.4 gtools_3.9.4
[46] ModelMetrics_1.2.2.2 dplyr_1.1.1 magrittr_2.0.3 Matrix_1.5-3 Rcpp_1.0.10
[51] munsell_0.5.0 fansi_1.0.4 lifecycle_1.0.3 pROC_1.18.0 stringi_1.7.12
[56] edgeR_3.38.4 MASS_7.3-58.3 gplots_3.1.3 plyr_1.8.8 recipes_1.0.5
[61] grid_4.2.1 blob_1.2.4 parallel_4.2.1 listenv_0.9.0 lattice_0.20-45
[66] splines_4.2.1 multtest_2.52.0 locfit_1.5-9.7 pillar_1.9.0 fgsea_1.22.0
[71] igraph_1.4.1 reshape2_1.4.4 future.apply_1.10.0 codetools_0.2-19 stats4_4.2.1
[76] fastmatch_1.1-3 glue_1.6.2 pcaMethods_1.88.0 data.table_1.14.8 RcppParallel_5.1.7
[81] vctrs_0.6.1 foreach_1.5.2 tidyr_1.3.0 gtable_0.3.3 purrr_1.0.1
[86] qs_0.25.5 future_1.32.0 cachem_1.0.7 ggplot2_3.4.2 gower_1.0.1
[91] prodlim_2023.03.31 viridisLite_0.4.1 class_7.3-21 survival_3.5-5 glasso_1.11
[96] timeDate_4022.108 tibble_3.2.1 iterators_1.0.14 memoise_2.0.1 hardhat_1.3.0
[101] lava_1.7.2.1 timechange_0.2.0 globals_0.16.2 caret_6.0-94 ipred_0.9-14