Should use SE transcriptomics dataset instead?

Gene Expression Omnibus

#library(ariadne)
#library(GEOquery)
#eList <- getGEO("GSE11675")

#eData <- eList[[1]]

#eData
#head(exprs(eData))
#genes <- featureData(eData)@data$ENTREZ_GENE_ID

#head(genes)
#graph <- ariadne()
#plotPath(graph, geneid ~ msig, prune = TRUE, focus = TRUE)
#gene2msig <- weavePath(graph, geneid ~ msig, init = genes)

#head(gene2msig)

Reproducibility

R session information:

## R version 4.6.1 (2026-06-24)
## Platform: x86_64-pc-linux-gnu
## Running under: Ubuntu 24.04.4 LTS
## 
## Matrix products: default
## BLAS:   /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3 
## LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.26.so;  LAPACK version 3.12.0
## 
## locale:
##  [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C               LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
##  [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8    LC_PAPER=en_US.UTF-8       LC_NAME=C                 
##  [9] LC_ADDRESS=C               LC_TELEPHONE=C             LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       
## 
## time zone: UTC
## tzcode source: system (glibc)
## 
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods   base     
## 
## other attached packages:
## [1] BiocStyle_2.41.0
## 
## loaded via a namespace (and not attached):
##  [1] digest_0.6.39       desc_1.4.3          R6_2.6.1            bookdown_0.47       fastmap_1.2.0      
##  [6] xfun_0.59           cachem_1.1.0        knitr_1.51          htmltools_0.5.9     rmarkdown_2.31     
## [11] lifecycle_1.0.5     cli_3.6.6           sass_0.4.10         pkgdown_2.2.1       textshaping_1.0.5  
## [16] jquerylib_0.1.4     systemfonts_1.3.2   compiler_4.6.1      tools_4.6.1         ragg_1.5.2         
## [21] bslib_0.11.0        evaluate_1.0.5      yaml_2.3.12         BiocManager_1.30.27 otel_0.2.0         
## [26] jsonlite_2.0.0      rlang_1.3.0         fs_2.1.0            htmlwidgets_1.6.4