Dependency graph


Authors: Brian Schilder, Alan Murphy, Hiranyamaya (Hiru) Dash, Nathan Skene


Vignette updated: May-05-2026

library(data.table)
## 
## Attaching package: 'data.table'
## The following object is masked from 'package:base':
## 
##     %notin%

A dependency graph for all GitHub repos that use the rworkflows GitHub Action.

Create

Here is the code for creating the plot.

Install required packages

if(!require("echodeps"))remotes::install_github("RajLabMSSM/echodeps",
                                                dependencies = TRUE)

Create graph

res <- echodeps::dep_graph(pkg = "rworkflows",
                           method_seed = "github",
                           exclude = c("neurogenomics_rworkflows",
                                       "neurogenomics_r_workflows"),
                           #node_size = "total_downloads", 
                           reverse = TRUE,
                           save_path = here::here("reports","rworkflows_depgraph.html"))

Save data

## Save network plot as PNG
echodeps::visnet_save(res$save_path)

## Save all data and plots
saveRDS(res, here::here("reports","dep_graph_res.rds"))

Count stars/clones/views

knitr::kable(res$report)

Show

rworkflow depgraph

Hover over each node to show additional metadata.

Identify highly downloaded packages

Identify the CRAN/Bioc R packages with the most number of downloads. This guides which packages would be the most useful to focus on implementing rworkflows in.

pkgs <- echogithub::r_repos_downloads(which = c("CRAN","Bioc"))

#### Get top 10 per R repository ####
pkgs_top <- pkgs[, tail(.SD, 10), by="r_repo"] 
methods::show(pkgs_top)

Assess R repository usage

This demonstrates the need for using rworkflows, as there are 25,000 R packages that are exclusively distributes via GitHub (which may or may not have code/documentation checks).

r_repos_res <- echogithub::r_repos(save_path = here::here("reports","r_repos_upset.pdf"), width=12)

Session Info

utils::sessionInfo()
## R version 4.6.0 (2026-04-24)
## Platform: aarch64-apple-darwin23
## Running under: macOS Tahoe 26.4.1
## 
## Matrix products: default
## BLAS:   /Library/Frameworks/R.framework/Versions/4.6/Resources/lib/libRblas.0.dylib 
## LAPACK: /Library/Frameworks/R.framework/Versions/4.6/Resources/lib/libRlapack.dylib;  LAPACK version 3.12.1
## 
## locale:
## [1] C/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
## 
## time zone: Europe/London
## tzcode source: internal
## 
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods   base     
## 
## other attached packages:
## [1] data.table_1.18.2.1 rworkflows_1.0.12  
## 
## loaded via a namespace (and not attached):
##  [1] gtable_0.3.6        jsonlite_2.0.0      renv_1.2.2         
##  [4] dplyr_1.2.1         compiler_4.6.0      BiocManager_1.30.27
##  [7] tidyselect_1.2.1    jquerylib_0.1.4     rvcheck_0.2.1      
## [10] scales_1.4.0        yaml_2.3.12         fastmap_1.2.0      
## [13] here_1.0.2          ggplot2_4.0.3       R6_2.6.1           
## [16] generics_0.1.4      curl_7.1.0          knitr_1.51         
## [19] yulab.utils_0.2.4   tibble_3.3.1        desc_1.4.3         
## [22] dlstats_0.1.7       rprojroot_2.1.1     bslib_0.10.0       
## [25] pillar_1.11.1       RColorBrewer_1.1-3  rlang_1.2.0        
## [28] cachem_1.1.0        badger_0.2.5        xfun_0.57          
## [31] fs_2.1.0            sass_0.4.10         S7_0.2.2           
## [34] otel_0.2.0          cli_3.6.6           magrittr_2.0.5     
## [37] digest_0.6.39       grid_4.6.0          rstudioapi_0.18.0  
## [40] rappdirs_0.3.4      lifecycle_1.0.5     vctrs_0.7.3        
## [43] evaluate_1.0.5      glue_1.8.1          farver_2.1.2       
## [46] rmarkdown_2.31      tools_4.6.0         pkgconfig_2.0.3    
## [49] htmltools_0.5.9