Dependency graph


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


Vignette updated: Mar-23-2026

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 Under development (unstable) (2026-02-16 r89426)
## Platform: aarch64-apple-darwin23
## Running under: macOS Tahoe 26.3
## 
## Matrix products: default
## BLAS:   /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.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_1.0.10  
## 
## loaded via a namespace (and not attached):
##  [1] gtable_0.3.6        jsonlite_2.0.0      renv_1.1.7         
##  [4] dplyr_1.2.0         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_4.0.2       R6_2.6.1           
## [16] generics_0.1.4      knitr_1.51          yulab.utils_0.2.4  
## [19] tibble_3.3.1        desc_1.4.3          dlstats_0.1.7      
## [22] rprojroot_2.1.1     bslib_0.10.0        pillar_1.11.1      
## [25] RColorBrewer_1.1-3  rlang_1.1.7         cachem_1.1.0       
## [28] badger_0.2.5        xfun_0.56           fs_1.6.6           
## [31] sass_0.4.10         S7_0.2.1            otel_0.2.0         
## [34] cli_3.6.5           magrittr_2.0.4      digest_0.6.39      
## [37] grid_4.6.0          rstudioapi_0.18.0   rappdirs_0.3.4     
## [40] lifecycle_1.0.5     vctrs_0.7.1         evaluate_1.0.5     
## [43] glue_1.8.0          farver_2.1.2        rmarkdown_2.30     
## [46] tools_4.6.0         pkgconfig_2.0.3     htmltools_0.5.9