buildPkgDependencyDataFrame: Work with Bioconductor package dependencies

In BiocPkgTools: Collection of simple tools for learning about Bioc Packages

Description

Bioconductor is built using an extensive set of core capabilities and data structures. This leads to package developers depending on other packages for interoperability and functionality. This function extracts package dependency information from biocPkgList and returns a tidy data.frame that can be used for analysis and to build graph structures of package dependencies.

Usage

buildPkgDependencyDataFrame(
  dependencies = c("Depends", "Imports", "Suggests"),
  ...
)

Arguments

dependencies	character() vector including one or more of "Depends", "Imports", or "Suggests". Default is to include all possibilities.
...	parameters passed along to biocPkgList

Value

A data.frame (also a tbl_df) of S3 class "biocDepDF" including columns "Package", "dependency", and "edgetype".

Note

This function requires network access.

See Also

See buildPkgDependencyIgraph, biocPkgList.

Examples

# performs a network call, so must be online.
library(BiocPkgTools)
depdf = buildPkgDependencyDataFrame()
head(depdf)
library(dplyr)
# filter to include only "Imports" type
# dependencies
imports_only = depdf %>% filter(edgetype=='Imports')

# top ten most imported packages
imports_only %>% select(dependency) %>%
  group_by(dependency) %>% tally() %>%
  arrange(desc(n))

# Bioconductor packages doing the largest
# amount of importing
largest_importers = imports_only %>%
  select(Package) %>%
  group_by(Package) %>% tally() %>%
  arrange(desc(n))

# not sure what these packages do. Join
# to their descriptions
biocPkgList() %>% select(Package, Description) %>%
  left_join(largest_importers) %>% arrange(desc(n)) %>%
  head()

BiocPkgTools documentation built on April 15, 2021, 6:01 p.m.