View source: R/buildPkgDependencyGraph.R
buildPkgDependencyDataFrame | R Documentation |
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.
buildPkgDependencyDataFrame(dependencies = c("strong", "most", "all"), ...)
dependencies |
character() a vector listing the types of dependencies, a subset of c("Depends", "Imports", "LinkingTo", "Suggests", "Enhances"). Character string "all" is shorthand for that vector, character string "most" for the same vector without "Enhances", character string "strong" (default) for the first three elements of that vector. |
... |
parameters passed along to |
A data.frame
(also a tbl_df
) of
S3 class "biocDepDF" including columns "Package", "dependency",
and "edgetype".
This function requires network access.
See buildPkgDependencyIgraph
, biocPkgList
.
# 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))
# The Bioconductor packages with the
# largest number of imports
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()
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.