Package 'BiocPkgTools'

Description

get the ORCID id from cre field of Authors@R in packageDescription result

Usage

.get_cre_orcid(pkgname)

Arguments

Description

This function uses the gh package to get a list of either issues, pull requests, or GitHub commits since the specified date for a particular GitHub repository. The repository must have both the username / organization and the name, e.g., "Bioconductor/S4Vectors".

Usage

activitySince(
  gh_repo,
  activity = c("issues", "pulls", "commits"),
  status = c("closed", "open", "all"),
  Date,
  issue_metadata = c("created_at", "number", "title"),
  token = NULL
)

Arguments

Details

The tibble returned by the commits activity report contains five columns:

• 'committer_date'

• 'commit' - hash

• 'parents' - hash of parent for merge commits

• 'author'

• 'message'

For information on other columns, refer to the GitHub API under repository issues or pulls (e.g., ⁠/repos/:repo/issues⁠).

Value

A tibble with three columns corresponding to issue metadata (i.e., "created_at", "number", "title")

Examples

activitySince("Bioconductor/S4Vectors", "issues", "closed", "2021-05-01")
activitySince("Bioconductor/S4Vectors", "issues", "open", "2022-05-01")
activitySince("Bioconductor/S4Vectors", "commits", Date = "2022-05-01")

Description

Get download statistics for Bioconductor packages distributed via Anaconda.

Usage

anacondaDownloadStats()

Details

Anaconda provide daily download counts for all software packages they distribute. These are summarised into monthly tables of counts and made available from https://github.com/grimbough/anaconda-download-stats This function provides a mechanism to download these monthly counts for Bioconductor packages distributed through Anaconda.

Value

A data.frame of download statistics for all Bioconductor packages distributed by Anaconda, in tidy format. Note: Anaconda do not provide counts for unique IP addresses. This column is listed as NA for all packages to provide continuity with data from Bioconductor.org obtained by biocDownloadStats(). The counts are updated monthly, so do not expect to see counts for the current month.

Author(s)

Mike L. Smith

Examples

anacondaDownloadStats()

Description

The biocBuildEmail function provides a template for notifying maintainers of errors in the Bioconductor Build System (BBS). This convenience function returns the body of the email from a template within the package and provides a copy in the clipboard.

Usage

biocBuildEmail(
  pkg,
  version = c("release", "devel"),
  PS = character(1L),
  dry.run = TRUE,
  to = NULL,
  cc = NULL,
  bcc = NULL,
  emailTemplate = templatePath(),
  core.name = NULL,
  core.email = NULL,
  core.id = NULL,
  textOnly = FALSE,
  resend = FALSE,
  verbose = FALSE,
  credFile = "~/.blastula_creds"
)

sentHistory()

Arguments

Details

The credFile argument is a convenience for avoiding password entry at every instance an email is sent. If the default file ⁠~/.blastula_creds⁠ does not exist, the user will be prompted for authorization information. Currently it is configured to emails for the core-team:

        blastula::create_smtp_creds_file(
            file = "~/.blastula_creds",
            user = "[email protected]",
            host = "smtp.office365.com",
            port = 587,
            use_ssl = TRUE
        )
    

Value

A character string of the email

sentHistory

Check the history of emails sent

Examples

biocBuildEmail("MultiAssayExperiment", dry.run = TRUE)

Description

The online Bioconductor build reports are great for humans to look at, but they are not easily computable. This function scrapes HTML and text files available from the build report online pages to generate a tidy data frame version of the build report.

Usage

biocBuildReport(
  version = BiocManager::version(),
  pkgType = c("software", "data-experiment", "data-annotation", "workflows"),
  stage.timings = FALSE
)

Arguments

Value

A tbl_df object with columns pkg, version, author, commit, date, node, stage, and result.

Examples

# Set the stage--what version of Bioc am I using?
BiocManager::version()

latest_build <- biocBuildReport()
head(latest_build)

Description

This function parses the Build Report tarball for a Bioconductor release. By default it will pull all the report.tgz files for each Bioconductor package type. The Bioconductor Build System (BBS) Build Report tarball contains build status information for all packages in a Bioconductor release. This function is mainly used by biocBuildReport().

Usage

biocBuildReportDB(
  version = BiocManager::version(),
  pkgType = c("software", "data-experiment", "data-annotation", "workflows"),
  stage.timings = FALSE
)

Arguments

Description

This function downloads and parses the build status information for Bioconductor packages. The build status information is available for the current release and the previous release. Other versions may be available.

Usage

biocBuildStatusDB(
  version = BiocManager::version(),
  pkgType = c("software", "data-experiment", "data-annotation", "workflows")
)

Arguments

Value

A data.frame with the following columns:

• pkg: The name of the package

• node: The builder on which the package was built

• stage: The stage of the build, e.g., 'install', 'buildsrc', 'checksrc', etc.

• result: The status of the build, e.g., 'OK', 'ERROR', 'WARNINGS', etc.

Description

Get Bioconductor download statistics

Usage

biocDownloadStats(
  pkgType = c("software", "data-experiment", "workflows", "data-annotation")
)

Arguments

Details

Note that Bioconductor package download stats are not version-specific.

Value

A tibble of download statistics for all Bioconductor packages

Examples

biocDownloadStats()

Description

Explore Bioconductor packages through an interactive bubble plot. Click on bubbles to bring up additional information about the package. Size and proximity to center of a bubble is based on the downloads the package has in the past month.

Usage

biocExplore(top = 500L, ...)

Arguments

Value

A bubble plot of Bioconductor packages

Description

List all the packages associated with a maintainer. By default, it will return all packages associated with the [email protected] email. hasBiocMaint returns a logical vector corresponding to the input character vector of packages indicating whether any package is maintained by the Bioconductor core team.

Usage

biocMaintained(
  main = "[email protected]",
  version = BiocManager::version(),
  pkgType = c("software", "data-experiment", "workflows", "data-annotation")
)

hasBiocMaint(
  pkg,
  version = BiocManager::version(),
  main = "maintainer@bioconductor\\.org",
  repo = c("BioCsoft", "BioCexp", "BioCworkflows", "BioCann")
)

Arguments

Value

For biocMaintained: a tibble of packages associated with the maintainer.

For hasBiocMaint: a logical vector indicating whether the package is maintained by Bioconductor.

Examples

biocMaintained()

## maintained by Hervé and not maintainer at bioconductor dot org
hasBiocMaint("BiocGenerics")

Description

The BiocViews-generated VIEWS file is available for Bioconductor release and devel repositories. It contains quite a bit more information from the package DESCRIPTION files than the PACKAGES file. In particular, it contains biocViews annotations and URLs for vignettes and developer URLs.

Usage

biocPkgList(
  version = BiocManager::version(),
  repo = c("BioCsoft", "BioCexp", "BioCworkflows", "BioCann", "CRAN"),
  addBiocViewParents = TRUE
)

Arguments

Details

Since packages are annotated with the most specific views, the default functionality here is to add parent terms for all views for each package. For example, in the bioCsoft repository, all packages will have at least "Software" added to their biocViews. If one wants to stick to only the most specific terms, set addBiocViewParents to FALSE.

Value

An object of class tbl_df with one row per package. The result always includes a fnd list-column whose elements are character vectors of funder names extracted from persons with role "fnd" in the formatted Author field. Elements are NA_character_ for packages that declare no funder (or whose Author field contains no ⁠[fnd]⁠ role tag).

Examples

bpkgl <- biocPkgList(repo = "BioCsoft")
bpkgl
unlist(bpkgl[1,'Depends'], use.names = FALSE)

# Get a list of all packages that
# import "GEOquery"
library(dplyr)
bpkgl |>
  filter(Package == 'GEOquery') |>
  pull('importsMe') |>
  unlist()

Description

Grab build report results from BUILD_STATUS_DB for a particular package range

Usage

biocPkgRanges(
  start,
  end,
  condition = c("ERROR", "WARNINGS"),
  phase = "buildsrc",
  version = c("devel", "release")
)

Arguments

Author(s)

Vincent J. Carey

Examples

## Not run: 
biocPkgRanges(
    start = "a4", end = "CMA",
    condition = "ERROR", version = "devel"
)

## End(Not run)

Description

Bioconductor has a rich ecosystem of metadata around packages, usage, and build status. This package is a simple collection of functions to access that metadata from R. The goal is to expose metadata for data mining and value-added functionality such as package searching, text mining, and analytics on packages.

For developers

The biocBuildReport() function returns a computable form of the Bioconductor Build Report.

For users

The biocDownloadStats() function gets Bioconductor download stats, allowing users to quickly find commonly used packages. The biocPkgList() is useful for getting a complete listing of all Bioconductor packages.

Infrastructure

Bioconductor packages all have Digital Object Identifiers (DOIs). This package contains basic infrastructure for creating, updating, and de-referencing DOIs.

Author(s)

Maintainer: Sean Davis [email protected] (ORCID)

Authors:

• Sean Davis [email protected] (ORCID)

• Shian Su [email protected] [contributor]

• Marcel Ramos [email protected] (ORCID) [contributor]

Other contributors:

• Lori Shepherd [email protected] [contributor]

• Felix G.M. Ernst [email protected] [contributor]

• Jennifer Wokaty [email protected] [contributor]

• Charlotte Soneson [email protected] [contributor]

• Martin Morgan [email protected] [contributor]

• Vince Carey [email protected] [contributor]

See Also

Useful links:

• https://github.com/seandavi/BiocPkgTools

• Report bugs at https://github.com/seandavi/BiocPkgTools/issues/new

Description

Managing user data is important to allow use of email functions such as biocBuildEmail and made easy with BiocFileCache.

Usage

setCache(
  directory = tools::R_user_dir("BiocPkgTools", "cache"),
  verbose = TRUE,
  ask = interactive()
)

pkgToolsCache(...)

Arguments

pkgToolsCache

Get the directory location of the cache. It will prompt the user to create a cache if not already created. A specific directory can be used via setCache.

setCache

Specify the directory location of the data cache. By default, it will got to the user's home/.cache/R and "appname" directory as specified by tools::R_user_dir (with package="BiocPkgTools" and which="cache").

Description

The biocRevDepEmail function collects all the emails of the reverse dependencies and sends a notification that upstream package(s) have been deprecated or removed. It uses a template found in inst/resources with the templatePath() function.

Usage

biocRevDepEmail(
  packages,
  which = c("strong", "most", "all"),
  PS = character(1L),
  version = BiocManager::version(),
  dry.run = TRUE,
  cc = NULL,
  emailTemplate = templatePath("revdepnote"),
  core.name = NULL,
  core.email = NULL,
  core.id = NULL,
  textOnly = FALSE,
  verbose = FALSE,
  credFile = "~/.blastula_creds",
  ...
)

Arguments

Examples

biocRevDepEmail(
    "FindMyFriends", version = "3.13", dry.run = TRUE, textOnly = TRUE
)

Description

The function parses and returns the VIEWS file for a specified Bioconductor version, either "release" or "devel". The VIEWS file contains metadata about Bioconductor packages, including information about their categories, topics, and other details.

Usage

biocVIEWSdb(
  version = BiocManager::version(),
  pkgType = c("software", "data-experiment", "data-annotation", "workflows")
)

Arguments

Examples

biocVIEWSdb(pkgType = "software")

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("strong", "most", "all"), ...)

Arguments

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))

# 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()

Description

Package dependencies represent a directed graph (though Bioconductor dependencies are not an acyclic graph). This function simply returns an igraph graph from the package dependency data frame from a call to buildPkgDependencyDataFrame() or any tidy data frame with rows of (Package, dependency) pairs. Additional columns are added as igraph edge attributes (see igraph::graph_from_data_frame()).

Usage

buildPkgDependencyIgraph(pkgDepDF)

Arguments

Value

An igraph directed graph. See the igraph package for details of what can be done.

See Also

See buildPkgDependencyDataFrame(), igraph::graph_from_data_frame(), inducedSubgraphByPkgs(), subgraphByDegree(), igraph::igraph-es-indexing, igraph::igraph-vs-indexing

Examples

library(igraph)

pkg_dep_df = buildPkgDependencyDataFrame()

# at this point, filter or join to manipulate
# dependency data frame as you see fit.

g = buildPkgDependencyIgraph(pkg_dep_df)
g

# Look at nodes and edges
head(V(g)) # vertices
head(E(g)) # edges

# subset graph by attributes


head(sort(degree(g, mode='in'), decreasing=TRUE))
head(sort(degree(g, mode='out'), decreasing=TRUE))

Description

As the title says it should do something with class relationships

Usage

buildClassDepGraph(class, includeUnions = FALSE)

buildClassDepData(class, includeUnions = FALSE)

buildClassDepFromPackage(pkg, includeUnions = FALSE)

plotClassDep(class, includeUnions = FALSE)

plotClassDepData(data)

plotClassDepGraph(g)

Arguments

Examples

library("SummarizedExperiment")
depData <- buildClassDepData("RangedSummarizedExperiment")
depData
g <- buildClassDepGraph("RangedSummarizedExperiment")
plotClassDepGraph(g)

Description

The CRANstatus function allows users to check the status of a package and send an email report of any failures.

Usage

CRANstatus(
  pkg,
  core.name = NULL,
  core.email = NULL,
  core.id = NULL,
  to.mail = "[email protected]",
  dry.run = TRUE,
  emailTemplate = templatePath("cranreport")
)

Arguments

Description

This function uses the biocDownloadStats data to approximate when a package entered Bioconductor. Note that the download stats go back only to 2009.

Usage

firstInBioc(download_stats)

Arguments

Examples

dls <- biocDownloadStats()
tail(firstInBioc(dls))

Description

This function makes calls out to the DataCite REST API described here: https://support.datacite.org/docs/api-create-dois. The function creates a new DOI for a Bioconductor package (cannot already exist). The target URL for the DOI is the short Bioconductor package URL.

Usage

generateBiocPkgDOI(
  pkg,
  authors,
  pubyear,
  event = c("publish", "register", "hide"),
  testing = TRUE
)

Arguments

Details

The login information for the "real" Bioconductor account should be stored in the environment variables "DATACITE_USERNAME" and "DATACITE_PASSWORD

The GUI is available here: https://doi.datacite.org/.

Value

The DOI as a character(1) vector.

Examples

generateBiocPkgDOI('RANDOM_TEST_PACKAGE','Sean Davis',1972, testing = TRUE)

Description

Get data from Bioconductor

Usage

get_bioc_data()

Value

A JSON string containing Bioconductor package details

Examples

bioc_data <- get_bioc_data()

Description

get ORCID ids from cre fields of Authors@R in packageDescription results

Usage

get_cre_orcids(pkgnames)

Arguments

Note

returns NA if no ORCID provided in Authors@R for package description

Examples

get_cre_orcids(c("BiocPkgTools", "utils"))

Description

The actual vignette path is available using biocPkgList().

Usage

getBiocVignette(
  vignettePath,
  destfile = tempfile(),
  version = BiocManager::version()
)

Arguments

Value

character(1) The filename of the downloaded vignette

Examples

x = biocPkgList()
tmp = getBiocVignette(x$vignettes[[1]][1])
tmp

## Not run: 
library(pdftools)
y = pdf_text(tmp)
y = paste(y,collapse=" ")
library(tm)
v = VCorpus(VectorSource(y))

v <- v |>
    tm_map(stripWhitespace) |>
    tm_map(content_transformer(tolower)) |>
    tm_map(removeWords, stopwords("english")) |>
    tm_map(stemDocument)
dtm = DocumentTermMatrix(v)
inspect(DocumentTermMatrix(v,
    list(dictionary = as.character(x$Package))))

## End(Not run)

Description

Generate needed information to create DOI from a package directory.

Usage

getPackageInfo(dir)

Arguments

Value

A data.frame

Description

This function determines the number of years a package has been in Bioconductor. Available information includes first Bioconductor version a package appeared and the current length of time in Bioconductor. If a package has been removed from Bioconductor, information on the last Bioconductor version and approximate time in Bioconductor before removal is available.

Usage

getPkgYearsInBioc(pkglist = NULL)

Arguments

Value

'tibble' with the following columns:

• package: name of Bioconductor package

• category: bioc, data/experiment, data/annotation, workflow

• first_version_available: Bioconductor version (e.g. 1.9, 3.21) the package first became available

• first_version_release_date: Equivalent calendar date of given Bioconductor release

• approx_years_in: Numeric indicator of years in Bioconductor. If empty, indicates package was removed. See final three columns for more information.

• last_version_available: If package was removed from Bioconductor, the last Bioconductor version (e.g. 1.9, 3.21) the package was able to be installed

• last_version_release_date: Equivalent calendar date of given Bioconductor release

• years_before_rm: If removed, how many years it was in Bioconductor

Author(s)

Lori Shepherd Kern, Robert Shear

Examples

## Not run: 
   ## full table all Bioconductor packages
   tbl <- getPkgYearsInBioc()

   ## example of package list. Packages active in Bioconductor
   tbl <- getPkgYearsInBioc(c("BiocFileCache", "BiocPkgTools"))

   ## example of a package that has been removed from Bioconductor
   tbl <- getPkgYearsInBioc("ensemblVEP")

## End(Not run)

Description

For packages that live on GitHub, we can mine further details. This function returns the GitHub details for the listed packages.

Usage

githubDetails(pkgs, sleep = 0)

Arguments

Details

The gh::gh() function is used to do the fetching. If the number of packages supplied to this function is large (>40 or so), it is possible to run into problems with API rate limits. The gh package uses the environment variable "GITHUB_PAT" (for personal access token) to authenticate and then provide higher rate limits. If you run into problems with rate limits, set sleep to some small positive number to slow queries. Alternatively, create a Personal Access Token on GitHub and register it. See the gh package for details.

Examples

pkglist = biocPkgList()

# example of "pkgs" format.
head(pkglist$URL)

gh_list = githubURLParts(pkglist$URL)
gh_list = gh_list[!is.null(gh_list$user_repo),]

head(gh_list$user_repo)

ghd = githubDetails(gh_list$user_repo[1:5])
lapply(ghd, '[[', "stargazers")

Description

Extract GitHub user and repo name from GitHub URL

Usage

githubURLParts(urls)

Arguments

Value

A data.frame with four columns:

• url: The original GitHub URL

• user_repo: The GitHub "username/repo", combined

• user: The GitHub username

• repo: The GitHub repo name

Examples

# find GitHub URL details for
# Bioconductor packages
bpkgl = biocPkgList()
urldetails = githubURLParts(bpkgl$URL)
urldetails = urldetails[!is.na(urldetails$url),]
head(urldetails)

Description

Find the subgraph induced by including specific packages. The induced subgraph is the graph that includes the named packages and all edges connecting them. This is useful for a developer, for example, to examine her packages and their intervening dependencies.

Usage

inducedSubgraphByPkgs(g, pkgs, pkg_color = "red")

Arguments

Examples

library(igraph)
g <- buildPkgDependencyIgraph(buildPkgDependencyDataFrame())
## subgraph of only the first 10 packages maintained by Bioconductor
biocmaintained <- head(biocMaintained()[["Package"]], 10L)
g2 <- inducedSubgraphByPkgs(g, pkgs = biocmaintained)
g2
V(g2)

plot(g2)

## subgraph of a package's strong Bioconductor package dependencies
maedeps <- unlist(pkgBiocDeps(
    "MultiAssayExperiment", which = "strong",
    recursive = TRUE, only.bioc = TRUE
), use.names = FALSE)
g3 <- inducedSubgraphByPkgs(g, pkgs = maedeps)
plot(g3)

## same subgraph with networkD3::forceNetwork
library(networkD3)
wt <- cluster_walktrap(g3)
members <- membership(wt)
ndg3 <- igraph_to_networkD3(g3, group = members)
forceNetwork(
    Links = ndg3$links, Nodes = ndg3$nodes, Source = 'source',
    Target = 'target', NodeID = 'name', Group = 'group', zoom = TRUE,
    linkDistance = 200, fontSize = 20, opacity = 0.9, opacityNoHover = 0.9
)

Description

The latestPkgStats function combines outputs from several functions to generate a table of relevant statistics for a given package.

Usage

latestPkgStats(
  gh_repo,
  Date,
  pkgType = c("software", "data-experiment", "workflows", "data-annotation")
)

Arguments

Examples

latestPkgStats("Bioconductor/BiocGenerics", "2021-05-05")

Description

Get a data.frame of employment info from ORCID

Usage

orcid_table(orcids)

Arguments

Value

a data.frame of employment info using the ORCID API

Examples

if (interactive()) {
    orcid_table(
        orcids = c(
            "0000-0002-3242-0582",
            "0000-0003-4046-0063",
            "0000-0003-2725-0694"
        )
    )
}

Description

The function uses the pkgType argument to restrict the look up to only the relevant Bioconductor repository. It works for multiple packages of the same type.

Usage

pkgBiocDeps(
  pkg,
  pkgType = c("software", "data-experiment", "workflows", "data-annotation"),
  which = "strong",
  only.bioc = TRUE,
  recursive = FALSE,
  version = BiocManager::version()
)

Arguments

Examples

pkgBiocDeps("MultiAssayExperiment", only.bioc = TRUE)

pkgBiocDeps("MultiAssayExperiment", only.bioc = FALSE)

Description

The function returns a slightly upgraded list with dependency types as elements and package names in each of those elements, if any. The types of dependencies can be seen in the which argument documentation.

Usage

pkgBiocRevDeps(
  pkg,
  pkgType = c("software", "data-experiment", "workflows", "data-annotation"),
  which = "all",
  only.bioc = TRUE,
  version = BiocManager::version(),
  recursive = FALSE
)

## S3 method for class 'biocrevdeps'
summary(object, ...)

Arguments

Details

The summary method of the biocrevdeps class given by pkgBiocRevDeps provides a tally in each dependency field.

Value

A biocrevdeps list class object

Examples

rdeps <- pkgBiocRevDeps("MultiAssayExperiment", which = "all")
rdeps
summary(rdeps)

Description

Calculate dependency gain achieved by excluding combinations of packages

Usage

pkgCombDependencyGain(pkg, depdf, maxNbr = 3L)

Arguments

Value

A data frame with three columns: ExclPackages (the excluded direct dependencies), NbrExcl (the number of excluded direct dependencies), DepGain (the dependency gain from excluding these direct dependencies)

Author(s)

Charlotte Soneson

Examples

depdf <- buildPkgDependencyDataFrame(
  dependencies=c("Depends", "Imports"),
  repo=c("BioCsoft", "CRAN")
)
pcd <- pkgCombDependencyGain('GEOquery', depdf, maxNbr = 3L)
head(pcd[order(pcd$DepGain, decreasing = TRUE), ])

Description

Function adapted from 'itdepends::dep_usage_pkg' at https://github.com/r-lib/itdepends to obtain the functionality imported and used by a given package.

Usage

pkgDepImports(pkg)

Arguments

Details

Certain imported elements, such as built-in constants, will not be identified as imported functionality by this function.

Value

A tidy data frame with two columns:

• pkg: name of the package dependency.

• fun: name of the functionality call imported from the the dependency in the column pkg and used within the analyzed package.

Author(s)

Robert Castelo

Examples

pkgDepImports('BiocPkgTools')

Description

Elaborate a report on the dependency burden of a given package.

Usage

pkgDepMetrics(pkg, depdf)

Arguments

Value

A tidy data frame with different metrics on the package dependency burden. More concretely, the following columns:

• ImportedAndUsed: number of functionality calls imported and used in the package.

• Exported: number of functionality calls exported by the dependency.

• Usage: (ImportedAndUsedx 100) / Exported. This value provides an estimate of what fraction of the functionality of the dependency is actually used in the given package.

• DepOverlap: Similarity between the dependency graph structure of the given package and the one of the dependency in the corresponding row, estimated as the Jaccard index between the two sets of vertices of the corresponding graphs. Its values goes between 0 and 1, where 0 indicates that no dependency is shared, while 1 indicates that the given package and the corresponding dependency depend on an identical subset of packages.

• DepGainIfExcluded: The 'dependency gain' (decrease in the total number of dependencies) that would be obtained if this package was excluded from the list of direct dependencies.

The reported information is ordered by the Usage column to facilitate the identification of dependencies for which the analyzed package is using a small fraction of their functionality and therefore, it could be easier remove them. To aid in that decision, the column DepOverlap reports the overlap of the dependency graph of each dependency with the one of the analyzed package. Here a value above, e.g., 0.5, could, albeit not necessarily, imply that removing that dependency could substantially lighten the dependency burden of the analyzed package.

An NA value in the ImportedAndUsed column indicates that the function pkgDepMetrics() could not identify what functionality calls in the analyzed package are made to the dependency.

Author(s)

Robert Castelo

Charlotte Soneson

Examples

depdf <- buildPkgDependencyDataFrame(
  dependencies=c("Depends", "Imports"),
  repo=c("BioCsoft", "CRAN")
)
pkgDepMetrics('BiocPkgTools', depdf)

Description

This function uses available.packages to calculate the download rank percentile of a given package. It approximates what is observed in the Bioconductor landing page.

Usage

pkgDownloadRank(
  pkg,
  pkgType = c("software", "data-experiment", "workflows", "data-annotation"),
  version = BiocManager::version()
)

Arguments

Value

The package's percentile rank, in terms of download statistics, and proportion in the name

Examples

## Percentile rank for BiocGenerics (top 1%)
pkgDownloadRank("BiocGenerics", "software")

Description

Get Bioconductor download statistics for a package

Usage

pkgDownloadStats(
  pkg,
  pkgType = c("software", "data-experiment", "workflows", "data-annotation"),
  years = format(Sys.time(), "%Y")
)

Arguments

Value

A tibble of download statistics

Examples

pkgDownloadStats("GenomicRanges")

Description

This is a quick way to get an HTML report of packages maintained by a specific developer or which depend directly on a specified package. The function is keyed to filter based on either the maintainer name or by using the 'Depends', 'Suggests' and 'Imports' fields in package descriptions.

Usage

problemPage(
  authorPattern = "V.*Carey",
  dependsOn,
  ver = "devel",
  includeOK = FALSE
)

Arguments

Value

DT::datatable call; if assigned to a variable, must evaluate to get the page to appear

Author(s)

Vince Carey, Mike L. Smith

Examples

if (interactive()) {
  problemPage()
  problemPage(dependsOn = "limma")
}

Description

Summarize binary packages compatible with the Bioconductor or Terra container in use.

Usage

repositoryStats(
  version = BiocManager::version(),
  binary_repository = BiocManager::containerRepository(version),
  local = FALSE
)

## S3 method for class 'repositoryStats'
print(x, ...)

Arguments

Details

For local repositories, use the local = TRUE argument. Local repositories will typically start with the ⁠file://⁠ URI. The function checks the mtime of the output of file.info on the PACKAGES file in the local repository. Otherwise, by default, it will check the last-modified header of the PACKAGES file via httr2::resp_header().

Value

a list of class repositoryStats with the following fields:

• container: character(1) container label, e.g., bioconductor_docker, or NA if not evaluated on a supported container

• bioconductor_version: package_version the Bioconductor version provided by the user.

• repository_exists: logical(1) TRUE if a binary repository exists for the container and Bioconductor_Version version.

• bioconductor_binary_repository: character(1) repository location, if available, or NA if the repository does not exist.

• n_software_packages: integer(1) number of software packages in the Bioconductor source repository.

• n_binary_packages: integer(1) number of binary packages available. When a binary repository exists, this number is likely to be larger than the number of source software packages, because it includes the binary version of the source software packages, as well as the (possibly CRAN) dependencies of the binary packages

• n_binary_software_packages: integer(1) number of binary packages derived from Bioconductor source packages. This number is less than or equal to n_software_packages.

• missing_binaries: integer(1) the number of Bioconductor source software packages that are not present in the binary repository.

• out_of_date_binaries: integer(1) the number of Bioconductor source software packages that are newer than their binary counterpart. A newer source software package might occur when the main Bioconductor build system has updated a package after the most recent run of the binary build system.

Methods (by generic)

• print(repositoryStats): Print a summary of package availability in binary repositories.

Author(s)

M. Morgan

Examples

stats <- repositoryStats() # obtain statistics
stats                       # display a summary
stats$container             # access an element for further computation

Description

While the inducedSubgraphByPkgs() returns the subgraph with the minimal connections between named packages, this function takes a vector of package names, a degree (1 or more) and returns the subgraph(s) that are within degree of the package named.

Usage

subgraphByDegree(g, pkg, degree = 1, ...)

Arguments

Value

An igraph graph, with only nodes and their edges within degree of the named package

Examples

g <- buildPkgDependencyIgraph(buildPkgDependencyDataFrame())
g2 <- subgraphByDegree(g, 'GEOquery')
plot(g2)

Description

These templates are used with biocBuildEmail to notify maintainers regarding package errors and final deprecation warning.

Usage

templatePath(
  type = c("buildemail", "deprecation", "deprecguide", "cranreport", "revdepnote")
)

Arguments

Examples

templatePath("buildemail")