Useful tools for working with HTTP organised by
    HTTP verbs (GET(), POST(), etc). Configuration functions make it easy
    to control additional request components (authenticate(),
    add_headers() and so on).

curl (>= 3.0.0), jsonlite, mime, openssl (>= 0.8), R6

covr, httpuv, jpeg, knitr, png, readr, rmarkdown, testthat
(>= 0.8.0), xml2

Hadley Wickham [aut, cre],
  RStudio [cph]

S4 implementation of vector-like and list-like objects

The S4Vectors package defines the Vector and List virtual classes
	and a set of generic functions that extend the semantic of ordinary
	vectors and lists in R. Package developers can easily implement
	vector-like or list-like objects as concrete subclasses of Vector or
	List. In addition, a few low-level concrete subclasses of general
	interest (e.g. DataFrame, Rle, and Hits) are implemented in the
	S4Vectors package itself (many more are implemented in the IRanges
	package and in other Bioconductor infrastructure packages).

R (>= 3.3.0), methods, utils, stats, stats4, BiocGenerics (>=
0.23.3)

IRanges, GenomicRanges, SummarizedExperiment, Matrix,
DelayedArray, ShortRead, graph, data.table, RUnit, BiocStyle

S4-utils.R show-utils.R utils.R normarg-utils.R LLint-class.R
isSorted.R subsetting-utils.R vector-utils.R integer-utils.R
character-utils.R eval-utils.R map_ranges_to_runs.R
DataTable-class.R Annotated-class.R Vector-class.R
Vector-comparison.R Vector-setops.R Vector-merge.R Hits-class.R
Hits-comparison.R Hits-setops.R Rle-class.R Rle-utils.R
List-class.R List-comparison.R List-utils.R SimpleList-class.R
HitsList-class.R DataFrame-class.R Pairs-class.R
expand-methods.R FilterRules-class.R aggregate-methods.R
shiftApply-methods.R split-methods.R zzz.R

Infrastructure for manipulating intervals on sequences

Provides efficient low-level and highly reusable S4
	classes for storing, manipulating and aggregating over annotated
	ranges of integers. Implements an algebra of range operations,
	including efficient algorithms for finding overlaps and nearest
	neighbors. Defines efficient list-like classes for storing,
	transforming and aggregating large grouped data, i.e., collections
	of atomic vectors and DataFrames.