Single cell RNA sequencing datasets can be large, consisting of matrices that contain expression data for several thousand features across several thousand cells. This package is designed to easily install, manage, and learn about various single-cell datasets, provided Seurat objects and distributed as independent packages.

This package provides support for linear order and unimodal order (univariate) isotonic regression and bivariate isotonic regression with linear order on both variables.

This package provides a flexible approach to Bayesian optimization / model based optimization building on the bbotk package. The mlr3mbo is a toolbox providing both ready-to-use optimization algorithms as well as their fundamental building blocks allowing for straightforward implementation of custom algorithms. Single- and multi-objective optimization is supported as well as mixed continuous, categorical and conditional search spaces. Moreover, using mlr3mbo for hyperparameter optimization of machine learning models within the mlr3 ecosystem is straightforward via mlr3tuning.

This package provides a platform-independent API to access the operating system's credential store. It currently supports Keychain on macOS, Credential Store on Windows, the Secret Service API on GNU/Linux, and a simple, platform independent store implemented with environment variables. Additional storage back-ends can be added easily.

This package offers a flexible, feature-rich yet light-weight logging framework based on R6 classes. It supports hierarchical loggers, custom log levels, arbitrary data fields in log events, logging to plaintext, JSON, (rotating) files, memory buffers, and databases, as well as email and push notifications.

This package provides a versatile interior point solver that solves linear programs (LPs), quadratic programs (QPs), second-order cone programs (SOCPs), semidefinite programs (SDPs), and problems with exponential and power cone constraints (https://clarabel.org/stable/). For quadratic objectives, unlike interior point solvers based on the standard homogeneous self-dual embedding (HSDE) model, Clarabel handles quadratic objective without requiring any epigraphical reformulation of its objective function. It can therefore be significantly faster than other HSDE-based solvers for problems with quadratic objective functions. Infeasible problems are detected using using a homogeneous embedding technique.

This package provides a header only, C++11 interface to R's C interface. Compared to other approaches cpp11 strives to be safe against long jumps from the C API as well as C++ exceptions, conform to normal R function semantics and supports interaction with ALTREP vectors.

This package provides an interface to Amazon Web Services cost management services, including cost and usage reports, budgets, pricing, and more.

This package provides a simple method for representing a visual scene as it may be seen by an animal with less acute vision.

This package provides some low-level utilities to use for R package development. It currently provides managers for multiple package specific options and registries, vignette, unit test and bibtex related utilities.

This package provides an enum-type representation of vectors and representation of intervals, including a method of coercing variables in data frames.

Reshape2 is an R library to flexibly restructure and aggregate data using just two functions: melt and dcast (or acast).

This package provides functions to perform k-prototypes partitioning clustering for mixed variable-type data according to Z.Huang (1998): Extensions to the k-Means Algorithm for Clustering Large Data Sets with Categorical Variables, Data Mining and Knowledge Discovery 2, 283-304.

Algebraic procedures for analyses of multiple social networks are delivered with this package. multiplex makes possible, among other things, to create and manipulate multiplex, multimode, and multilevel network data with different formats. Effective ways are available to treat multiple networks with routines that combine algebraic systems like the partially ordered semigroup with decomposition procedures or semiring structures with the relational bundles occurring in different types of multivariate networks. multiplex provides also an algebraic approach for affiliation networks through Galois derivations between families of the pairs of subsets in the two domains of the network with visualization options.

The biglm package lets you create a linear model object that uses only codep^2 memory for p variables. It can be updated with more data using update. This allows linear regression on data sets larger than memory.

This package provides kernel-based machine learning methods for classification, regression, clustering, novelty detection, quantile regression and dimensionality reduction. Among other methods kernlab includes Support Vector Machines, Spectral Clustering, Kernel PCA, Gaussian Processes and a QP solver.

This package lets you build complex plots, heatmaps in particular, using natural semantics. Bigger plots can be assembled using directives such as LeftOf, RightOf, TopOf, and Beneath and more. Other features include clustering, dendrograms and integration with ggplot2 generated grid objects. This package is particularly designed for bioinformaticians to assemble complex plots for publication.

This package provides tools to export R data as LaTeX and HTML tables.

This package creates alluvial diagrams (also known as parallel sets plots) for multivariate and time series-like data.

A treemap is a space-filling visualization of hierarchical structures. This package offers great flexibility to draw treemaps.

This package provides logicless templating, with a syntax that is not limited to R.

The ps package implements an API to list, query, and manipulate system processes. Most of its code is based on the psutil Python package.

This package provides the means to plot ggplot2 graphs in the style of the XKCD web comic.

Create and customize interactive maps using the Leaflet JavaScript library and the htmlwidgets package. These maps can be used directly from the R console, from RStudio, in Shiny applications and R Markdown documents.