The Munsell package contains functions for exploring and using the Munsell colour system.

This package provides a drop-in replacement for rasterize from the raster package that takes sf-type objects, and is much faster. There is support for the main options provided by the rasterize function, including setting the field used and background value, and options for aggregating multi-layer rasters.

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.

Raw vectors in R are useful for storing a single binary object. What if you want to put a vector of them in a data frame? The blob package provides the blob object, a list of raw vectors, suitable for use as a column in data frame.

This package provides access to phyloinformatic data in NeXML format. The package should add new functionality to R such as the possibility to manipulate NeXML objects in more various and refined way and compatibility with ape objects.

Tools that can be used to reshape and restructure text data.

Phylogenetic trees generally contain multiple components including nodes, edges, branches and associated data. This package provides an approach to convert tree objects to tidy data frames. It also provides tidy interfaces to manipulate tree data.

This package contains functions for non-parametric survival analysis of exact and interval-censored observations.

The main function biclust() provides several algorithms to find biclusters in two-dimensional data, spectral, plaid model, xmotifs, and bimax. In addition, the package provides methods for data preprocessing (normalization and discretization), visualization, and validation of bicluster solutions.

This package implements functionality for exploratory data analysis and nonparametric analysis of spatial data, mainly spatial point patterns, in the spatstat family of packages. Methods include quadrat counts, K-functions and their simulation envelopes, nearest neighbour distance and empty space statistics, Fry plots, pair correlation function, kernel smoothed intensity, relative risk estimation with cross-validated bandwidth selection, mark correlation functions, segregation indices, mark dependence diagnostics, and kernel estimates of covariate effects. Formal hypothesis tests of random pattern (chi-squared, Kolmogorov-Smirnov, Monte Carlo, Diggle-Cressie-Loosmore-Ford, Dao-Genton, two-stage Monte Carlo) and tests for covariate effects (Cox-Berman-Waller-Lawson, Kolmogorov-Smirnov, ANOVA) are also supported.

This package provides tools for calculating the Delaunay triangulation and the Dirichlet or Voronoi tessellation (with respect to the entire plane) of a planar point set. It plots triangulations and tessellations in various ways, clips tessellations to sub-windows, calculates perimeters of tessellations, and summarizes information about the tiles of the tessellation.

Partial application is the process of reducing the arity of a function by fixing one or more arguments, thus creating a new function lacking the fixed arguments. The curry package provides three different ways of performing partial function application by fixing arguments from either end of the argument list (currying and tail currying) or by fixing multiple named arguments (partial application). This package provides this functionality through the %<%, %-<%, and %><% operators which allows for a programming style comparable to modern functional languages. Compared to other implementations such a purrr::partial() the operators in curry composes functions with named arguments, aiding in autocomplete etc.

This package helps to construct standard dialog boxes for your GUI, including message boxes, input boxes, list, file or directory selection, and others. In case R cannot display GUI dialog boxes, a simpler command line version of these interactive elements is also provided as a fallback solution.

This package provides interactive visualizations for profiling R code.

This package provides extra themes and scales for ggplot2 that replicate the look of plots by Edward Tufte and Stephen Few in Fivethirtyeight, The Economist, Stata, Excel, and The Wall Street Journal, among others. This package also provides geoms for Tufte's box plot and range frame.

This package provides the "enrich" method to enrich list-like R objects with new, relevant components. The current version has methods for enriching objects of class family, link-glm, lm, glm and betareg. The resulting objects preserve their class, so all methods associated with them still apply. The package also provides the enriched_glm function that has the same interface as glm but results in objects of class enriched_glm. In addition to the usual components in a glm object, enriched_glm objects carry an object-specific simulate method and functions to compute the scores, the observed and expected information matrix, the first-order bias, as well as model densities, probabilities, and quantiles at arbitrary parameter values. The package can also be used to produce customizable source code templates for the structured implementation of methods to compute new components and enrich arbitrary objects.

This R package downloads labeled single-cell RNA-seq data from PanglaoDB. It merges the data into a Seurat object for streamlined analysis.

This package provides an R implementation of an extension of the BayeScan software for codominant markers, adding the option to group individual SNPs into pre-defined blocks. A typical application of this new approach is the identification of genomic regions, genes, or gene sets containing one or more SNPs that evolved under directional selection.

This package was previously an R wrapper of the ARPACK library, and now a shell of the R package RSpectra, an R interface to the Spectra library for solving large scale eigenvalue/vector problems. The current version of rARPACK simply imports and exports the functions provided by RSpectra. New users of rARPACK are advised to switch to the RSpectra package.

Generalized Additive Mixed Modeling (GAMM; Lin & Zhang, 1999) as implemented in the R package mgcv is a nonlinear regression analysis which is particularly useful for time course data such as EEG, pupil dilation, gaze data (eye tracking), and articulography recordings, but also for behavioral data such as reaction times and response data. As time course measures are sensitive to autocorrelation problems, GAMMs implements methods to reduce the autocorrelation problems. This package includes functions for the evaluation of GAMM models (e.g., model comparisons, determining regions of significance, inspection of autocorrelational structure in residuals) and interpreting of GAMMs (e.g., visualization of complex interactions, and contrasts).

Unlike other tools that dynamically link to the Cairo stack, freetypeharfbuzz is statically linked to specific versions of the FreeType and harfbuzz libraries. This ensures deterministic computation of text box extents for situations where reproducible results are crucial (for instance unit tests of graphics).

This package helps you with creation and use of R repositories via helper functions to insert packages into a repository, and to add repository information to the current R session. Two primary types of repositories are supported: gh-pages at GitHub, as well as local repositories on either the same machine or a local network. Drat is a recursive acronym: Drat R Archive Template.

This package provides a system for querying, retrieving and analyzing protocol- and results-related information on clinical trials from three public registers, the European Union Clinical Trials Register (EUCTR), ClinicalTrials.gov (CTGOV) and the ISRCTN. Trial information is downloaded, converted and stored in a database. Functions are included to identify deduplicated records, to easily find and extract variables (fields) of interest even from complex nesting as used by the registers, and to update previous queries. The package can be used for meta-analysis and trend-analysis of the design and conduct as well as for results of clinical trials.

This is a deprecated package for accessing huge amounts of data. Cross-platform alternatives are the following packages: bigmemory (CRAN), ff (CRAN), or BufferedMatrix (Bioconductor). The main usage of it was inside the aroma.affymetrix package.