This package contains many functions useful for data analysis, high-level graphics, utility operations, functions for computing sample size and power, importing and annotating datasets, imputing missing values, advanced table making, variable clustering, character string manipulation, conversion of R objects to LaTeX code, and recoding variables.

This package provides an R interface to the nanoarrow C library and the Apache Arrow application binary interface. Functions to import and export ArrowArray, ArrowSchema, and ArrowArrayStream C structures to and from R objects are provided alongside helpers to facilitate zero-copy data transfer among R bindings to libraries implementing the Arrow C data interface.

Tools to clean and process text. Tools are geared at checking for substrings that are not optimal for analysis and replacing or removing them (normalizing) with more analysis friendly substrings (see Sproat, Black, Chen, Kumar, Ostendorf, & Richards (2001) doi:10.1006/csla.2001.0169) or extracting them into new variables. For example, emoticons are often used in text but not always easily handled by analysis algorithms. The replace_emoticon() function replaces emoticons with word equivalents.

mlr3 enables efficient, object-oriented programming on the building blocks of machine learning. It provides R6 objects for tasks, learners, resamplings, and measures. The package is geared towards scalability and larger datasets by supporting parallelization and out-of-memory data-backends like databases. While mlr3 focuses on the core computational operations, add-on packages provide additional functionality.

This package provides functions for obtaining the density, random variates and maximum likelihood estimates of the Zero-truncated Poisson lognormal distribution and their mixture distribution.

This package generates area-proportional Euler diagrams using numerical optimization. An Euler diagram is a generalization of a Venn diagram, relaxing the criterion that all interactions need to be represented. Diagrams may be fit with ellipses and circles via a wide range of inputs and can be visualized in numerous ways.

Thisp package enables you to track and report code coverage for your package and (optionally) upload the results to a coverage service. Code coverage is a measure of the amount of code being exercised by a set of tests. It is an indirect measure of test quality and completeness. This package is compatible with any testing methodology or framework and tracks coverage of both R code and compiled C/C++/FORTRAN code.

This package implements an S3 class for storing and formatting time-of-day values, based on the difftime class.

This package implements fast OpenMP parallel computing of Breiman's random forests for survival, competing risks, regression and classification based on Ishwaran and Kogalur's popular random survival forests (RSF) package. It handles missing data and now includes multivariate, unsupervised forests, quantile regression and solutions for class imbalanced data. It provides a fast interface using subsampling and confidence regions for variable importance.

This package provides functions for bitwise operations on integer vectors.

This package provides functions for viewing 2D and 3D data, including perspective plots, slice plots, surface plots, scatter plots, etc. It includes data sets from oceanography.

This package enables variogram modelling, including: simple, ordinary and universal point or block (co)kriging; spatio-temporal kriging; and sequential Gaussian or indicator (co)simulation. It includes variogram and variogram map plotting utility functions, and supports sf and stars.

This package provides a collection of tools to evaluate probability density functions, cumulative distribution functions, quantile functions and random numbers for truncated random variables. These functions are provided to also compute the expected value and variance. Q-Q plots can be produced. All the probability functions in the stats, stats4 and evd packages are automatically available for truncation.

The aim of the ggplot2 package is to aid in visual data investigations. This focus has led to a lack of facilities for composing specialized plots. This package aims to be a collection of mainly new statistics and geometries that fills this gap.

The h5Seurat file format is specifically designed for the storage and analysis of multi-modal single-cell and spatially-resolved expression experiments, for example, from CITE-seq or 10X Visium technologies. It holds all molecular information and associated metadata, including (for example) nearest-neighbor graphs, dimensional reduction information, spatial coordinates and image data, and cluster labels. This package also supports rapid and on-disk conversion between h5Seurat and AnnData objects, with the goal of enhancing interoperability between Seurat and Scanpy.

This package provides fast machine learning algorithms including matrix factorization and divisive clustering for large sparse and dense matrices.

This tool provides an algorithm to identify rare cell types in single-cell data. It also identifies abundant cell types. The method is based on transcript counts obtained with unique molecular identifies.

This package provides an implementation of heatmaps that offers more control over dimensions and appearance.

Tidyft is an extension of data.table. It uses modifification by reference whenever possible. This toolkit is designed for big data analysis in high-performance desktop or laptop computers. The syntax of the package is similar or identical to tidyverse.

This package provides an API for efficient .hic file data extraction with programmatic matrix access. It doesn't store the pointer data for all the matrices, only the one queried, and currently it only supports matrices.

This package provides tools to create themes and color palettes for the package ggplot2.

This package provides SNP array data from different types of copy-number regions. These regions were identified manually by the authors of the package and may be used to generate realistic data sets with known truth.

This package provides a collection of functions to visualize spatial data and models on top of static maps from various online sources (e.g Google Maps and Stamen Maps). It includes tools common to those tasks, including functions for geolocation and routing.

This package generates graphics with embedded details from statistical tests. Statistical tests included in the plots themselves. It provides an easier syntax to generate information-rich plots for statistical analysis of continuous or categorical data. Currently, it supports the most common types of statistical approaches and tests: parametric, nonparametric, robust, and Bayesian versions of t-test/ANOVA, correlation analyses, contingency table analysis, meta-analysis, and regression analyses.