This package provides a reticulate wrapper for the Python package anndata. It provides a scalable way of keeping track of data and learned annotations. It is used to read from and write to the h5ad file format.

This package provides alluvial plots for ggplot2. Alluvial plots use variable-width ribbons and stacked bar plots to represent multi-dimensional or repeated-measures data with categorical or ordinal variables.

This package provides utilities to understand and describe posterior distributions and Bayesian models. It includes point-estimates such as Maximum A Posteriori (MAP), measures of dispersion such as Highest Density Interval (HDI), and indices used for null-hypothesis testing (such as ROPE percentage and pd).

This package provides an implementation of sparse linear discriminant analysis, which is a supervised classification method for multiple classes. Various novel optimization approaches to this problem are implemented including alternating direction method of multipliers (ADMM), proximal gradient (PG) and accelerated proximal gradient (APG). Functions for performing cross validation are also supplied along with basic prediction and plotting functions. Sparse zero variance discriminant (SZVD) analysis is also included in the package.

This package provides an implementation of dimensionality reduction via regression using Kernel Ridge Regression.

This package lets you download Google fonts and generate CSS to use in rmarkdown documents and Shiny applications. Some popular fonts are included and ready to use.

This package provides a complete analysis pipeline for matrix-assisted laser desorption/ionization-time-of-flight (MALDI-TOF) and other two-dimensional mass spectrometry data. In addition to commonly used plotting and processing methods it includes distinctive features, namely baseline subtraction methods such as morphological filters (TopHat) or the statistics-sensitive non-linear iterative peak-clipping algorithm (SNIP), peak alignment using warping functions, handling of replicated measurements as well as allowing spectra with different resolutions.

This package lets you import OpenDocument Spreadsheet (ODS) into R as a data frame. It also supports writing data frames to an ODS file.

Dichromat collapses red-green or green-blue distinctions to simulate the effects of different types of color-blindness.

This package implements a James-Stein-type shrinkage estimator for the covariance matrix, with separate shrinkage for variances and correlations. Furthermore, functions are available for fast singular value decomposition, for computing the pseudoinverse, and for checking the rank and positive definiteness of a matrix.

This package provides a fast dimensionality reduction method scalable to large numbers of samples. Landmark Multi-Dimensional Scaling (LMDS) is an extension of classical Torgerson MDS, but rather than calculating a complete distance matrix between all pairs of samples, only the distances between a set of landmarks and the samples are calculated.

This package provides tools to render DOT diagram markup language in R and also provides the possibility to export the graphs in PostScript and SVG (Scalable Vector Graphics) formats. In addition, it supports literate programming packages such as knitr and rmarkdown.

This package provides functions that solve initial value problems of a system of first-order ordinary differential equations (ODE), of partial differential equations (PDE), of differential algebraic equations (DAE), and of delay differential equations. The functions provide an interface to the FORTRAN functions lsoda, lsodar, lsode, lsodes of the ODEPACK collection, to the FORTRAN functions dvode and daspk and a C-implementation of solvers of the Runge-Kutta family with fixed or variable time steps. The package contains routines designed for solving ODEs resulting from 1-D, 2-D and 3-D partial differential equations that have been converted to ODEs by numerical differencing.

This package provides bindings to the OSQP solver. The OSQP solver is a numerical optimization package or solving convex quadratic programs written in C and based on the alternating direction method of multipliers. See <arXiv:1711.08013> for details.

This package provides a set of predicates and assertions for checking the properties of numbers. This is mainly for use by other package developers who want to include run-time testing features in their own packages.

int64 values can be created and accessed via the bit64 package and its integer64 class which package the int64 representation cleverly into a double. The nanotime package builds on this to support nanosecond-resolution timestamps. This package helps conversions between R and C++ via several helper functions provided via a single header file. A complete example client package is included as an illustration.

This package allows you to create Q-Q and Manhattan plots for GWAS data from PLINK results.

The package includes the necessary functions to construct a self-organizing map of data, to evaluate the statistical significance of the observed data patterns, and to visualize the results.

This package offers quick statistical hypothesis testing for matrix rows/columns. The main goals are speed through vectorization, detailed and user-friendly output, and compatibility with tests implemented in R.

The r-ggformula introduces a family of graphics functions, gf_point(), gf_density(), and so on, bring the formula interface to ggplot(). This captures and extends the excellent simplicity of the lattice-graphics formula interface, while providing the intuitive capabilities of r-ggplot2.

This package provides functions to compute insolation on tilted surfaces, computes atmospheric transmittance and related parameters such as: Earth radius vector, declination, sunset and sunrise, daylength, equation of time, vector in the direction of the sun, vector normal to surface, and some atmospheric physics.

The r-mhsmm package implements estimation and prediction methods for hidden Markov and semi-Markov models for multiple observation sequences. Such techniques are of interest when observed data is thought to be dependent on some unobserved (or hidden) state. Also, this package is suitable for equidistant time series data, with multivariate and/or missing data. Allows user defined emission distributions.

This package provides utilities to process, organize and explore protein structure, sequence and dynamics data. Features include the ability to read and write structure, sequence and dynamic trajectory data, perform sequence and structure database searches, data summaries, atom selection, alignment, superposition, rigid core identification, clustering, torsion analysis, distance matrix analysis, structure and sequence conservation analysis, normal mode analysis, principal component analysis of heterogeneous structure data, and correlation network analysis from normal mode and molecular dynamics data. In addition, various utility functions are provided to enable the statistical and graphical power of the R environment to work with biological sequence and structural data.

automap performs an automatic interpolation by automatically estimating the variogram and then calling gstat.