Functions to help implement the extraction / subsetting / indexing function [ and replacement function [<- of custom matrix-like types (based on S3, S4, etc.), modeled as closely to the base matrix class as possible (with tests to prove it).

This tool provides a parallel version of the L-BFGS-B method of optim(). The main function of the package is optimParallel(), which has the same usage and output as optim(). Using optimParallel() can significantly reduce the optimization time.

This package implements a general framework for finite mixtures of regression models using the EM algorithm. FlexMix provides the E-step and all data handling, while the M-step can be supplied by the user to easily define new models. Existing drivers implement mixtures of standard linear models, generalized linear models and model-based clustering.

This package provides convenience functions for analyzing factorial experiments using ANOVA or mixed models.

This package provides tools to compute and represent gene set enrichment or depletion from your data based on pre-saved maps from the Atlas of Cancer Signalling Networks (ACSN) or user imported maps. The gene set enrichment can be run with hypergeometric test or Fisher exact test, and can use multiple corrections. Visualization of data can be done either by barplots or heatmaps.

This R package caches the results of a function so that when you call it again with the same arguments it returns the pre-computed value.

This package provides tools to identify and read BMP, JPEG, PNG, and TIFF format bitmap images. Identification defaults to the use of the magic number embedded in the file rather than the file extension.

This package provides fundamental physical constants (quantity, value, uncertainty, unit) for SI and non-SI units, plus unit conversions based on the data from NIST, USA.

This package provides building blocks for the design and analysis of multiobjective optimization algorithms.

This package provides a fast and improved implementation of the graphical LASSO.

This package provides different high-level graphics functions for displaying large datasets, displaying circular data in a very flexible way, finding local maxima, brewing color ramps, drawing nice arrows, zooming 2D-plots, creating figures with differently colored margin and plot region. In addition, the package contains auxiliary functions for data manipulation like omitting observations with irregular values or selecting data by logical vectors, which include NAs. Other functions are especially useful in spectroscopy and analyses of environmental data: robust baseline fitting, finding peaks in spectra, converting humidity measures.

This package provides a low-level interface to the Java VM very much like .C/.Call and friends. It allows the creation of objects, calling methods and accessing fields.

This package allows you to render vector-based SVG images into high-quality custom-size bitmap arrays using the librsvg2 library. The resulting bitmap can be written to e.g. PNG, JPEG or WEBP format. In addition, the package can convert images directly to various formats such as PDF or PostScript.

This package is a port of the new matplotlib color maps (viridis, magma, plasma and inferno) to R. matplotlib is a popular plotting library for Python. These color maps are designed in such a way that they will analytically be perfectly perceptually-uniform, both in regular form and also when converted to black-and-white. They are also designed to be perceived by readers with the most common form of color blindness. This is the lite version of the more complete viridis package.

This package provides a developer-facing interface to Arrow Database Connectivity (ADBC) for the purposes of driver development, driver testing, and building high-level database interfaces for users. ADBC is an API standard for database access libraries that uses Arrow for result sets and query parameters.

This is a lightweight package for computing different kinds of correlations. These correlations include partial correlations, Bayesian correlations, multilevel correlations, polychoric correlations, biweight correlations, distance correlations and more.

Radix trees, or tries, are key-value data structures optimized for efficient lookups, similar in purpose to hash tables. This package provides an implementation of radix trees for use in R programming and in developing packages with Rcpp.

This package provides tools for importing and working with bibliographic references. It greatly enhances the bibentry class by providing a class BibEntry which stores BibTeX and BibLaTeX references, supports UTF-8 encoding, and can be easily searched by any field, by date ranges, and by various formats for name lists (author by last names, translator by full names, etc.). Entries can be updated, combined, sorted, printed in a number of styles, and exported. BibTeX and BibLaTeX .bib files can be read into R and converted to BibEntry objects.

The ACE file format is used in genomics to store contigs from sequencing machines. This tools converts it into FASTQ format. Both formats contain the sequence characters and their corresponding quality information. Unlike the FASTQ file, the ACE file stores the quality values numerically. The conversion algorithm uses the standard Sanger formula. The package facilitates insertion into pipelines, and content inspection.

This package provides a framework to create Bootstrap 3 HTML reports from knitr Rmarkdown.

This package provides convenience functions for advanced linear algebra with tensors and computation with datasets of tensors on a higher level abstraction. It includes Einstein and Riemann summing conventions, dragging, co- and contravariate indices, and parallel computations on sequences of tensors.

Estimate quantile regression (QR) and composite quantile regression (cqr) and with adaptive lasso penalty using interior point (IP), majorize and minimize (MM), coordinate descent (CD), and alternating direction method of multipliers algorithms (ADMM).

Facilitates easy analysis of factorial experiments, including purely within-Ss designs (a.k.a. "repeated measures"), purely between-Ss designs, and mixed within-and-between-Ss designs. The functions in this package aim to provide simple, intuitive and consistent specification of data analysis and visualization. Visualization functions also include design visualization for pre-analysis data auditing, and correlation matrix visualization. Finally, this package includes functions for non-parametric analysis, including permutation tests and bootstrap resampling. The bootstrap function obtains predictions either by cell means or by more advanced/powerful mixed effects models, yielding predictions and confidence intervals that may be easily visualized at any level of the experiment's design.

The r-phylogram package is a tool for for developing phylogenetic trees as deeply-nested lists known as "dendrogram" objects. It provides functions for conversion between "dendrogram" and "phylo" class objects, as well as several tools for command-line tree manipulation and import/export via Newick parenthetic text. This improves accessibility to the comprehensive range of object-specific analytical and tree-visualization functions found across a wide array of bioinformatic R packages.