This package provides various themes, palettes, and other functions that are used to customise ggplots to look like they were made in GraphPad Prism. The Prism-look is achieved with theme_prism() and scale_fill|colour_prism(), axes can be changed with custom guides like guide_prism_minor(), and significance indicators added with add_pvalue().

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

This package provides functions for summarizing and plotting the output from Markov Chain Monte Carlo (MCMC) simulations, as well as diagnostic tests of convergence to the equilibrium distribution of the Markov chain.

This package provides algorithms for accelerating the convergence of slow, monotone sequences from smooth, contraction mapping such as the EM algorithm. It can be used to accelerate any smooth, linearly convergent acceleration scheme. A tutorial style introduction to this package is available in a vignette.

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

This package contains a set of functions that extend the cancor function. These functions provide new numerical and graphical outputs. It also includes a regularized extension of the canonical correlation analysis to deal with datasets with more variables than observations.

This package provides a ggplot2 extension that enables the rendering of complex formatted plot labels (titles, subtitles, facet labels, axis labels, etc.). Text boxes with automatic word wrap are also supported.

The choices of color palettes in R can be quite overwhelming with palettes spread over many packages with many different API's. This package aims to collect all color palettes across the R ecosystem under the same package with a streamlined API.

This package provides basic classes and methods for Natural Language Processing.

This package provides a system for generating extendable and customizable heatmaps for exploring complex datasets, including big data and data with multiple data types.

This package provides functions that simplify submitting R scripts to a Slurm workload manager, in part by automating the division of embarrassingly parallel calculations across cluster nodes.

This package provides gsubfn which is like gsub but can take a replacement function or certain other objects instead of the replacement string. Matches and back references are input to the replacement function and replaced by the function output. gsubfn can be used to split strings based on content rather than delimiters and for quasi-perl-style string interpolation. The package also has facilities for translating formulas to functions and allowing such formulas in function calls instead of functions.

This package provides utilities for computation and analysis of correlation/covariation in multiple sequence alignments and in side chain motions during molecular dynamics simulations. Features include the computation of correlation/covariation scores using a variety of scoring functions between either sequence positions in alignments or side chain dihedral angles in molecular dynamics simulations and utilities to analyze the correlation/covariation matrix through a variety of tools including network representation and principal components analysis. In addition, several utility functions are based on the R graphical environment to provide friendly tools for help in data interpretation.

This package is an implementation of a regularized regression prediction and empirical Bayes method to recover the true gene expression profile in noisy and sparse single-cell RNA-seq data. In single-cell RNA sequencing (scRNA-seq) studies, only a small fraction of the transcripts present in each cell are sequenced. This leads to unreliable quantification of genes with low or moderate expression, which hinders downstream analysis. This package single-cell analysis via expression recovery (SAVER) implements an expression recovery method for unique molecule index (UMI)-based scRNA-seq data that borrows information across genes and cells to provide accurate expression estimates for all genes.

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.

R-coop offers implementations of covariance, correlation and cosine similarity. The implementations are fast and memory-efficient and their use is resolved automatically based on the input data, handled by R's S3 methods. Full descriptions of the algorithms and benchmarks are available in the package vignettes.

This package provides the tools necessary to do non-standard evaluation (NSE) in R.

This package models with sparse and dense matrix matrices, using modular prediction and response module classes.

This package contains routines for logspline density estimation. The function oldlogspline() uses the same algorithm as the logspline package version 1.0.x; i.e., the Kooperberg and Stone (1992) algorithm (with an improved interface). The recommended routine logspline() uses an algorithm from Stone et al (1997).

This package provides assorted routines for combinatorics.

This is a package for visualizing data quality of partially accruing data.

The TOML configuration format specifies an excellent format suitable for both human editing as well as the common uses of a machine-readable format. This package provides Rcpp bindings to a TOML parser.

Create and manage unique directories for each TensorFlow training run. This package provides a unique, time stamped directory for each run along with functions to retrieve the directory of the latest run or latest several runs.

This package provides a normalization method for single-cell UMI count data using a variance stabilizing transformation. The transformation is based on a negative binomial regression model with regularized parameters. As part of the same regression framework, this package also provides functions for batch correction, and data correction.