This package provides S3 generic methods and some default implementations for Bayesian analyses that generate Markov Chain Monte Carlo (MCMC) samples. The purpose of universals is to reduce package dependencies and conflicts. The nlist package implements many of the methods for its nlist class.

Turn R analysis outputs into full sentences, by writing vectors into in-sentence lists, pluralising words conditionally, spelling out numbers if they are at the start of sentences, writing out dates in full following US or UK style, and managing capitalisations in tidy data.

Vega and Vega-Lite parse text in JSON notation to render chart-specifications into HTML'. This package is used to facilitate the rendering. It also provides a means to interact with signals, events, and datasets in a Vega chart using JavaScript or Shiny'.

An all-in-one document reader for GNU Emacs, supporting all major document formats. This package intends to take from doc-view, nov.el, and pdf-tools and make them better. And as such, it is effectively a drop-in replacement for them.

This package provides a collection of programs for plotting SKEW-T,log p diagrams and wind profiles for data collected by radiosondes (the typical weather balloon-borne instrument). The format of this plot with companion lines to assess atmospheric stability are both standard in meteorology and difficult to create from basic graphics functions. Hence this package. One novel feature is being able add several profiles to the same plot for comparison. Use "help(ExampleSonde)" for an explanation of the variables needed and how they should be named in a data frame. See <https://github.com/dnychka/Radiosonde> for the package home page.

This package provides a trimmed down copy of the "kent-core source tree" turned into a C library for manipulation of .2bit files. See <https://genome.ucsc.edu/FAQ/FAQformat.html#format7> for a quick overview of the 2bit format. The "kent-core source tree" can be found here: <https://github.com/ucscGenomeBrowser/kent-core/>. Only the .c and .h files from the source tree that are related to manipulation of .2bit files were kept. Note that the package is primarily useful to developers of other R packages who wish to use the 2bit C library in their own C'/'C++ code.

New Markov chain Monte Carlo (MCMC) samplers new to be thoroughly tested and their performance accurately assessed. This requires densities that offer challenging properties to the novel sampling algorithms. One such popular problem is the Rosenbrock function. However, while its shape lends itself well to a benchmark problem, no codified multivariate expansion of the density exists. We have developed an extension to this class of distributions and supplied densities and direct sampler functions to assess the performance of novel MCMC algorithms. The functions are introduced in "An n-dimensional Rosenbrock Distribution for MCMC Testing" by Pagani, Wiegand and Nadarajah (2019) <arXiv:1903.09556>.

An optimized method for identifying mutually exclusive genomic events. Its main contribution is a statistical analysis based on the Poisson-Binomial distribution that takes into account that some samples are more mutated than others. See [Canisius, Sander, John WM Martens, and Lodewyk FA Wessels. (2016) "A novel independence test for somatic alterations in cancer shows that biology drives mutual exclusivity but chance explains most co-occurrence." Genome biology 17.1 : 1-17. <doi:10.1186/s13059-016-1114-x>]. The mutations matrices are sparse matrices. The method developed takes advantage of the advantages of this type of matrix to save time and computing resources.

This package provides an mlr3 extension that provides various resampling-based confidence interval (CI) methods for estimating the generalization error. These CI methods are implemented as mlr3 measures, enabling the evaluation of individual algorithms on specific tasks as well as the comparison of different learning algorithms.

This package provides a variety of descriptive multivariate analyses with the singular value decomposition, such as principal components analysis, correspondence analysis, and multidimensional scaling. See An ExPosition of the Singular Value Decomposition in R (Beaton et al 2014) <doi:10.1016/j.csda.2013.11.006>.

Single cell RNA sequencing datasets can be large, consisting of matrices that contain expression data for several thousand features across several thousand cells. This package is designed to easily install, manage, and learn about various single-cell datasets, provided Seurat objects and distributed as independent packages.

This class implements the File Transfer Protocol. If you have used a command-line FTP program, and are familiar with the commands, you will be able to use this class easily. Some extra features are included to take advantage of Ruby's style and strengths.

ChIPXpress takes as input predicted TF bound genes from ChIPx data and uses a corresponding database of gene expression profiles downloaded from NCBI GEO to rank the TF bound targets in order of which gene is most likely to be functional TF target.

This package provides access to eoPred pretrained model hosted on ExperimentHub. Model was trained on placental DNA methylation preeclampsia samples using mixOmics splsda. There are two resources: 1. the model object, and 2. a testing data set used to demonstrate the function.

This package provides a set of tools for analyzing data from a factorial designed microarray experiment, or any microarray experiment for which a linear model is appropriate. The functions can be used to evaluate tests of contrast of biological interest and perform single outlier detection.

The Mergeomics pipeline serves as a flexible framework for integrating multidimensional omics-disease associations, functional genomics, canonical pathways and gene-gene interaction networks to generate mechanistic hypotheses. It includes two main parts, 1) Marker set enrichment analysis (MSEA); 2) Weighted Key Driver Analysis (wKDA).

An ASCII ruler is for measuring text and is especially useful for sequence analysis. Included in this package are methods to create ASCII rulers and associated GenBank sequence blocks, multi-column text displays that make it easy for viewers to locate nucleotides by position.

Flexible and efficient cleaning of data with interactivity. datacleanr facilitates best practices in data analyses and reproducibility with built-in features and by translating interactive/manual operations to code. The package is designed for interoperability, and so seamlessly fits into reproducible analyses pipelines in R'.

This package provides methods for efficient algebraic operations and factorization of dyadic matrices using Rcpp and RcppArmadillo'. The details of dyadic matrices and the corresponding methodology are described in Kos, M., Podgórski, K., and Wu, H. (2025) <doi:10.48550/arXiv.2505.08144>.

The goal of forstringr is to enable complex string manipulation in R especially to those more familiar with LEFT(), RIGHT(), and MID() functions in Microsoft Excel. The package combines the power of stringr with other manipulation packages such as dplyr and tidyr'.

This package implements an extension of ggplot2 (formerly ggESDA') and visualizes symbolic interval-valued data with various plots, offering more general and flexible input arguments. Additionally, it provides a function to transform classical data into symbolic data using both clustering algorithms and customized methods.

Graph clustering using an agglomerative algorithm to maximize the integrated classification likelihood criterion and a mixture of stochastic block models. The method is described in the article "Model-based clustering of multiple networks with a hierarchical algorithm" by T. Rebafka (2022) <arXiv:2211.02314>.

This package provides functions and classes to compute, handle and visualise incidence from dated events for a defined time interval. Dates can be provided in various standard formats. The class incidence2 is used to store computed incidence and can be easily manipulated, subsetted, and plotted.

This is an extension package to logrx', which is a log creation program focused on Clinical Reporting within the Pharma Industry. This package enables a simple shiny-based Add-in that provides a point and click interface to produce a log for a single program.