This package includes HTML functions and methods to write in an HTML file. Thus, making HTML reports is easy. It includes a function that allows redirection on the fly, which appears to be very useful for teaching purposes, as the student can keep a copy of the produced output to keep all that they did during the course. The package comes with a vignette describing how to write HTML reports for statistical analysis. Finally, a driver for Sweave parses HTML flat files containing R code and to automatically write the corresponding outputs (tables and graphs).

This package provides routines for the analysis of indirectly measured haplotypes. The statistical methods assume that all subjects are unrelated and that haplotypes are ambiguous (due to unknown linkage phase of the genetic markers). The main functions are: haplo.em(), haplo.glm(), haplo.score(), and haplo.power(); all of which have detailed examples in the vignette.

This package provides template functions to assist in building friendly R packages that praise their users.

This package provides an R Shiny application to create visual abstracts for original research. A variety of user defined options and formatting are included.

This package defines S4 classes for single-cell genomic data and associated information, such as dimensionality reduction embeddings, nearest-neighbor graphs, and spatially-resolved coordinates. It provides data access methods and R-native hooks to ensure the Seurat object is familiar to other R users.

This package provides several utility functions for the book entitled "Practices of Medical and Health Data Analysis using R" (Pearson Education Japan, 2007) with Japanese demographic data and some demographic analysis related functions.

This package provides tools to convert plot function calls (using expression or formula) to grob or ggplot objects that are compatible with the grid and ggplot2 environment. With this package, we are able to e.g. use cowplot to align plots produced by base graphics, grid, lattice, vcd etc. by converting them to ggplot objects.

This package implements a generalized version of principal components analysis (GLM-PCA) for dimension reduction of non-normally distributed data such as counts or binary matrices.

This package provides a set of utilities for client/server computing with R, controlling a remote R session (the server) from a local one (the client).

This is a package for the manipulation of genetic data (SNPs). Computation of genetic relationship matrix (GRM) and dominance matrix, linkage disequilibrium (LD), and heritability with efficient algorithms for linear mixed models (AIREML).

This package provides a comprehensive collection for structural multivariate function estimation using smoothing splines.

This package creates square pie charts also known as waffle charts. These can be used to communicate parts of a whole for categorical quantities. To emulate the percentage view of a pie chart, a 10x10 grid should be used. In this way each square is representing 1% of the total. Waffle provides tools to create charts as well as stitch them together. Isotype pictograms can be made by using glyphs.

This package implements S4 classes and various tools for financial time series. Basic functions such as scaling and sorting, subsetting, mathematical operations and statistical functions are provided.

This package includes functions and reference data to generate and manipulate log-ratios (also known as log size index (LSI) values) from measurements obtained on zooarchaeological material. Log ratios are used to compare the relative (rather than the absolute) dimensions of animals from archaeological contexts. The zoolog package is also able to seamlessly integrate data and references with heterogeneous nomenclature, which is internally managed by a zoolog thesaurus.

mlr3pipelines enriches mlr3 with a diverse set of pipelining operators (PipeOps) that can be composed into graphs. Operations exist for data preprocessing, model fitting, and ensemble learning. Graphs can themselves be treated as mlr3 Learners and can therefore be resampled, benchmarked, and tuned.

This is a package for ratios of count data such as obtained from RNA-seq are modelled using Bayesian statistics to derive posteriors for effects sizes. This approach is described in Erhard & Zimmer (2015) <doi:10.1093/nar/gkv696> and Erhard (2018) <doi:10.1093/bioinformatics/bty471>.

This package provides an R interface to functions of the SAMtools library.

Manage the life cycle of your exported functions with shared conventions, documentation badges, and non-invasive deprecation warnings. The lifecycle package defines four development stages (experimental, maturing, stable, and questioning) and three deprecation stages (soft-deprecated, deprecated, and defunct). It makes it easy to insert badges corresponding to these stages in your documentation. Usage of deprecated functions are signalled with increasing levels of non-invasive verbosity.

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

This is a package for mixture and flexible discriminant analysis, multivariate adaptive regression splines (MARS), BRUTO, and so on.

This package provides the header files for a stripped-down version of the plog header-only C++ logging library, and a method to log to R's standard error stream.

The main aim of the pander R package is to provide a minimal and easy tool for rendering R objects into Pandoc's markdown. The package is also capable of exporting/converting complex Pandoc documents (reports) in various ways.

This package provides a small collection of interesting and educational machine learning data sets which are used as examples in the mlr3 book Applied machine learning using mlr3 in R https://mlr3book.mlr-org.com, the use case gallery https://mlr3gallery.mlr-org.com, or in other examples. All data sets are properly preprocessed and ready to be analyzed by most machine learning algorithms. Data sets are automatically added to the dictionary of tasks if mlr3 is loaded.

This package contains functions useful for correlation theory, meta-analysis (validity-generalization), reliability, item analysis, inter-rater reliability, and classical utility.