Tools that can be used to reshape and restructure text data.

This package provides functions to make zebra-striped tables (tables with alternating row colors) in LaTeX and HTML formats easily from data.frame, matrix, lm, aov, anova, glm, coxph, nls, fitdistr, mytable and cbind.mytable objects.

This package provides UI widget and layout functions for writing Shiny apps that work well on small screens.

This package allows communication with the Extensible Neuroimaging Archive Toolkit. Rxnat uses the XNAT REST API to perform data queries and download images.

This package provides functions for the input/output and visualization of medical imaging data that follow either the ANALYZE, NIfTI or AFNI formats. This package is part of the Rigorous Analytics bundle.

This package provides tools for testing, monitoring and dating structural changes in (linear) regression models. It features tests/methods from the generalized fluctuation test framework as well as from the F test (Chow test) framework. This includes methods to fit, plot and test fluctuation processes (e.g., CUSUM, MOSUM, recursive/moving estimates) and F statistics, respectively. It is possible to monitor incoming data online using fluctuation processes. Finally, the breakpoints in regression models with structural changes can be estimated together with confidence intervals. Emphasis is always given to methods for visualizing the data.

This package provides the header files of mio, a cross-platform C++11 header-only library for memory mapped file IO.

This package provides an R interface to the Spectra library for large-scale eigenvalue and SVD problems. It is typically used to compute a few eigenvalues/vectors of an n by n matrix, e.g., the k largest eigenvalues, which is usually more efficient than eigen() if k << n.

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.

The brew package implements a templating framework for mixing text and R code for report generation. The template syntax is similar to PHP, Ruby's erb module, Java Server Pages, and Python's psp module.

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 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).

A treemap is a space-filling visualization of hierarchical structures. This package offers great flexibility to draw treemaps.

This package allows for fast, correct, consistent, portable, as well as convenient character string/text processing in every locale and any native encoding. Owing to the use of the ICU library, the package provides R users with platform-independent functions known to Java, Perl, Python, PHP, and Ruby programmers. Among available features there are: pattern searching (e.g. via regular expressions), random string generation, string collation, transliteration, concatenation, date-time formatting and parsing, etc.

For outlier detection in small and normally distributed samples the ratio test of Dixon (Q-test) can be used. Density, distribution function, quantile function and random generation for Dixon's ratio statistics are provided as wrapper functions. The core applies McBane's Fortran functions that use Gaussian quadrature for a numerical solution.

Sensitivity (or recall or true positive rate), false positive rate, specificity, precision (or positive predictive value), negative predictive value, misclassification rate, accuracy, F-score---these are popular metrics for assessing performance of binary classifiers for certain thresholds. These metrics are calculated at certain threshold values. Receiver operating characteristic (ROC) curve is a common tool for assessing overall diagnostic ability of the binary classifier. Unlike depending on a certain threshold, area under ROC curve (also known as AUC), is a summary statistic about how well a binary classifier performs overall for the classification task. The ROCit package provides flexibility to easily evaluate threshold-bound metrics.

This package provides fundamental abstractions for doing asynchronous programming in R using promises. Asynchronous programming is useful for allowing a single R process to orchestrate multiple tasks in the background while also attending to something else. Semantics are similar to JavaScript promises, but with a syntax that is idiomatic R.

This package provides different approaches for selecting the threshold in generalized Pareto distributions. Most of them are based on minimizing the AMSE-criterion or at least by reducing the bias of the assumed GPD-model. Others are heuristically motivated by searching for stable sample paths, i.e. a nearly constant region of the tail index estimator with respect to k, which is the number of data in the tail. The third class is motivated by graphical inspection. In addition, a sequential testing procedure for GPD-GoF-tests is also implemented here.

The sqldf function is typically passed a single argument which is an SQL select statement where the table names are ordinary R data frame names. sqldf transparently sets up a database, imports the data frames into that database, performs the SQL statement and returns the result using a heuristic to determine which class to assign to each column of the returned data frame. The sqldf or read.csv.sql functions can also be used to read filtered files into R even if the original files are larger than R itself can handle.

This package provides a menu-driven program and library of functions for carrying out convergence diagnostics and statistical and graphical analysis of Markov chain Monte Carlo (MCMC) sampling output.

This package offers an implementation of the Abnormal blood profile score (ABPS). The ABPS is a part of the Athlete biological passport program of the World anti-doping agency, which combines several blood parameters into a single score in order to detect blood doping. The package also contains functions to calculate other scores used in anti-doping programs, such as the ratio of hemoglobin to reticulocytes (OFF-score), as well as example data.

This package provides a wrapper for the homologene database by the National Center for Biotechnology Information (NCBI). It allows searching for gene homologs across species. The package also includes an updated version of the homologene database where gene identifiers and symbols are replaced with their latest (at the time of submission) version and functions to fetch latest annotation data to keep updated.

This R package downloads labeled single-cell RNA-seq data from PanglaoDB. It merges the data into a Seurat object for streamlined analysis.

This package contains methods for the detection of clusters in hierarchical clustering dendrograms.