This package facilitates RNA secondary structure plotting.

Written in C++ using Rcpp, this package provides a collection of metrics for evaluating models.

This package implements beta regression for modeling beta-distributed dependent variables on the open unit interval (0, 1), e.g., rates and proportions, see Cribari-Neto and Zeileis (2010) <doi:10.18637/jss.v034.i02>. Moreover, extended-support beta regression models can accommodate dependent variables with boundary observations at 0 and/or 1. For the classical beta regression model, alternative specifications are provided: Bias-corrected and bias-reduced estimation, finite mixture models, and recursive partitioning for beta regression, see <doi:10.18637/jss.v048.i11>.

This package provides a scripting and command-line front-end is provided by r (aka littler) as a lightweight binary wrapper around the GNU R language and environment for statistical computing and graphics. While R can be used in batch mode, the r binary adds full support for both shebang-style scripting (i.e. using a hash-mark-exclamation-path expression as the first line in scripts) as well as command-line use in standard pipelines. In other words, r provides the R language without the environment.

This package provides various methods for MRI tissue classification.

When testing multiple hypotheses simultaneously, this package provides functionality to calculate a lower bound for the number of correct rejections (as a function of the number of rejected hypotheses), which holds simultaneously -with high probability- for all possible number of rejections. As a special case, a lower bound for the total number of false null hypotheses can be inferred. Dependent test statistics can be handled for multiple tests of associations. For independent test statistics, it is sufficient to provide a list of p-values.

This package provides functions for latent class analysis, short time Fourier transform, fuzzy clustering, support vector machines, shortest path computation, bagged clustering, naive Bayes classifier, and more.

This package provides functions to build tables with advanced layout elements such as row spanners, column spanners, table spanners, zebra striping, and more. While allowing advanced layout, the underlying CSS-structure is simple in order to maximize compatibility with word processors such as LibreOffice. The package also contains a few text formatting functions that help outputting text compatible with HTML or LaTeX.

This package implements a simple key-value style database where character string keys are associated with data values that are stored on the disk. A simple interface is provided for inserting, retrieving, and deleting data from the database. Utilities are provided that allow filehash databases to be treated much like environments and lists are already used in R. These utilities are provided to encourage interactive and exploratory analysis on large datasets.

Nucleotide conversion sequencing experiments have been developed to add a temporal dimension to RNA-seq and single-cell RNA-seq. Such experiments require specialized tools for primary processing such as GRAND-SLAM, and specialized tools for downstream analyses. grandR provides a comprehensive toolbox for quality control, kinetic modeling, differential gene expression analysis and visualization of such data.

This package provides common base and stats methods for rle objects, aiming to make it possible to treat them transparently as vectors.

Estimate generalized additive mixed models via a version of function gamm from the mgcv package, using the lme4 packagefor estimation.

This package provides some functions for sample classification in microarrays.

This package adds additional Twitter Bootstrap components to Shiny.

This package lets you compute the median ranking according to Kemeny's axiomatic approach. Rankings can or cannot contain ties, rankings can be both complete or incomplete. The package contains both branch-and-bound algorithms and heuristic solutions recently proposed. The searching space of the solution can either be restricted to the universe of the permutations or unrestricted to all possible ties. The package also provides some useful utilities for deal with preference rankings, including both element-weight Kemeny distance and correlation coefficient.

This package provides an R interface to the vis.js JavaScript charting library. It allows an interactive visualization of networks.

This package provides building blocks for allowing HTML widgets to communicate with each other, with Shiny or without (i.e., static .html files). It currently supports linked brushing and filtering.

The wordspace package turns R into an interactive laboratory for empirical research on distributional semantic models (DSM). It consists of a small set of carefully designed functions, most of which

• encapsulate non-trivial R operations in a user-friendly manner or

• provide efficient and memory-lean C implementations of key operations.

This package provides tools to find the k nearest neighbours for every point in a given dataset in O(N log N) time using Arya and Mount's ANN library. There is support for approximate as well as exact searches, fixed radius searches and bd as well as kd trees. The distance is computed using the L1 (Manhattan, taxicab) metric.

This package provides functions that:

1. find the minimum/maximum of a linear or quadratic function,

2. sample an underdetermined or overdetermined system,

3. solve a linear system Ax=B for the unknown x.

It includes banded and tridiagonal linear systems. The package calls Fortran functions from LINPACK.

This package provides tools to compute ordinal, statistics and effect sizes as an alternative to mean comparison: Cliff's delta or success rate difference (SRD), Vargha and Delaney's A or the Area Under a Receiver Operating Characteristic Curve (AUC), the discrete type of McGraw & Wong's Common Language Effect Size (CLES) or Grissom & Kim's Probability of Superiority (PS), and the Number needed to treat (NNT) effect size. Moreover, comparisons to Cohen's d are offered based on Huberty & Lowman's Percentage of Group (Non-)Overlap considerations.

This package provides a set of tools for displaying, modeling and analysing multivariate abundance data in community ecology.

This package provides a collection of R-functions implementing adaptive smoothing procedures in 1D, 2D and 3D. This includes the Propagation-Separation approach to adaptive smoothing, the Intersecting Confidence Intervals (ICI), variational approaches, and a non-local means filter.

The package offers functions for analyzing and interactively exploring large-scale single-cell RNA-seq datasets. Pagoda2 primarily performs normalization and differential gene expression analysis, with an interactive application for exploring single-cell RNA-seq datasets. It performs basic tasks such as cell size normalization, gene variance normalization, and can be used to identify subpopulations and run differential expression within individual samples. pagoda2 was written to rapidly process modern large-scale scRNAseq datasets of approximately 1e6 cells. The companion web application allows users to explore which gene expression patterns form the different subpopulations within your data. The package also serves as the primary method for preprocessing data for conos.