This package provides a violin plot, which is a combination of a box plot and a kernel density plot.

This is a developer-focused, low dependency package in tidymodels that provides functions to register how models are to be used. Functions to register models are complimented with accessor functions to retrieve registered model information to aid in model fitting and error handling.

The h5Seurat file format is specifically designed for the storage and analysis of multi-modal single-cell and spatially-resolved expression experiments, for example, from CITE-seq or 10X Visium technologies. It holds all molecular information and associated metadata, including (for example) nearest-neighbor graphs, dimensional reduction information, spatial coordinates and image data, and cluster labels. This package also supports rapid and on-disk conversion between h5Seurat and AnnData objects, with the goal of enhancing interoperability between Seurat and Scanpy.

This package provides a native R plotting library that provides a flexible declarative interface for creating interactive web-based graphics, backed by the Bokeh visualization library.

Low-rank matrix decompositions are fundamental tools and widely used for data analysis, dimension reduction, and data compression. Classically, highly accurate deterministic matrix algorithms are used for this task. However, the emergence of large-scale data has severely challenged our computational ability to analyze big data. The concept of randomness has been demonstrated as an effective strategy to quickly produce approximate answers to familiar problems such as the singular value decomposition (SVD). This package provides several randomized matrix algorithms such as the randomized singular value decomposition (rsvd), randomized principal component analysis (rpca), randomized robust principal component analysis (rrpca), randomized interpolative decomposition (rid), and the randomized CUR decomposition (rcur). In addition several plot functions are provided.

This package contains linear and nonlinear regression methods based on partial least squares and penalization techniques. Model parameters are selected via cross-validation, and confidence intervals ans tests for the regression coefficients can be conducted via jackknifing.

OOMPA offers R packages for gene expression and proteomics analysis. OOMPA uses S4 classes to construct object-oriented tools with a consistent user interface. All higher level analysis tools in OOMPA are compatible with the eSet classes defined in BioConductor. The lower level processing tools offer an alternative to parts of BioConductor, but can also be used to enhance existing BioConductor packages.

This package performs angle-based outlier detection on a given data frame. It offers three methods to process data:

1. full but slow implementation using all the data that has cubic complexity;

2. a fully randomized method;

3. a method using k-nearest neighbours.

These algorithms are well suited for high dimensional data outlier detection.

This package provides simple bindings to Unidata's udunits library.

This package was previously an R wrapper of the ARPACK library, and now a shell of the R package RSpectra, an R interface to the Spectra library for solving large scale eigenvalue/vector problems. The current version of rARPACK simply imports and exports the functions provided by RSpectra. New users of rARPACK are advised to switch to the RSpectra package.

This package provides functionality for client-side navigation of the server side file system in shiny apps. In case the app is running locally this gives the user direct access to the file system without the need to "download" files to a temporary location. Both file and folder selection as well as file saving is available.

This package provides a low-level interface to the Java VM very much like .C/.Call and friends. It allows the creation of objects, calling methods and accessing fields.

This package provides a fast dimensionality reduction method scalable to large numbers of samples. Landmark Multi-Dimensional Scaling (LMDS) is an extension of classical Torgerson MDS, but rather than calculating a complete distance matrix between all pairs of samples, only the distances between a set of landmarks and the samples are calculated.

This package provides means to run simulations for adaptive seamless designs with and without early outcomes for treatment selection and subpopulation type designs.

This package provides kernel-based machine learning methods for classification, regression, clustering, novelty detection, quantile regression and dimensionality reduction. Among other methods kernlab includes Support Vector Machines, Spectral Clustering, Kernel PCA, Gaussian Processes and a QP solver.

This package runs a minimum-hypergeometric (mHG) test as described in "Discovering Motifs in Ranked Lists of DNA Sequences" by Eran Eden.

Content-preserving transformations transformations of PDF files such as split, combine, and compress. This package interfaces directly to the qpdf C++ API and does not require any command line utilities. Note that qpdf does not read actual content from PDF files: to extract text and data you need the pdftools package.

This package provides an API for efficient .hic file data extraction with programmatic matrix access. It doesn't store the pointer data for all the matrices, only the one queried, and currently it only supports matrices.

The R kernel for the Jupyter environment executes R code which the front-end (Jupyter Notebook or other front-ends) submits to the kernel via the network.

This package provides data sets and scripts to accompany Time Series Analysis and Its Applications: With R Examples (4th ed), by R.H. Shumway and D.S. Stoffer. Springer Texts in Statistics, 2017, https://doi.org/10.1007/978-3-319-52452-8, and Time Series: A Data Analysis Approach Using R. Chapman-Hall, 2019, https://doi.org/10.1201/9780429273285.

This package provides streamlined data import and export infrastructure by making assumptions that the user is probably willing to make: import and export determine the data structure from the file extension, reasonable defaults are used for data import and export (e.g., stringsAsFactors=FALSE), web-based import is natively supported (including from SSL/HTTPS), compressed files can be read directly without explicit decompression, and fast import packages are used where appropriate. An additional convenience function, convert, provides a simple method for converting between file types.

This package contains genomic data for the plant pathogen Phytophthora infestans. It includes a variant file, a sequence file and an annotation file. This package is intended to be used as example data for packages that work with genomic data.

This package provides an extensible framework for automatically placing direct labels onto multicolor plots. Label positions are described using positioning methods that can be re-used across several different plots. There are heuristics for examining trellis and ggplot objects and inferring an appropriate positioning method.

This package performs sparse linear discriminant analysis for Gaussians and mixture of Gaussian models.