Examples: visualization, C++, networks, data cleaning, html widgets, ropensci.

Found 91 packages in 0.02 seconds

TopDom — by Henrik Bengtsson, 5 years ago

An Efficient and Deterministic Method for Identifying Topological Domains in Genomes

The 'TopDom' method identifies topological domains in genomes from Hi-C sequence data (Shin et al., 2016 ). The authors published an implementation of their method as an R script (two different versions; also available in this package). This package originates from those original 'TopDom' R scripts and provides help pages adopted from the original 'TopDom' PDF documentation. It also provides a small number of bug fixes to the original code.

digest — by Dirk Eddelbuettel, a month ago

Create Compact Hash Digests of R Objects

Implementation of a function 'digest()' for the creation of hash digests of arbitrary R objects (using the 'md5', 'sha-1', 'sha-256', 'crc32', 'xxhash', 'murmurhash', 'spookyhash', 'blake3', 'crc32c', 'xxh3_64', and 'xxh3_128' algorithms) permitting easy comparison of R language objects, as well as functions such as 'hmac()' to create hash-based message authentication code. Please note that this package is not meant to be deployed for cryptographic purposes for which more comprehensive (and widely tested) libraries such as 'OpenSSL' should be used.

sudoku — by David Brahm, 4 years ago

Sudoku Puzzle Generator and Solver

Generates, plays, and solves Sudoku puzzles. The GUI playSudoku() needs package "tkrplot" if you are not on Windows.

googleComputeEngineR — by Mark Edmondson, 7 years ago

R Interface with Google Compute Engine

Interact with the 'Google Compute Engine' API in R. Lets you create, start and stop instances in the 'Google Cloud'. Support for preconfigured instances, with templates for common R needs.

MPAgenomics — by Samuel Blanck, 5 years ago

Multi-Patient Analysis of Genomic Markers

Preprocessing and analysis of genomic data. 'MPAgenomics' provides wrappers from commonly used packages to streamline their repeated manipulation, offering an easy-to-use pipeline. The segmentation of successive multiple profiles is performed with an automatic choice of parameters involved in the wrapped packages. Considering multiple profiles in the same time, 'MPAgenomics' wraps efficient penalized regression methods to select relevant markers associated with a given outcome. Grimonprez et al. (2014) .

tidypopgen — by Andrea Manica, 2 months ago

Tidy Population Genetics

We provide a tidy grammar of population genetics, facilitating the manipulation and analysis of data on biallelic single nucleotide polymorphisms (SNPs). 'tidypopgen' scales to very large genetic datasets by storing genotypes on disk, and performing operations on them in chunks, without ever loading all data in memory. The full functionalities of the package are described in Carter et al. (2025) .

LaplacesDemon — by Henrik Singmann, 4 years ago

Complete Environment for Bayesian Inference

Provides a complete environment for Bayesian inference using a variety of different samplers (see ?LaplacesDemon for an overview).

rgee — by Matthieu Stigler, 2 months ago

R Bindings for Calling the 'Earth Engine' API

Earth Engine < https://earthengine.google.com/> client library for R. All of the 'Earth Engine' API classes, modules, and functions are made available. Additional functions implemented include importing (exporting) of Earth Engine spatial objects, extraction of time series, interactive map display, assets management interface, and metadata display. See < https://r-spatial.github.io/rgee/> for further details.

covr — by Jim Hester, a month ago

Test Coverage for Packages

Track and report code coverage for your package and (optionally) upload the results to a coverage service like 'Codecov' < https://about.codecov.io> or 'Coveralls' < https://coveralls.io>. Code coverage is a measure of the amount of code being exercised by a set of tests. It is an indirect measure of test quality and completeness. This package is compatible with any testing methodology or framework and tracks coverage of both R code and compiled C/C++/FORTRAN code.

BrailleR — by A. Jonathan R. Godfrey, 2 years ago

Improved Access for Blind Users

Blind users do not have access to the graphical output from R without printing the content of graphics windows to an embosser of some kind. This is not as immediate as is required for efficient access to statistical output. The functions here are created so that blind people can make even better use of R. This includes the text descriptions of graphs, convenience functions to replace the functionality offered in many GUI front ends, and experimental functionality for optimising graphical content to prepare it for embossing as tactile images.