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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
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 Puzzle Generator and Solver
Generates, plays, and solves Sudoku puzzles. The GUI playSudoku() needs package "tkrplot" if you are not on Windows.
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.
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)
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)
Complete Environment for Bayesian Inference
Provides a complete environment for Bayesian inference using a variety of different samplers (see ?LaplacesDemon for an overview).
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.
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.
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.