This package provides a comprehensive suite of spatial functions created to analyze and assess data heterogeneity and climate variability in spatial datasets. This package is specifically designed to address the challenges associated with characterizing and understanding complex spatial patterns in environmental and climate-related data.

Implementations of the weighted Kozachenko-Leonenko entropy estimator and independence tests based on this estimator, (Kozachenko and Leonenko (1987) <http://mi.mathnet.ru/eng/ppi797>). Also includes a goodness-of-fit test for a linear model which is an independence test between covariates and errors.

Individual based simulations of hybridizing populations, where the accumulation of junctions is tracked. Furthermore, mathematical equations are provided to verify simulation outcomes. Both simulations and mathematical equations are based on Janzen (2018, <doi:10.1101/058107>) and Janzen (2022, <doi:10.1111/1755-0998.13519>).

High-performance MongoDB client based on mongo-c-driver and jsonlite'. Includes support for aggregation, indexing, map-reduce, streaming, encryption, enterprise authentication, and GridFS. The online user manual provides an overview of the available methods in the package: <https://jeroen.github.io/mongolite/>.

Deep Learning library that extends the mlr3 framework by building upon the torch package. It allows to conveniently build, train, and evaluate deep learning models without having to worry about low level details. Custom architectures can be created using the graph language defined in mlr3pipelines'.

This package provides the probability, distribution, and quantile functions and random number generator for the Poisson-Binomial distribution. This package relies on FFTW to implement the discrete Fourier transform, so that it is much faster than the existing implementation of the same algorithm in R.

This package implements multinomial CDF (P(N1<=n1, ..., Nk<=nk)) and tail probabilities (P(N1>n1, ..., Nk>nk)), as well as probabilities with both constraints (P(l1<N1<=u1, ..., lk<Nk<=uk)). Uses a method suggested by Bruce Levin (1981) <doi:10.1214/aos/1176345593>.

Create a project directory structure, along with typical files for that project. This allows projects to be quickly and easily created, as well as for them to be standardized. Designed specifically with scientists in mind (mainly bio-medical researchers, but likely applies to other fields).

Useful git hooks for R building on top of the multi-language framework pre-commit for hook management. This package provides git hooks for common tasks like formatting files with styler or spell checking as well as wrapper functions to access the pre-commit executable.

Connect R to the PhotosynQ platform (<https://photosynq.org>). It allows to login and logout, as well as receive project information and project data. Further it transforms the received JSON objects into a data frame, which can be used for the final data analysis.

Convert laboratory data to the Portuguese Information System for Water Resources SNIRH file format. SNIRH is Portugal's national water resources information system <https://snirh.apambiente.pt/>. The package validates station data, converts parameters and units, and generates compliant output files for data submission.

This package provides machine-readable access to parliamentary data of the Swiss Federal Assembly via the OData interface (<https://ws.parlament.ch/odata.svc/>) and the OpenParlData REST API (<https://api.openparldata.ch>), which also offers harmonized data for selected cantonal and municipal parliaments.

An aid for text mining in R, with a syntax that should be familiar to experienced R users. Provides a wrapper for several topic models that take similarly-formatted input and give similarly-formatted output. Has additional functionality for analyzing and diagnostics for topic models.

cl-ratify is a collection of utilities to perform validation checks and parsing. The main intention of usage for this is in web-applications in order to check form inputs for correctness and automatically parse them into their proper representations or return meaningful errors.

This package provides an R interface to Megadepth. It is particularly useful for computing the coverage of a set of genomic regions across bigWig or BAM files. With this package, you can build base-pair coverage matrices for regions or annotations of your choice from BigWig files.

This package extends the grammar of graphics as implemented by ggplot2 to include the description of animation. It does this by providing a range of new grammar classes that can be added to the plot object in order to customise how it should change with time.

This package helps to construct standard dialog boxes for your GUI, including message boxes, input boxes, list, file or directory selection, and others. In case R cannot display GUI dialog boxes, a simpler command line version of these interactive elements is also provided as a fallback solution.

Package designed to aid in classifying cells from single-cell RNA sequencing data using external reference data (e.g., bulk RNA-seq, scRNA-seq, microarray, gene lists). A variety of correlation based methods and gene list enrichment methods are provided to assist cell type assignment.

This package is designed for calling lineage-informative mitochondrial mutations using single-cell sequencing data, such as scRNASeq and scATACSeq (preferably the latter due to RNA editing issues). It includes functions for mutation calling and visualization. Mutation calling is done using beta-binomial distribution.

You can use this package to create custom pipeline badges in a standard svg format. This is useful for a company to use internally, where it may not be possible to create badges through external providers. This project was inspired by the anybadge library in python.

Use Monte-Carlo and K-fold cross-validation coupled with machine- learning classification algorithms to perform population assignment, with functionalities of evaluating discriminatory power of independent training samples, identifying informative loci, reducing data dimensionality for genomic data, integrating genetic and non-genetic data, and visualizing results.

Simulating synthetic clumped isotope dataset, fitting linear regression models under Bayesian and non-Bayesian frameworks, and generating temperature reconstructions for the same two approaches. Please note that models implemented in this package are described in Roman-Palacios et al. (2021) <doi:10.1002/essoar.10507995.1>.

Statistical summary of STRUCTURE output. STRUCTURE is a K-means clustering method for inferring population structure and assigning individuals to populations using genetic data. Pritchard JK, Stephens M, Donnelly PJ (2000) <DOI:10.1093/genetics/155.2.945>. <https://web.stanford.edu/group/pritchardlab/structure.html>.

This package provides a Bayesian method for Phenome-wide association studies (PheWAS) that identifies causal associations between genetic variants and traits, while simultaneously addressing confounding due to linkage disequilibrium. For details see Manipur et al (2024, Nature Communications) <doi:10.1038/s41467-024-49990-8>.