This package provides a collection of R Markdown templates for nicely structured, reproducible data analyses in R. The templates have embedded examples on how to write citations, footnotes, equations and use colored message/info boxes, how to cross-reference different parts/sections in the report, provide a nice table of contents (toc) with a References section and proper R session information as well as examples using DT tables and ggplot2 graphs. The bookdown Lite template theme supports code folding.

The traditional linear regression trend, Modified Mann-Kendall (MK) non-parameter trend and bootstrap trend are included in this package. Linear regression trend is rewritten by .lm.fit'. MK trend is rewritten by Rcpp'. Finally, those functions are about 10 times faster than previous version in R. Reference: Hamed, K. H., & Rao, A. R. (1998). A modified Mann-Kendall trend test for autocorrelated data. Journal of hydrology, 204(1-4), 182-196. <doi:10.1016/S0022-1694(97)00125-X>.

Mimic the style of traditional reporting macros for clinical trials. The purpose is to generate tables, listings and figures that support clinical research. This package is well suited for firms or individuals who wish to incorporate R without changing their ways of working as it follows a traditional clinical research workflow. Invoke functions (instead of macros) to summarize data and produce formatted reports. This package differs from others in that it includes tools (wrappers) for both analyzing and reporting data.

Automatically flags common spatial errors in biological collection data using metadata and specialists information. RuHere implements a workflow to manage occurrence data through six steps: dataset merging, metadata flagging, validation against expert-derived distribution maps, visualization of flagged records, and sampling bias exploration. It specifically integrates specialist-curated range information to identify geographic errors and introductions that often escape standard automated validation procedures. For details on the methodology, see: Trindade & Caron (2026) <doi:10.64898/2026.02.02.703373>.

The stageR package allows automated stage-wise analysis of high-throughput gene expression data. The method is published in Genome Biology at https://genomebiology.biomedcentral.com/articles/10.1186/s13059-017-1277-0.

This package identifies differential expression in high-throughput count data, such as that derived from next-generation sequencing machines, calculating estimated posterior likelihoods of differential expression (or more complex hypotheses) via empirical Bayesian methods.

This package provides a set of annotation maps describing the entire Human Disease Ontology. The annotation data comes from https://github.com/DiseaseOntology/HumanDiseaseOntology/tree/main/src/ontology.

This package provides an efficient interface to MPI by utilizing S4 classes and methods with a focus on Single Program/Multiple Data (SPMD) parallel programming style, which is intended for batch parallel execution.

This package provides functions for analyzing multivariate data. Dependencies of the distribution of the specified variable (response variable) to other variables (explanatory variables) are derived and evaluated by the Akaike Information Criterion (AIC).

Ruby-FFI is a Ruby extension for programmatically loading dynamic libraries, binding functions within them, and calling those functions from Ruby code. Moreover, a Ruby-FFI extension works without changes on Ruby and JRuby.

This package provides a Common Lisp library for fetching and parsing RSS feeds data via HTTP. Currently, it supports RSS versions 0.90, 0.91, and 0.92 as well as RSS version 2.

rust-swc is a typescript/javascript compiler. It consumes a javascript or typescript file which uses recently added features like async-await and emits javascript code which can be executed on old browsers.

Retrieves condition-specific variants in RNA-seq data (SNVs, alternative-splicings, indels). It has been developed as a post-treatment of KisSplice but can also be used with user's own data.

Gut 16S sequencing expression data from 992 healthy and moderate-to-severe diarrhetic samples used in Diarrhea in young children from low-income countries leads to large-scale alterations in intestinal microbiota composition'.

This package provides a system to facilitate brand identity management using the brand.yml standard, providing functions to consistently access and apply brand colors, typography, and other visual elements across your R projects.

Full Bayesian estimation of Multidimensional Generalized Graded Unfolding Model (MGGUM) using rstan (See Stan Development Team (2020) <https://mc-stan.org/>). Functions are provided for estimation, result extraction, model fit statistics, and plottings.

Bindings to badgen <https://www.npmjs.com/package/badgen> to generate beautiful svg badges in R without internet access. Images can be converted to png using the rsvg package as shown in examples.

This package provides easy and consistent time conversion for public health purposes. The time conversion functions provided here are between date, ISO week, ISO yearweek, ISO year, calendar month/year, season, season week.

Retrieves historical versions of clinical trial registry entries from <https://ClinicalTrials.gov>. Package functionality and implementation for v 1.0.0 is documented in Carlisle (2022) <DOI:10.1371/journal.pone.0270909>.

This package provides methods for performing fMRI quality assurance (QA) measurements of test objects. Heavily based on the fBIRN procedures detailed by Friedman and Glover (2006) <doi:10.1002/jmri.20583>.

Supply implementation to model generalized multivariate functional data using Bayesian additive mixed models of R package bamlss via a latent Gaussian process (see Umlauf, Klein, Zeileis (2018) <doi:10.1080/10618600.2017.1407325>).

This package provides tools for the generalized logistic distribution (Type I, also known as skew-logistic distribution), encompassing basic distribution functions (p, q, d, r, score), maximum likelihood estimation, and structural change methods.

Variable selection deviation (VSD) measures and instability tests for high-dimensional model selection methods such as LASSO, SCAD and MCP, etc., to decide whether the sparse patterns identified by those methods are reliable.

This package provides user-friendly functions for programmatic access to macroeconomic data from the International Monetary Fund's SDMX 3.0 IMF Data API <https://data.imf.org/en/Resource-Pages/IMF-API>.