This package implements transcript quantification import from Salmon and alevin with automatic attachment of transcript ranges and release information, and other associated metadata. De novo transcriptomes can be linked to the appropriate sources with linkedTxomes and shared for computational reproducibility.

PSIplot is an R package for generating plots of percent spliced-in (PSI) values of alternatively-spliced exons that were computed by vast-tools, an RNA-Seq pipeline for alternative splicing analysis. The plots are generated using ggplot2.

This package provides a collection of functions to compute the standardized effect sizes for experiments (Cohen d, Hedges g, Cliff delta, Vargha-Delaney A). The computation algorithms have been optimized to allow efficient computation even with very large data sets.

This package provides functionality to assert conditions that have to be met so that errors in data used in analysis pipelines can fail quickly. It is similar to stopifnot() but more powerful, friendly, and easier for use in pipelines.

This package enables you to estimate the p-values for predictors x against target variable y in Lasso regression, using the regularization strength when each predictor enters the active set of regularization path for the first time as the statistic.

Webshot makes it easy to take screenshots of web pages from within R. It can also run Shiny applications locally and take screenshots of the application; and it can render and screenshot static as well as interactive R Markdown documents.

The lattice package provides a powerful and elegant high-level data visualization system inspired by Trellis graphics, with an emphasis on multivariate data. Lattice is sufficient for typical graphics needs, and is also flexible enough to handle most nonstandard requirements.

Simulate multivariate data with arbitrary marginal distributions. bigsimr is a package for simulating high-dimensional multivariate data with a target correlation and arbitrary marginal distributions via Gaussian copula. It utilizes the Julia package Bigsimr.jl for its core routines.

Permutational method to incorporate taxonomic uncertainty and some functions to assess its effects on parameters of some widely used multivariate methods in ecology, as explained in Cayuela et al. (2011) <doi:10.1111/j.1600-0587.2009.05899.x>.

This package produces formal landscape PDF certificates with configurable color themes, optional logos, decorative borders, laurels, and corner ornaments. Built on grid with no external LaTeX or Quarto dependency. Suitable for academic awards, professional recognition, and similar uses.

Explore and normalize American campaign finance data. Created by the Investigative Reporting Workshop to facilitate work on The Accountability Project, an effort to collect public data into a central, standard database that is more easily searched: <https://publicaccountability.org/>.

This package provides text-based summaries and analysis tools for profvis profiling output. Designed for terminal workflows and artificial intelligence (AI) agent consumption, offering views including hotspot analysis, call trees, source context, caller/callee relationships, and memory allocation breakdowns.

This package implements fast algorithms for kernel quantile regression and related models, including non-crossing kernel quantile regression and regularized linear quantile regression. The methods are described in Tang, Gu and Wang (2026) <doi:10.1080/10618600.2025.2541004>.

Uses jackknife and bootstrap methods to quantify the sampling uncertainty in goodness-of-fit statistics. Full details are in Clark et al. (2021), "The abuse of popular performance metrics in hydrologic modeling", Water Resources Research, <doi:10.1029/2020WR029001>.

Features the marginal parametric and semi-parametric proportional hazards mixture cure models for analyzing clustered survival data with a possible cure fraction. A reference is Yi Niu and Yingwei Peng (2014) <doi:10.1016/j.jmva.2013.09.003>.

An implementation of the International Association for the Properties of Water (IAPWS) Formulation 1995 for the Thermodynamic Properties of Ordinary Water Substance for General and Scientific Use and on the releases for viscosity, conductivity, surface tension and melting pressure.

Multi-data type subtyping, which is data type agnostic and accepts missing data. Subtyping is performed using intermediary assessments created with autoencoders and similarity calculations. See Fox et al. (2024) <doi:10.1016/j.crmeth.2024.100884> for details.

Imputation of incomplete continuous or categorical datasets; Missing values are imputed with a principal component analysis (PCA), a multiple correspondence analysis (MCA) model or a multiple factor analysis (MFA) model; Perform multiple imputation with and in PCA or MCA.

The companion package provides all original data sets and functions that are used in the book "Model-Based Clustering and Classification for Data Science" by Charles Bouveyron, Gilles Celeux, T. Brendan Murphy and Adrian E. Raftery (2019, ISBN:9781108644181).

This package provides modules as an organizational unit for source code. Modules enforce to be more rigorous when defining dependencies and have a local search path. They can be used as a sub unit within packages or in scripts.

Data-driven approach for Exploratory Factor Analysis (EFA) that uses Model Implied Instrumental Variables (MIIVs). The method starts with a one factor model and arrives at a suggested model with enhanced interpretability that allows cross-loadings and correlated errors.

This package provides methods for modeling moderator variables in cross-sectional, temporal, and multi-level networks. Includes model selection techniques and a variety of plotting functions. Implements the methods described by Swanson (2020) <https://www.proquest.com/openview/d151ab6b93ad47e3f0d5e59d7b6fd3d3>.

This package provides methods for determining optimum plot size and shape in field experiments using Fairfield-Smith's variance law approach. It will evaluate field variability, determine optimum plot size and shape and study fertility trends across the field.

Data from All the World's Primates relational SQL database and other tabular datasets are made available via drivers and connection functions. Additionally we provide several functions and examples to facilitate the merging and aggregation of these tabular inputs.