Datasets and wrapper functions for tidyverse-friendly introductory linear regression, used in "Statistical Inference via Data Science: A ModernDive into R and the Tidyverse" available at <https://moderndive.com/>.

Implementation of two p-value combination techniques (inverse normal and Fisher methods). A vignette is provided to explain how to perform a meta-analysis from two independent RNA-seq experiments.

The Needleman-Wunsch global alignment algorithm can be used to find approximate matches between sample names in different data sets. See Wang et al. (2010) <doi:10.4137/CIN.S5613>.

Generation of count (assuming Poisson distribution) and continuous data (using Fleishman polynomials) simultaneously. The details of the method are explained in Demirtas et al. (2012) <DOI:10.1002/sim.5362>.

Tokenizers break text into pieces that are more usable by machine learning models. Many tokenizers share some preparation steps. This package provides those shared steps, along with a simple tokenizer.

This package provides a series of checks to identify common issues in Study Data Tabulation Model (SDTM) datasets. These checks are intended to be generalizable, actionable, and meaningful for analysis.

This package provides a small set of functions wrapping up the call stack and command line inspection needed to determine a running script's filename from within the script itself.

This package provides methods for sampling contact matrices from diary data for use in infectious disease modelling, as discussed in Mossong et al. (2008) <doi:10.1371/journal.pmed.0050074>.

This package contains functions to standardize tracheid profiles using the traditional method (Vaganov) and a new method to standardize tracheidograms based on the relative position of tracheids within tree rings.

Two- and three-dimensional morphometric maps of enamel and dentine thickness and multivariate analysis. Volume calculation of dental materials. Principal component analysis of thickness maps with associated morphometric map variations.

This package provides tools to visualize oligonucleotide patterns and sequence motif occurrences across a large set of sequences centred at a common reference point and sorted by a user defined feature.

This package provides two methods of plotting categorical scatter plots such that the arrangement of points within a category reflects the density of data at that region, and avoids over-plotting.

This package provides tools for creating, viewing, and assessing qualitative palettes with many (20-30 or more) colors. See Coombes and colleagues (2019) https://doi:10.18637/jss.v090.c01.

This package provides alluvial plots for ggplot2. Alluvial plots use variable-width ribbons and stacked bar plots to represent multi-dimensional or repeated-measures data with categorical or ordinal variables.

Net::SSH is a pure-Ruby implementation of the SSH2 client protocol. It allows you to write programs that invoke and interact with processes on remote servers, via SSH2.

Launchy is helper class for launching applications in a fire and forget manner. The aim of Launchy is to provide a common approach to launching external applications from within Ruby programs.

This package provides a flexible and streamlined pipeline for formatting, analyzing, and visualizing omics data, regardless of omics type (e.g. transcriptomics, proteomics, metabolomics). The package includes tools for shaping input data into analysis-ready structures, fitting linear or mixed-effect models, extracting key contrasts, and generating a rich variety of ready-to-use publication-quality plots. Designed for transparency and reproducibility across a wide range of study designs, with customizable components for statistical modeling.

Implementation of a Principal Component Analysis (PCA) in the torus via density ridge estimation. The main function, ridge_pca(), obtains the relevant density ridge for bivariate sine von Mises and bivariate wrapped Cauchy distribution models and provides the associated scores and variance decomposition. Auxiliary functions for evaluating, fitting, and sampling these models are also provided. The package provides replicability to Garcà a-Portugués and Prieto-Tirado (2023) <doi:10.1007/s11222-023-10273-9>.

This package provides a useful statistical tool for the construction and analysis of Honeycomb Selection Designs. More information about this type of designs: Fasoula V. (2013) <doi:10.1002/9781118497869.ch6> Fasoula V.A., and Tokatlidis I.S. (2012) <doi:10.1007/s13593-011-0034-0> Fasoulas A.C., and Fasoula V.A. (1995) <doi:10.1002/9780470650059.ch3> Tokatlidis I. (2016) <doi:10.1017/S0014479715000150> Tokatlidis I., and Vlachostergios D. (2016) <doi:10.3390/d8040029>.

Simple animated versions of basic R plots, using the animation package. Includes animated versions of plot, barplot, persp, contour, filled.contour, hist, curve, points, lines, text, symbols, segments, and arrows.

This package provides a function for fitting Poisson and negative binomial regression models when the number of parameters exceeds the sample size, using the the generalized monotone incremental forward stagewise method.

Estimates latent class vector-autoregressive models via EM algorithm on time-series data for model-based clustering and classification. Includes model selection criteria for selecting the number of lags and clusters.

Apply the Deductive Rational Method to a monthly series of flow or precipitation data to fill in missing data. The method is as described in: Campos, D.F., (1984, ISBN:9686194444).

Helpers functions to process, analyse, and visualize the output of single locus species delimitation methods. For full functionality, please install suggested software at <https://legallab.github.io/delimtools/articles/install.html>.