This package implements a system of linear equations to recover unreported diagnostic test accuracy cell counts from commonly reported measures such as sensitivity, specificity, predictive values, prevalence, and sample size. The package is intended for applied researchers who require complete 2x2 table counts for downstream analyses.

Extracting desired data using the proper Census variable names can be time-consuming. This package takes the pain out of that process by providing functions to quickly locate variables and download labeled tables from the Census APIs (<https://www.census.gov/data/developers/data-sets.html>).

Query NCBI Entrez and retrieve PubMed records in XML or text format. Process PubMed records by extracting and aggregating data from selected fields. A large number of records can be easily downloaded via this simple-to-use interface to the NCBI PubMed API.

This package provides methods for searching through genealogical data and displaying the results. Plotting algorithms assist with data exploration and publication-quality image generation. Includes interactive genealogy visualization tools. Provides parsing and calculation methods for variables in descendant branches of interest. Uses the Grammar of Graphics.

The functionality provided by this package is an expansion of the code of the statebins package, created by B. Rudis (2022), <doi:10.32614/CRAN.package.statebins>. It allows for the creation of square choropleths for the entire world, provided an appropriate specified grid is supplied.

Input multiple versions of a source document, and receive HTML code for a highlighted version of the source document indicating the frequency of occurrence of phrases in the different versions. This method is described in Chapter 3 of Rogers (2024) <https://digitalcommons.unl.edu/dissertations/AAI31240449/>.

This package implements the Linear Approach to Threshold with Ergodic Rate (LATER) model, which predicts distributions of reaction times and summarises them with as little as two free parameters. Allows for easy visualisation and comparison of datasets, along with fitting of datasets using the LATER model.

This package provides unified workflows for quality control, normalization, and visualization of proteomic and metabolomic data. The package simplifies preprocessing through automated imputation, scaling, and principal component analysis (PCA)-based exploratory analysis, enabling researchers to prepare omics datasets efficiently for downstream statistical and machine learning analyses.

R version of scperturb tool for single-cell perturbation analysis. Contains wrappers for performing E-statistics for Seurat objects. More details on the method can be found in Peidli et al. (2023) <doi:10.1101/2022.08.20.504663> and in Székely and Rizzo (2004).

Some M-estimators for 1-dimensional location (Bisquare, ML for the Cauchy distribution, and the estimators from application of the smoothing principle introduced in Hampel, Hennig and Ronchetti (2011) to the above, the Huber M-estimator, and the median, main function is smoothm), and Pitman estimator.

This package provides a statistical method for reducing the number of covariates in an analysis by evaluating Variable Importance Measures (VIMPs) derived from the Random Forest algorithm. It performs statistical tests on the VIMPs and outputs whether the covariate is significant along with the p-values.

Computing the one-sided/two-sided integrated/maximally selected EL statistics for simultaneous testing, the one-sided/two-sided EL tests for pointwise testing, and an initial test that precedes one-sided testing to exclude the possibility of crossings or alternative orderings among the survival functions.

This package provides a stable approach to variable selection through stability selection and the use of a permutation-based objective stability threshold. Lima et al (2021) <doi:10.1038/s41598-020-79317-8>, Meinshausen and Buhlmann (2010) <doi:10.1111/j.1467-9868.2010.00740.x>.

Implementation of ZENIT-POLAR substitution cipher method of encryption using by default the TENIS-POLAR cipher. This last cipher of encryption became famous through the collection of Brazilian books "Os Karas" by the author Pedro Bandeira. For more details, see "A Cryptographic Dictionary" (GC&CS, 1944).

Automatically converts language-specific verbal information, e.g., "1st half of the 19th century," to its standardized numerical counterparts, e.g., "1801-01-01/1850-12-31." It follows the recommendations of the MIDAS ('Marburger Informations-, Dokumentations- und Administrations-System'), see <doi:10.11588/artdok.00003770>.

Implementation of Bayesian models for estimating object lengths and morphological relationships between object lengths using photographic data collected from drones. The Bayesian model is described in "Bayesian approach for predicting photogrammetric uncertainty in morphometric measurements derived from drones" (Bierlich et al., 2021, <doi:10.3354/meps13814>).

This package provides tools for estimating HIV incidence using cross-sectional recency testing data, adjusting for internal and external target populations and supporting subtype-specific parameters. The statistical methodology implemented builds on the framework described in Wang, Duerr, and Gao(2025) <doi:10.1002/sim.70216>.

RcisTarget identifies transcription factor binding motifs (TFBS) over-represented on a gene list. In a first step, RcisTarget selects DNA motifs that are significantly over-represented in the surroundings of the transcription start site (TSS) of the genes in the gene-set. This is achieved by using a database that contains genome-wide cross-species rankings for each motif. The motifs that are then annotated to TFs and those that have a high Normalized Enrichment Score (NES) are retained. Finally, for each motif and gene-set, RcisTarget predicts the candidate target genes (i.e. genes in the gene-set that are ranked above the leading edge).

This package provides a Poisson mixture model is implemented to cluster genes from high-throughput transcriptome sequencing (RNA-seq) data. Parameter estimation is performed using either the EM or CEM algorithm, and the slope heuristics are used for model selection (i.e., to choose the number of clusters).

Radon is a Python tool which computes various code metrics. Supported metrics are:

• raw metrics: SLOC, comment lines, blank lines, &c.

• Cyclomatic Complexity (i.e., McCabe’s Complexity)

• Halstead metrics (all of them)

• the Maintainability Index (a Visual Studio metric)

This package stores two merged expressionSet objects that contain the gene expression profile and clinical information of -a- six breast cancer cohorts and -b- four colorectal cancer cohorts. Breast cancer data are employed in the vignette of the hrunbiased package for survival analysis of gene signatures.

This package primarily identifies variants in mitochondrial genomes from BAM alignment files. It filters these variants to remove RNA editing events then estimates their evolutionary relationship (i.e. their phylogenetic tree) and groups single cells into clones. It also visualizes the mutations and providing additional genomic context.

Processes Automatic Identification System (AIS) vessel tracking data, including travel estimation, trajectory correction, interpolation, extraction, and summarising vessel information. The package is designed to facilitate reproducible analyses of maritime traffic in ecological, environmental, and marine spatial planning applications. For more details see <https://remip48.github.io/AISanalyze/>.

Deduplicates bibliographic citations from multiple sources while preserving customizable metadata, supporting data-driven search strategy development and evidence synthesis reporting. Search results can be analyzed using plots and tables, and imported or exported in RIS and CSV formats. An interactive shiny application is included for exploratory use.