This package provides access to a copy of the Human Cell Atlas, but with harmonised metadata. This allows for uniform querying across numerous datasets within the Atlas using common fields such as cell type, tissue type, and patient ethnicity. Usage involves first querying the metadata table for cells of interest, and then downloading the corresponding cells into a SingleCellExperiment object.

This package implements a DelayedArray of random values where the realization of the sampled values is delayed until they are needed. Reproducible sampling within any subarray is achieved by chunking where each chunk is initialized with a different random seed and stream. The usual distributions in the stats package are supported, along with scalar, vector and arrays for the parameters.

Cluster analysis with compositional data using the alpha--transformation. Relevant papers include: Tsagris M. and Kontemeniotis N. (2025). Lobachevskii Journal of Mathematics <doi:10.1134/S1995080225613700>. Tsagris M.T., Preston S. and Wood A.T.A. (2011), <doi:10.48550/arXiv.1106.1451>. Garcia-Escudero Luis A., Gordaliza Alfonso, Matran Carlos, Mayo-Iscar Agustin. (2008), <doi:10.1214/07-AOS515>.

An inverse probability of censoring weighted (IPCW) targeted maximum likelihood estimator (TMLE) for evaluating a marginal point treatment effect from data where some variables were collected on only a subset of participants using a two-stage design (or marginal mean outcome for a single arm study). A TMLE for conditional parameters defined by a marginal structural model (MSM) is also available.

This package contain functions to run genomic instability analysis (GIA) from scRNA-Seq data. GIA estimates the association between gene expression and genomic location of the coding genes. It uses the aREA algorithm to quantify the enrichment of sets of contiguous genes (loci-blocks) on the gene expression profiles and estimates the Genomic Instability Score (GIS) for each analyzed cell.

This package provides functions to perform missing value imputation with compositional data using the Jensen-Shannon divergence based k--NN and a--k--NN algorithms. The functions are based on the following paper: Tsagris M., Alenazi A. and Stewart C. (2026). "A Jensen--Shannon divergence based k--NN algorithm for missing value imputation in compositional data", <doi:10.1080/02664763.2026.2677908>.

This package implements regression models for circular response data, including homogeneous angular regression, consensus angular regression, a two-step workflow, selected special-case model wrappers, and a random-intercept extension for clustered circular outcomes. The main methodology follows Rivest et al. (2016) "A General Angular Regression Model for the Analysis of Data on Animal Movement in Ecology" <doi:10.1111/rssc.12124>.

This package implements RetryClient for aiohttp to retry connection to provided endpoint with timeouts logic or use:

• ExponentialRetry with exponential backoff

• RandomRetry for random backoff

• ListRetry with backoff you predefine by list

• FibonacciRetry with backoff that looks like fibonacci sequence

• JitterRetry exponential retry with a bit of randomness

The statistical analysis of circular data using distributions based on symmetric Nonnegative Trigonometric Sums (NNTS). It includes functions to perform empirical analysis and estimate the parameters of density functions. Fernandez-Duran, J.J. and Gregorio-Dominguez, M.M. (2025), "Multimodal Symmetric Circular Distributions Based on Nonnegative Trigonometric Sums and a Likelihood Ratio Test for Reflective Symmetry", <doi:10.48550/arXiv.2412.19501>.

Presentation two independence tests for two-way, three-way and four-way contingency tables. These tests are: the modular test and the logarithmic minimum test. For details on this method see: Sulewski (2017) <doi:10.18778/0208-6018.330.04>, Sulewski (2018) <doi:10.1080/02664763.2018.1424122>, Sulewski (2019) <doi:10.2478/bile-2019-0003>, Sulewski (2021) <doi:10.1080/00949655.2021.1908286>.

We perform general mediation analysis in the Bayesian setting using the methods described in Yu and Li (2022, ISBN:9780367365479). With the package, the mediation analysis can be performed on different types of outcomes (e.g., continuous, binary, categorical, or time-to-event), with default or user-defined priors and predictive models. The Bayesian estimates and credible sets of mediation effects are reported as analytic results.

Recoll is a local search engine that knows how to index a wide variety of file formats, including PDFs, org and other text files and emails. It also offers a sophisticated query language, and, for some document kinds, snippets in the found documents actually matching the query at hand. This package provides an emacs interface to perform recoll queries, and display its results, via emacs-consult.

Allows local bone density estimates to be derived from CT data and mapped to 3D bone models in a reproducible manner. Processing can be performed at the individual bone or group level. Also includes tools for visualizing the bone density estimates. Example methods are described in Telfer et al., (2021) <doi:10.1002/jor.24792>, Telfer et al., (2021) <doi:10.1016/j.jse.2021.05.011>.

Facilitates the creation of xpose data objects from Nonlinear Mixed Effects (NLME) model outputs produced by Certara.RsNLME or Phoenix NLME. This integration enables users to utilize all ggplot2'-based plotting functions available in xpose for thorough model diagnostics and data visualization. Additionally, the package introduces specialized plotting functions tailored for covariate model evaluation, extending the analytical capabilities beyond those offered by xpose alone.

This package provides a set of functions to investigate raw data from (metabol)omics experiments intended to be used on a raw data matrix, i.e. following peak picking and signal deconvolution. Functions can be used to normalize data, detect biomarkers and perform sample classification. A detailed description of best practice usage may be found in the publication <doi:10.1007/978-1-4939-7819-9_20>.

U-Boot is a bootloader used mostly for ARM boards. It also initializes the boards (RAM etc).

It allows network booting and uses the device-tree from the firmware, allowing the usage of overlays. It can act as an EFI firmware for the grub-efi-netboot-removable-bootloader. This is a common 64-bit build of U-Boot for all 64-bit capable Raspberry Pi variants.

This package provides a unified set of helper functions to access datasets from the Cincinnati Open Data platform <https://data.cincinnati-oh.gov/>. Functions return results as tidy tibbles and support optional filtering, sorting, and row limits via the Socrata API. The package provides a consistent interface for discovering and downloading datasets from the Cincinnati Open Data Portal using human-readable dataset keys or official Socrata dataset identifiers.

This package provides a port of the matrixStats API for use with DelayedMatrix objects from the DelayedArray package. It contains high-performing functions operating on rows and columns of DelayedMatrix objects, e.g. colMedians, rowMedians, colRanks, rowRanks, colSds, and rowSds. Functions are optimized per data type and for subsetted calculations such that both memory usage and processing time is minimized.

U-Boot is a bootloader used mostly for ARM boards. It also initializes the boards (RAM etc).

It allows network booting and uses the device-tree from the firmware, allowing the usage of overlays. It can act as an EFI firmware for the grub-efi-netboot-removable-bootloader. This is a 32-bit build of U-Boot.

This package only contains the file u-boot.bin.

This package provides some commands (in French) to perform calculations on small (2x2 or 3x3 or 4x4) linear systems, with xint or pyluatex:

• \DetMatrice or \DetMatricePY to display the determinant of a matrix;

• \MatriceInverse or \MatriceInversePY to display the inverse of a matrix;

• \SolutionSysteme or \SolutionSystemePY to display the solution of a linear system;

• …

These are harmonized datasets produced as part of the Clinical Trials Network (CTN) protocol number 0094. This is a US National Institute of Drug Abuse (NIDA) funded project; to learn more go to <https://ctnlibrary.org/protocol/ctn0094/>. These are datasets which have the data harmonized from CTN-0027 (<https://ctnlibrary.org/protocol/ctn0027/>), CTN-0030 (<https://ctnlibrary.org/protocol/ctn0030/>), and CTN-0051 (<https://ctnlibrary.org/protocol/ctn0051/>).

Out-of-box, Citar provides default support for file-per-note bibliographic notes that are compatible with Org-Roam v2. This package integrates directly with the Org-Roam database, and provides the following additional features to Citar note support:

• multiple references per note

• multiple reference notes per file

• ability to query note citations by reference

• ``live'' updating of Citar UI for presence of notes

This package provides tools to analysis of experiments having two or more quantitative explanatory variables and one quantitative dependent variable. Experiments can be without repetitions or with a statistical design (Hair JF, 2016) <ISBN: 13: 978-0138132637>. Pacote para uma analise de experimentos havendo duas ou mais variaveis explicativas quantitativas e uma variavel dependente quantitativa. Os experimentos podem ser sem repeticoes ou com delineamento estatistico (Hair JF, 2016) <ISBN: 13: 978-0138132637>.

Application to estimate statistical values using properties provided by a group of individuals to describe concepts using shiny'. It estimates the underlying distribution to generate new descriptive words Canessa et al. (2023) <doi:10.3758/s13428-022-01811-w>, applies a new clustering model, and uses simulations to estimate the probability that two persons describe the same words based on their descriptions Canessa et al. (2022) <doi:10.3758/s13428-022-02030-z>.