Exploit controlled vocabularies organized on tematres servers.

Inverse normal transformation (INT) based genetic association testing. These tests are recommend for continuous traits with non-normally distributed residuals. INT-based tests robustly control the type I error in settings where standard linear regression does not, as when the residual distribution exhibits excess skew or kurtosis. Moreover, INT-based tests outperform standard linear regression in terms of power. These tests may be classified into two types. In direct INT (D-INT), the phenotype is itself transformed. In indirect INT (I-INT), phenotypic residuals are transformed. The omnibus test (O-INT) adaptively combines D-INT and I-INT into a single robust and statistically powerful approach. See McCaw ZR, Lane JM, Saxena R, Redline S, Lin X. "Operating characteristics of the rank-based inverse normal transformation for quantitative trait analysis in genome-wide association studies" <doi:10.1111/biom.13214>.

Extension to REddyProc that allows reading data from netCDF files.

Defines functions that can be used to collect provenance as an R script executes or during a console session. The output is a text file in PROV-JSON format.

This package provides functions to analyse DNA fragment samples (i.e. derived from RFLP-analysis) and standalone BLAST report files (i.e. DNA sequence analysis).

Interactive data tables for R, based on the React Table JavaScript library. Provides an HTML widget that can be used in R Markdown or Quarto documents, Shiny applications, or viewed from an R console.

Evaluates R source codes by variable and/or functions names. Similar source codes should deliver similarity coefficients near one. Since neither the frequency nor the order of the used names is considered, a manual inspection of the R source code is required to check for similarity. Possible use cases include detection of code clones for improving software quality and of plagiarism amongst students assignments.

Generates random walks of various types by providing a set of functions that are compatible with the tidyverse'. The functions provided in the package make it simple to create random walks with a variety of properties, such as how many simulations to run, how many steps to take, and the distribution of random walk itself.

This package provides the user with functions to develop their trading strategy, uncover actionable trading ideas, and monitor consensus shifts with crowdsourced earnings and economic estimate data directly from <www.estimize.com>. Further information regarding the web services this package invokes can be found at <www.estimize.com/api>.

Implementation of the following methods for event history analysis. Risk regression models for survival endpoints also in the presence of competing risks are fitted using binomial regression based on a time sequence of binary event status variables. A formula interface for the Fine-Gray regression model and an interface for the combination of cause-specific Cox regression models. A toolbox for assessing and comparing performance of risk predictions (risk markers and risk prediction models). Prediction performance is measured by the Brier score and the area under the ROC curve for binary possibly time-dependent outcome. Inverse probability of censoring weighting and pseudo values are used to deal with right censored data. Lists of risk markers and lists of risk models are assessed simultaneously. Cross-validation repeatedly splits the data, trains the risk prediction models on one part of each split and then summarizes and compares the performance across splits.

Calculation of ratios between two data sets containing environmental data like element concentrations by different methods. Additionally plant element concentrations can be corrected for adhering particles (soil, airborne dust).

Electrical properties of resistor networks using matrix methods.

The Brazilian Central Bank API delivers many datasets which regard economic activity, regional economy, international economy, public finances, credit indicators and many more. For more information please see <http://dadosabertos.bcb.gov.br/>. These datasets can be accessed through rbcb functions and can be obtained in different data structures common to R ('tibble', data.frame', xts', ...).

PDF tools based on the Poppler PDF rendering library. See <http://poppler.freedesktop.org/> for more information on Poppler.

Clinical care data from 130 U.S. hospitals in the years 1999-2008 adapted from the study Strack et al. (2014) <doi:10.1155/2014/781670>. Each row describes an "encounter" with a patient with diabetes, including variables on demographics, medications, patient history, diagnostics, payment, and readmission.

Access and handle APIs that use the international open311 GeoReport v2 standard for civic issue tracking <https://wiki.open311.org/GeoReport_v2/>. Retrieve civic service types and request data. Select and add available open311 endpoints and jurisdictions. Implicitly supports custom queries and open311 extensions. Requires a minimal number of hard dependencies while still allowing the integration in common R formats ('xml2', tibble', sf').

This package provides functionality for carrying out sample size estimation and power calculation in Respondent-Driven Sampling.

Encode network data as strings of printable ASCII characters. Implemented functions include encoding and decoding adjacency matrices, edgelists, igraph, and network objects to/from formats graph6', sparse6', and digraph6'. The formats and methods are described in McKay, B.D. and Piperno, A (2014) <doi:10.1016/j.jsc.2013.09.003>.

Network-based regularization has achieved success in variable selection for high-dimensional biological data due to its ability to incorporate correlations among genomic features. This package provides procedures of network-based variable selection for generalized linear models (Ren et al. (2017) <doi:10.1186/s12863-017-0495-5> and Ren et al.(2019) <doi:10.1002/gepi.22194>). Continuous, binary, and survival response are supported. Robust network-based methods are available for continuous and survival responses.

Encrypt R objects to a raw vector or file using modern cryptographic techniques. Password-based key derivation is with Argon2 (<https://en.wikipedia.org/wiki/Argon2>). Objects are serialized and then encrypted using XChaCha20-Poly1305 (<https://en.wikipedia.org/wiki/ChaCha20-Poly1305>) which follows RFC 8439 for authenticated encryption (<https://en.wikipedia.org/wiki/Authenticated_encryption>). Cryptographic functions are provided by the included monocypher C library (<https://monocypher.org>).

Reference database manager offering a set of functions to import, organize, clean, filter, audit and export reference genetic data. Provide functions to download sequence data from NCBI GenBank <https://www.ncbi.nlm.nih.gov/genbank/>. Designed as an environment for semi-automatic and assisted construction of reference databases and to improve standardization and repeatability in barcoding and metabarcoding studies.

This package provides an intuitive and user-friendly interface for working with emojis in R'. It allows users to search, insert, and manage emojis by keyword, category, or through an interactive shiny'-based drop-down. The package enables integration of emojis into R scripts, R Markdown', Quarto', shiny apps, and ggplot2 plots. Also includes built-in mappings for commit messages, useful for version control. It builds on established emoji libraries and Unicode standards, adding expressiveness and visual cues to documentation, user interfaces, and reports. For more details see Emojipedia (2024) <https://emojipedia.org> and GitHub Emoji Cheat Sheet <https://github.com/ikatyang/emoji-cheat-sheet/tree/master>.

Analysis of corneal data obtained from a Placido disk corneal topographer with calculation of irregularity indices. This package performs analyses of corneal data obtained from a Placido disk corneal topographer, with the calculation of the Placido irregularity indices and the posterior analysis. The package is intended to be easy to use by a practitioner, providing a simple interface and yielding easily interpretable results. A corneal topographer is an ophthalmic clinical device that obtains measurements in the cornea (the anterior part of the eye). A Placido disk corneal topographer makes use of the Placido disk [Rowsey et al. (1981)]<doi:10.1001/archopht.1981.03930011093022>, which produce a circular pattern of measurement nodes. The raw information measured by such a topographer is used by practitioners to analyze curvatures, to study optical aberrations, or to diagnose specific conditions of the eye (e.g. keratoconus, an important corneal disease). The rPACI package allows the calculation of the corneal irregularity indices described in [Castro-Luna et al. (2020)]<doi:10.1016%2Fj.clae.2019.12.006>, [Ramos-Lopez et al. (2013)]<doi:10.1097%2FOPX.0b013e3182843f2a>, and [Ramos-Lopez et al. (2011)]<doi:10.1097/opx.0b013e3182279ff8>. It provides a simple interface to read corneal topography data files as exported by a typical Placido disk topographer, to compute the irregularity indices mentioned before, and to display summary plots that are easy to interpret for a clinician.

Measuring information flow between time series with Shannon and Rényi transfer entropy. See also Dimpfl and Peter (2013) <doi:10.1515/snde-2012-0044> and Dimpfl and Peter (2014) <doi:10.1016/j.intfin.2014.03.004> for theory and applications to financial time series. Additional references can be found in the theory part of the vignette.