Test hypotheses and construct confidence intervals for AUC (area under Receiver Operating Characteristic curve) and pAUC (partial area under ROC curve), from the given two samples of test data with disease/healthy subjects. The method used is based on TWO SAMPLE empirical likelihood and PROFILE empirical likelihood, as described in <https://www.ms.uky.edu/~mai/research/eAUC1.pdf>.

Estimation of the cutpoint defined by the Generalized Symmetry point in a binary classification setting based on a continuous diagnostic test or marker. Two methods have been implemented to construct confidence intervals for this optimal cutpoint, one based on the Generalized Pivotal Quantity and the other based on Empirical Likelihood. Numerical and graphical outputs for these two methods are easily obtained.

Simulating single cell RNA-seq data with complicated structure. This package is developed based on the Splat method (Zappia, Phipson and Oshlack (2017) <doi:10.1186/s13059-017-1305-0>). GeneScape incorporates additional features to simulate single cell RNA-seq data with complicated differential expression and correlation structures, such as sub-cell-types, correlated genes (pathway genes) and hub genes.

Estimation procedures and goodness-of-fit test for several Markov regime switching models and mixtures of bivariate copula models. The goodness-of-fit test is based on a Cramer-von Mises statistic and uses Rosenblatt's transform and parametric bootstrap to estimate the p-value. The proposed methodologies are described in Nasri, Remillard and Thioub (2020) <doi:10.1002/cjs.11534>.

This package provides a simple and effective tool for computing and visualizing statistical power for meta-analysis, including power analysis of main effects (Jackson & Turner, 2017)<doi:10.1002/jrsm.1240>, test of homogeneity (Pigott, 2012)<doi:10.1007/978-1-4614-2278-5>, subgroup analysis, and categorical moderator analysis (Hedges & Pigott, 2004)<doi:10.1037/1082-989X.9.4.426>.

This package provides a low-dependency implementation of GSIF::mpspline() <https://r-forge.r-project.org/scm/viewvc.php/pkg/R/mpspline.R?view=markup&revision=240&root=gsif>, which applies a mass-preserving spline to soil attributes. Splining soil data is a safe way to make continuous down-profile estimates of attributes measured over discrete, often discontinuous depth intervals.

Prediction limits for the Poisson distribution are produced from both frequentist and Bayesian viewpoints. Limiting results are provided in a Bayesian setting with uniform, Jeffreys and gamma as prior distributions. More details on the methodology are discussed in Bejleri and Nandram (2018) <doi:10.1080/03610926.2017.1373814> and Bejleri, Sartore and Nandram (2021) <doi:10.1007/s42952-021-00157-x>.

Send requests to the PurpleAir Application Programming Interface (API; <https://community.purpleair.com/c/data/api/18>). Check a PurpleAir API key and get information about the related organization. Download real-time data from a single PurpleAir sensor or many sensors by sensor identifier, geographical bounding box, or time since modified. Download historical data from a single sensor.

Work with containers over the Docker API. Rather than using system calls to interact with a docker client, using the API directly means that we can receive richer information from docker. The interface in the package is automatically generated using the OpenAPI (a.k.a., swagger') specification, and all return values are checked in order to make them type stable.

Aggregates large single-cell data into metacell dataset by merging together gene expression of very similar cells. SuperCell uses velocyto.R <doi:10.1038/s41586-018-0414-6> <https://github.com/velocyto-team/velocyto.R> for RNA velocity. We also recommend installing scater Bioconductor package <doi:10.18129/B9.bioc.scater> <https://bioconductor.org/packages/release/bioc/html/scater.html>.

This package provides a user-friendly wrapper for web automation, using either chromote or selenium'. Provides a simple and consistent API to make web scraping and testing scripts easy to write and understand. Elements are lazy, and automatically wait for the website to be valid, resulting in reliable and reproducible code, with no visible impact on the experience of the programmer.

This package provides function for area level of small area estimation using hierarchical Bayesian (HB) method with Zero-Inflated Binomial distribution for variables of interest. Some dataset produced by a data generation are also provided. The rjags package is employed to obtain parameter estimates. Model-based estimators involves the HB estimators which include the mean and the variation of mean.

Here we provide tools for the computation and factorization of high-dimensional tensor products that are formed by smaller matrices. The methods are based on properties of Kronecker products (Searle 1982, p. 265, ISBN-10: 0470009616). We evaluated this methodology by benchmark testing and illustrated its use in Gaussian Linear Models ('Lopez-Cruz et al., 2024') <doi:10.1093/g3journal/jkae001>.

The goal of tidyplate is to help researchers convert different types of microplates into tibbles which can be used in data analysis. It accepts xlsx and csv files formatted in a specific way as input. It supports all types of standard microplate formats such as 6-well, 12-well, 24-well, 48-well, 96-well, 384-well, and, 1536-well plates.

This package is an extension to CellNOptR. It contains additional functionality needed to simulate and train a prior knowledge network to experimental data using constrained fuzzy logic (cFL, rather than Boolean logic as is the case in CellNOptR). Additionally, this package will contain functions to use for the compilation of multiple optimization results (either Boolean or cFL).

gINTomics is an R package for Multi-Omics data integration and visualization. gINTomics is designed to detect the association between the expression of a target and of its regulators, taking into account also their genomics modifications such as Copy Number Variations (CNV) and methylation. What is more, gINTomics allows integration results visualization via a Shiny-based interactive app.

This package provides an R API and htmlwidget facilitating interactive visualization of spatial single-cell data with Vitessce. The R API contains classes and functions for loading single-cell data stored in compatible on-disk formats. The htmlwidget is a wrapper around the Vitessce JavaScript library and can be used in the Viewer tab of RStudio or Shiny apps.

The ACE file format is used in genomics to store contigs from sequencing machines. This tools converts it into FASTQ format. Both formats contain the sequence characters and their corresponding quality information. Unlike the FASTQ file, the ACE file stores the quality values numerically. The conversion algorithm uses the standard Sanger formula. The package facilitates insertion into pipelines, and content inspection.

This package provides a collection of tools to evaluate probability density functions, cumulative distribution functions, quantile functions and random numbers for truncated random variables. These functions are provided to also compute the expected value and variance. Q-Q plots can be produced. All the probability functions in the stats, stats4 and evd packages are automatically available for truncation.

'Apache' 'Arrow' <https://arrow.apache.org/> is a cross-language development platform for in-memory data. It specifies a standardized language-independent columnar memory format for flat and hierarchical data, organized for efficient analytic operations on modern hardware. This package provides an interface to the 'Arrow C++' library. Unlike 'r-arrow', this package is compiled with the Apache Arrow C++ libraries.

This package provides a software that implements a method for partitioning genetic trends to quantify the sources of genetic gain in breeding programmes. The partitioning method is described in Garcia-Cortes et al. (2008) <doi:10.1017/S175173110800205X>. The package includes the main function AlphaPart for partitioning breeding values and auxiliary functions for manipulating data and summarizing, visualizing, and saving results.

R Interface to AutoKeras <https://autokeras.com/>. AutoKeras is an open source software library for Automated Machine Learning (AutoML). The ultimate goal of AutoML is to provide easily accessible deep learning tools to domain experts with limited data science or machine learning background. AutoKeras provides functions to automatically search for architecture and hyperparameters of deep learning models.

This package provides methods to deal with under sampling in ecological bipartite networks from Terry and Lewis (2020) Ecology <doi:10.1002/ecy.3047> Includes tools to fit a variety of statistical network models and sample coverage estimators to highlight most likely missing links. Also includes simple functions to resample from observed networks to generate confidence intervals for common ecological network metrics.

Allow to run Cppcheck (<https://cppcheck.sourceforge.io/>) on C and C++ files with a R command or a RStudio addin. The report appears in the RStudio viewer pane as a formatted HTML file. It is also possible to get this report with a shiny application. Cppcheck can spot many error types and it can also give some recommendations on the code.