Similarity regression, evaluating the probability of association between sets of ontological terms and binary response vector. A no-association model is compared with one in which the log odds of a true response is linked to the semantic similarity between terms and a latent characteristic ontological profile - Phenotype Similarity Regression for Identifying the Genetic Determinants of Rare Diseases', Greene et al 2016 <doi:10.1016/j.ajhg.2016.01.008>.

The nature of working with structured query language ('SQL') scripts efficiently often requires the creation of temporary tables and there are few clean and simple R SQL execution approaches that allow you to complete this kind of work with the R environment. This package seeks to give SQL implementations in R a little love by deploying functions that allow you to deploy complex SQL scripts within a typical R workflow.

Stationary subspace analysis (SSA) is a blind source separation (BSS) variant where stationary components are separated from non-stationary components. Several SSA methods for multivariate time series are provided here (Flumian et al. (2021); Hara et al. (2010) <doi:10.1007/978-3-642-17537-4_52>) along with functions to simulate time series with time-varying variance and autocovariance (Patilea and Raissi(2014) <doi:10.1080/01621459.2014.884504>).

Utilities for single nucleotide polymorphism (SNP) based kinship analysis testing and evaluation. The skater package contains functions for importing, parsing, and analyzing pedigree data, performing relationship degree inference, benchmarking relationship degree classification, and summarizing identity by descent (IBD) segment data. Package functions and methods are described in Turner et al. (2021) "skater: An R package for SNP-based Kinship Analysis, Testing, and Evaluation" <doi:10.1101/2021.07.21.453083>.

Sample size calculation to detect dynamic treatment regime (DTR) effects based on change in clinical attachment level (CAL) outcomes from a non-surgical chronic periodontitis treatments study. The experiment is performed under a Sequential Multiple Assignment Randomized Trial (SMART) design. The clustered tooth (sub-unit) level CAL outcomes are skewed, spatially-referenced, and non-randomly missing. The implemented algorithm is available in Xu et al. (2019+) <arXiv:1902.09386>.

This package provides a simple approach for constructing dynamic materials modeling suggested by Prasad and Gegel (1984) <doi:10.1007/BF02664902>. It can easily generate various processing-maps based on this model as well. The calculation result in this package contains full materials constants, information about power dissipation efficiency factor, and rheological properties, can be exported completely also, through which further analysis and customized plots will be applicable as well.

Computes a point pattern in R^2 or on a graph that is representative of a collection of many data patterns. The result is an approximate barycenter (also known as Fréchet mean or prototype) based on a transport-transform metric. Possible choices include Optimal SubPattern Assignment (OSPA) and Spike Time metrics. Details can be found in Müller, Schuhmacher and Mateu (2020) <doi:10.1007/s11222-020-09932-y>.

Biological studies often consist of multiple conditions which are examined with different laboratory set ups like RNA-sequencing or ChIP-sequencing. To get an overview about the whole resulting data set, Cogito provides an automated, complete, reproducible and clear report about all samples and basic comparisons between all different samples. This report can be used as documentation about the data set or as starting point for further custom analysis.

This package integrates colocalization probabilities from colocalization analysis with transcriptome-wide association study (TWAS) scan summary statistics to implicate genes that may be biologically relevant to a complex trait. The probabilistic framework implemented in this package constrains the TWAS scan z-score-based likelihood using a gene-level colocalization probability. Given gene set annotations, this package can estimate gene set enrichment using posterior probabilities from the TWAS-colocalization integration step.

This package contains the Summix2 method for estimating and adjusting for substructure in genetic summary allele frequency data. The function summix() estimates reference group proportions using a mixture model. The adjAF() function produces adjusted allele frequencies for an observed group with reference group proportions matching a target individual or sample. The summix_local() function estimates local ancestry mixture proportions and performs selection scans in genetic summary data.

Uniparental disomy (UPD) is a genetic condition where an individual inherits both copies of a chromosome or part of it from one parent, rather than one copy from each parent. This package contains a HMM for detecting UPDs through HTS (High Throughput Sequencing) data from trio assays. By analyzing the genotypes in the trio, the model infers a hidden state (normal, father isodisomy, mother isodisomy, father heterodisomy and mother heterodisomy).

This package creates square pie charts also known as waffle charts. These can be used to communicate parts of a whole for categorical quantities. To emulate the percentage view of a pie chart, a 10x10 grid should be used. In this way each square is representing 1% of the total. Waffle provides tools to create charts as well as stitch them together. Isotype pictograms can be made by using glyphs.

Self-organizing maps (also known as SOM, see Kohonen (2001) <doi:10.1007/978-3-642-56927-2>) are a method for dimensionality reduction and clustering of continuous data. This package introduces interactive (html) graphics for easier analysis of SOM results. It also features an interactive interface, for push-button training and visualization of SOM on numeric, categorical or mixed data, as well as tools to evaluate the quality of SOM.

This R package offers block Gibbs samplers for the Bayesian (adaptive) graphical lasso, ridge, and naive elastic net priors. These samplers facilitate the simulation of the posterior distribution of precision matrices for Gaussian distributed data and were originally proposed by: Wang (2012) <doi:10.1214/12-BA729>; Smith et al. (2022) <doi:10.48550/arXiv.2210.16290> and Smith et al. (2023) <doi:10.48550/arXiv.2306.14199>, respectively.

This package performs Correspondence Analysis on the given dataframe and plots the results in a scatterplot that emphasizes the geometric interpretation aspect of the analysis, following Borg-Groenen (2005) and Yelland (2010). It is particularly useful for highlighting the relationships between a selected row (or column) category and the column (or row) categories. See Borg-Groenen (2005, ISBN:978-0-387-28981-6); Yelland (2010) <doi:10.3888/tmj.12-4>.

Statistical tests for the comparison between two or more alpha coefficients based on either dependent or independent groups of individuals. A web interface is available at http://comparingcronbachalphas.org. A plugin for the R GUI and IDE RKWard is included. Please install RKWard from https:// rkward.kde.org to use this feature. The respective R package rkward cannot be installed directly from a repository, as it is a part of RKWard.

Programmatic interface to the European Centre for Medium-Range Weather Forecasts dataset web services (ECMWF; <https://www.ecmwf.int/>) and Copernicus's Data Stores. Allows for easy downloads of weather forecasts and climate reanalysis data in R. Data stores covered include the Climate Data Store (CDS; <https://cds.climate.copernicus.eu>), Atmosphere Data Store (ADS; <https://ads.atmosphere.copernicus.eu>) and Early Warning Data Store (CEMS; <https://ewds.climate.copernicus.eu>).

Find the smallest circle that contains all longitude and latitude input points. From the generated center and radius, variable side polygons can be created, navigation based on bearing and distance can be applied, and more. Based on a modified version of Welzl's algorithm for smallest circle. Distance calculations are based on the haversine formula. Calculations for distance, midpoint, bearing and more are derived from <https://www.movable-type.co.uk>.

This package provides methods for closed testing using Simes local tests. In particular, calculates adjusted p-values for Hommel's multiple testing method, and provides lower confidence bounds for true discovery proportions. A robust but more conservative variant of the closed testing procedure that does not require the assumption of Simes inequality is also implemented. The methods have been described in detail in Goeman et al (Biometrika 106, 841-856, 2019).

The goal of Momocs is to provide a complete, convenient, reproducible and open-source toolkit for 2D morphometrics. It includes most common 2D morphometrics approaches on outlines, open outlines, configurations of landmarks, traditional morphometrics, and facilities for data preparation, manipulation and visualization with a consistent grammar throughout. It allows reproducible, complex morphometrics analyses and other morphometrics approaches should be easy to plug in, or develop from, on top of this canvas.

Straightforward and detailed evaluation of machine learning models. MLeval can produce receiver operating characteristic (ROC) curves, precision-recall (PR) curves, calibration curves, and PR gain curves. MLeval accepts a data frame of class probabilities and ground truth labels, or, it can automatically interpret the Caret train function results from repeated cross validation, then select the best model and analyse the results. MLeval produces a range of evaluation metrics with confidence intervals.

Developed for the following tasks. 1- simulating realizations from the canonical, restricted, and unrestricted finite mixture models. 2- Monte Carlo approximation for density function of the finite mixture models. 3- Monte Carlo approximation for the observed Fisher information matrix, asymptotic standard error, and the corresponding confidence intervals for parameters of the mixture models sing the method proposed by Basford et al. (1997) <https://espace.library.uq.edu.au/view/UQ:57525>.

Inspired by pattern matching and enum types in Rust and many functional programming languages, this package offers an updated version of the switch function called Match that accepts atomic values, functions, expressions, and enum variants. Conditions and return expressions are separated by -> and multiple conditions can be associated with the same return expression using |'. Match also includes support for fallthrough'. The package also replicates the Result and Option enums from Rust.

Maps of Australian coastline and administrative regions. Data can be drawn or accessed directly as simple features objects. Includes simple functions for country or state maps of Australia and in-built data sets of administrative regions from the Australian Bureau of Statistics <https://www.abs.gov.au/>. Layers include electoral divisions and local government areas, simplified from the original sources but with sufficient detail to allow mapping of a local municipality.