The openMSE package is designed for building operating models, doing simulation modelling and management strategy evaluation for fisheries. openMSE is an umbrella package for the MSEtool (Management Strategy Evaluation toolkit), DLMtool (Data-Limited Methods toolkit), and SAMtool (Stock Assessment Methods toolkit) packages. By loading and installing openMSE', users have access to the full functionality contained within these packages. Learn more about openMSE at <https://openmse.com/>.

This package implements a range of facilities for post-hoc analysis and summarizing linear models, generalized linear models and generalized linear mixed models, including grouping and clustering via pairwise comparisons using graph representations and efficient algorithms for finding maximal cliques of a graph. Includes also non-parametric toos for post-hoc analysis. It has S3 methods for printing summarizing, and producing plots, line and barplots suitable for post-hoc analyses.

An R implementation of quality controlâ based robust LOESS(local polynomial regression fitting) signal correction for metabolomics data analysis, described in Dunn, W., Broadhurst, D., Begley, P. et al. (2011) <doi:10.1038/nprot.2011.335>. The optimisation of LOESS's span parameter using generalized cross-validation (GCV) is provided as an option. In addition to signal correction, qcrlscR includes some utility functions like batch shifting and data filtering.

Presents an explanatory animation of normal quantile-quantile plots based on a water-filling analogy. The animation presents a normal QQ plot as the parametric plot of the water levels in vases defined by two distributions. The distributions decorate the axes in the normal QQ plot and are optionally shown as vases adjacent to the plot. The package draws QQ plots for several distributions, either as samples or continuous functions.

This data-driven phylogenetic comparative method fits stabilizing selection models to continuous trait data, building on the ouch methodology of Butler and King (2004) <doi:10.1086/426002>. The main functions fit a series of Hansen models using stepwise AIC, then identify cases of convergent evolution where multiple lineages have shifted to the same adaptive peak. For more information see Ingram and Mahler (2013) <doi:10.1111/2041-210X.12034>.

This tiny package contains one function smirnov() which calculates two scaled taxonomic coefficients, Txy (coefficient of similarity) and Txx (coefficient of originality). These two characteristics may be used for the analysis of similarities between any number of taxonomic groups, and also for assessing uniqueness of giving taxon. It is possible to use smirnov() output as a distance measure: convert it to distance by "as.dist(1 - smirnov(x))".

Data wrangling, pre-processing, and generating automated reports from Colombia's epidemiological surveillance system, SIVIGILA <https://portalsivigila.ins.gov.co/>. It provides a customizable R Markdown template for analysis and automatic generation of epidemiological reports that can be adapted to local, regional, and national contexts. This tool offers a standardized and reproducible workflow that helps to reduce manual labor and potential errors in report generation, improving their efficiency and consistency.

This package provides a collection of commonly used tools for animal movement and other tracking data. Variously distance, angle, bearing, distance-to, bearing-to and speed are provided for geographic data that can be used directly or within tidyverse syntax. Distances and bearings are calculated using modern geodesic methods as provided by Charles F. F. Karney (2013) <doi:10.1007/s00190-012-0578-z> via the geodist and geosphere packages.

This package implements marginal structural models combined with a latent class growth analysis framework for assessing the causal effect of treatment trajectories. Based on the approach described in "Marginal Structural Models with Latent Class Growth Analysis of Treatment Trajectories" Diop, A., Sirois, C., Guertin, J.R., Schnitzer, M.E., Candas, B., Cossette, B., Poirier, P., Brophy, J., Mésidor, M., Blais, C. and Hamel, D., (2023) <doi:10.1177/09622802231202384>.

Estimates heterogeneous treatment effects using tidy semantics on experimental or observational data. Methods are based on the doubly-robust learner of Kennedy (n.d.) <arXiv:2004.14497>. You provide a simple recipe for what machine learning algorithms to use in estimating the nuisance functions and tidyhte will take care of cross-validation, estimation, model selection, diagnostics and construction of relevant quantities of interest about the variability of treatment effects.

There are two new network metrics, RWC (random walk centrality) and CBET (counting betweenness). Also available are the normalized versions of those metrics. These measures of centrality and betweenness are particularly useful for the analysis of very dense weighted networks which include loops. Traditional measures do not work as well for those network characteristics. The main reference is DePaolis at al (2022) <doi:10.1007/s41109-022-00519-2>.

This package provides a model designed for dimensionality reduction and batch effect removal for scRNA-seq data. It is designed to be massively parallelizable using shared objects that prevent memory duplication, and it can be used with different mini-batch approaches in order to reduce time consumption. It assumes a negative binomial distribution for the data with a dispersion parameter that can be both commonwise across gene both genewise.

This package provides functions for identification and visualization of potential intramolecular triplex patterns in DNA sequence. The main functionality is to detect the positions of subsequences capable of folding into an intramolecular triplex (H-DNA) in a much larger sequence. The potential H-DNA (triplexes) should be made of as many cannonical nucleotide triplets as possible. The package includes visualization showing the exact base-pairing in 1D, 2D or 3D.

This package provides tools to visualize simple graphs (networks) based on a transition matrix, utilities to plot flow diagrams, visualizing webs, electrical networks, etc. It also includes supporting material for the book "A practical guide to ecological modelling - using R as a simulation platform" by Karline Soetaert and Peter M.J. Herman (2009) and the book "Solving Differential Equations in R" by Karline Soetaert, Jeff Cash and Francesca Mazzia (2012).

This package provides a fast implementation of a key-value store. Environments are commonly used as key-value stores, but every time a new key is used, it is added to R's global symbol table, causing a small amount of memory leakage. This can be problematic in cases where many different keys are used. Fastmap avoids this memory leak issue by implementing the map using data structures in C++.

This package provides HTTP error helpers. Methods are included for general purpose HTTP error handling, as well as individual methods for every HTTP status code, both via status code numbers as well as their descriptive names. It supports the ability to adjust behavior to stop, message or warning. It includes the ability to use a custom whisker template to have any configuration of status code, short description, and verbose message.

This package can be used to predict the r-species accumulation curve (r-SAC), which is the number of species represented at least r times as a function of the sampling effort. When r = 1, the curve is known as the species accumulation curve, or the library complexity curve in high-throughput genomic sequencing. The package includes both parametric and nonparametric methods, as described by Deng C, et al. (2018).

Alga aims to provide solid mathematical abstractions to algebra-focused applications. It defines and organizes through trait inheritance the basic building blocks of general algebraic structures. Specific implementations of algebraic structure traits are left to other crates. Higher-level traits for specialized domains of algebra (like linear algebra) are also provided and will prove useful for applications that include code that is generic with regard to the algebraic entity types.

Rofi-pass provides a way to manipulate information stored using password-store through rofi interface:

1. open URLs of entries with hotkey;

2. type any field from entry;

3. auto-typing of user and/or password fields;

4. auto-typing username based on path;

5. auto-typing of more than one field, using the autotype entry;

6. bookmarks mode (open stored URLs in browser, default: Alt+x).

This package provides functions to identify Homozygous-by-Descent (HBD) segments associated with runs of homozygosity (ROH) and to estimate individual autozygosity (or inbreeding coefficient). HBD segments and autozygosity are assigned to multiple HBD classes with a model-based approach relying on a mixture of exponential distributions. The rate of the exponential distribution is distinct for each HBD class and defines the expected length of the HBD segments. These HBD classes are therefore related to the age of the segments (longer segments and smaller rates for recent autozygosity / recent common ancestor). The functions allow to estimate the parameters of the model (rates of the exponential distributions, mixing proportions), to estimate global and local autozygosity probabilities and to identify HBD segments with the Viterbi decoding. The method is fully described in Druet and Gautier (2017) <doi:10.1111/mec.14324> and Druet and Gautier (2022) <doi:10.1016/j.tpb.2022.03.001>.

Download data from the Access to Opportunities Project (AOP)'. The aopdata package brings annual estimates of access to employment, health, education and social assistance services by transport mode, as well as data on the spatial distribution of population, jobs, health care, schools and social assistance facilities at a fine spatial resolution for all cities included in the project. More info on the AOP website <https://www.ipea.gov.br/acessooportunidades/en/>.

This package provides a ggplot2 centric approach to bivariate mapping. This is a technique that maps two quantities simultaneously rather than the single value that most thematic maps display. The package provides a suite of tools for calculating breaks using multiple different approaches, a selection of palettes appropriate for bivariate mapping and scale functions for ggplot2 calls that adds those palettes to maps. Tools for creating bivariate legends are also included.

This package implements the Bayesian FDR control described by Newton et al. (2004), <doi:10.1093/biostatistics/5.2.155>. Allows optimisation and visualisation of expected error rates based on tail posterior probability tests. Based on code written by Catalina Vallejos for BASiCS, see Beyond comparisons of means: understanding changes in gene expression at the single-cell level Vallejos et al. (2016) <doi:10.1186/s13059-016-0930-3>.

This package implements non-parametric analyses for clustered binary and multinomial data. The elements of the cluster are assumed exchangeable, and identical joint distribution (also known as marginal compatibility, or reproducibility) is assumed for clusters of different sizes. A trend test based on stochastic ordering is implemented. Szabo A, George EO. (2010) <doi:10.1093/biomet/asp077>; George EO, Cheon K, Yuan Y, Szabo A (2016) <doi:10.1093/biomet/asw009>.