_            _    _        _         _
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      \_\ \       /  \ \\ \ \   / / /     / /  \
      /\__ \     / /\ \ \\ \ \_/ / /     / / /\ \__
     / /_ \ \   / / /\ \ \\ \___/ /     / / /\ \___\
    / / /\ \ \ / / /  \ \_\\ \ \_/      \ \ \ \/___/
   / / /  \/_// / /   / / / \ \ \        \ \ \
  / / /      / / /   / / /   \ \ \   _    \ \ \
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/_/ /      / / /____\/ /       \ \_\\ \/___/ /
\_\/       \/_________/         \/_/ \_____\/

Enter the query into the form above. You can look for specific version of a package by using @ symbol like this: gcc@10.

API method:

GET /api/packages?search=hello&page=1&limit=20

where search is your query, page is a page number and limit is a number of items on a single page. Pagination information (such as a number of pages and etc) is returned in response headers.

If you'd like to join our channel webring send a patch to ~whereiseveryone/toys@lists.sr.ht adding your channel as an entry in channels.scm.


r-chem-databases 1.0.0
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://gitlab.com/iembry/chem.databases
Licenses: CC0
Build system: r
Synopsis: Collection of 3 Chemical Databases from Public Sources
Description:

This package contains the Multi-Species Acute Toxicity Database (CAS & SMILES columns only) [United States (US) Department of Health and Human Services (DHHS) National Institutes of Health (NIH) National Cancer Institute (NCI), "Multi-Species Acute Toxicity Database", <https://cactus.nci.nih.gov/download/acute-toxicity-db/>] combined with the Toxic Substances Control Act (TSCA) Inventory [United States Environmental Protection Agency (US EPA), "Toxic Substances Control Act (TSCA) Chemical Substance Inventory", <https://www.epa.gov/tsca-inventory/how-access-tsca-inventory

r-cleanr 1.4.0
Propagated dependencies: r-rprojroot@2.1.1 r-pkgload@1.4.1 r-fritools@4.5.0 r-checkmate@2.3.3
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://gitlab.com/fvafrcu/cleanr
Licenses: FreeBSD
Build system: r
Synopsis: Helps You to Code Cleaner
Description:

Check your R code for some of the most common layout flaws. Many tried to teach us how to write code less dreadful, be it implicitly as B. W. Kernighan and D. M. Ritchie (1988) <ISBN:0-13-110362-8> in The C Programming Language did, be it explicitly as R.C. Martin (2008) <ISBN:0-13-235088-2> in Clean Code: A Handbook of Agile Software Craftsmanship did. So we should check our code for files too long or wide, functions with too many lines, too wide lines, too many arguments or too many levels of nesting. Note: This is not a static code analyzer like pylint or the like. Checkout <https://cran.r-project.org/package=lintr> instead.

r-certara-modelresults 3.0.1
Propagated dependencies: r-xpose@0.4.22 r-tidyr@1.3.1 r-sortable@0.6.0 r-shinywidgets@0.9.0 r-shinytree@0.3.1 r-shinymeta@0.2.1 r-shinyjs@2.1.0 r-shinyjqui@0.4.1 r-shinyace@0.4.4 r-shiny@1.11.1 r-scales@1.4.0 r-rlang@1.1.6 r-plotly@4.11.0 r-magrittr@2.0.4 r-ggplot2@4.0.1 r-flextable@0.9.10 r-dplyr@1.1.4 r-colourpicker@1.3.0 r-certara-xpose-nlme@2.0.2 r-bslib@0.9.0
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://certara.github.io/R-model-results/
Licenses: LGPL 3
Build system: r
Synopsis: Generate Diagnostics for Pharmacometric Models Using 'shiny'
Description:

Utilize the shiny interface to generate Goodness of Fit (GOF) plots and tables for Non-Linear Mixed Effects (NLME / NONMEM) pharmacometric models. From the interface, users can customize model diagnostics and generate the underlying R code to reproduce the diagnostic plots and tables outside of the shiny session. Model diagnostics can be included in a rmarkdown document and rendered to desired output format.

r-cloneseeker 1.0.16
Propagated dependencies: r-quantmod@0.4.28 r-mc2d@0.2.1 r-combinat@0.0-8
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: http://oompa.r-forge.r-project.org/
Licenses: ASL 2.0
Build system: r
Synopsis: Seeking and Finding Clones in Copy Number and Sequencing Data
Description:

Defines the classes and functions used to simulate and to analyze data sets describing copy number variants and, optionally, sequencing mutations in order to detect clonal subsets. See Zucker et al. (2019) <doi:10.1093/bioinformatics/btz057>.

r-cpmcglm 1.2
Propagated dependencies: r-plyr@1.8.9 r-mvtnorm@1.3-3 r-abind@1.4-8
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/
Licenses: GPL 3+
Build system: r
Synopsis: Correction of the P-Value after Multiple Coding in Generalized Linear Models
Description:

We propose to determine the correction of the significance level after multiple coding of an explanatory variable in Generalized Linear Model. The different methods of correction of the p-value are the Single step Bonferroni procedure, and resampling based methods developed by P.H.Westfall in 1993. Resampling methods are based on the permutation and the parametric bootstrap procedure. If some continuous, and dichotomous transformations are performed this package offers an exact correction of the p-value developed by B.Liquet & D.Commenges in 2005. The naive method with no correction is also available.

r-colombiapi 0.3.1
Propagated dependencies: r-tibble@3.3.0 r-scales@1.4.0 r-jsonlite@2.0.0 r-httr@1.4.7 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/lightbluetitan/colombiapi
Licenses: GPL 3
Build system: r
Synopsis: Access Colombian Data via APIs and Curated Datasets
Description:

This package provides a comprehensive interface to access diverse public data about Colombia through multiple APIs and curated datasets. The package integrates four different APIs: API-Colombia for Colombian-specific data including geography, culture, tourism, and government information; World Bank API for economic and demographic indicators; Nager.Date for public holidays; and REST Countries API for general country information. The package enables users to explore various aspects of Colombia such as geographic locations, cultural attractions, economic indicators, demographic data, and public holidays. Additionally, ColombiAPI includes curated datasets covering Bogota air stations, business and holiday dates, public schools, Colombian coffee exports, cannabis licenses, Medellin rainfall, malls in Bogota, as well as datasets on indigenous languages, student admissions and school statistics, forest liana mortality, municipal and regional data, connectivity and digital infrastructure, program graduates, vehicle counts, international visitors, and GDP projections. These datasets provide users with a rich and multifaceted view of Colombian social, economic, environmental, and technological information, making ColombiAPI a comprehensive tool for exploring Colombia's diverse data landscape. For more information on the APIs, see: API-Colombia <https://api-colombia.com/>, Nager.Date <https://date.nager.at/Api>, World Bank API <https://datahelpdesk.worldbank.org/knowledgebase/articles/889392>, and REST Countries API <https://restcountries.com/>.

r-covkcd 0.1
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=covKCD
Licenses: GPL 3
Build system: r
Synopsis: Covariance Estimation for Matrix Data with the Kronecker-Core Decomposition
Description:

Matrix-variate covariance estimation via the Kronecker-core decomposition. Computes the Kronecker and core covariance matrices corresponding to an arbitrary covariance matrix, and provides an empirical Bayes covariance estimator that adaptively shrinks towards the space of separable covariance matrices. For details, see Hoff, McCormack and Zhang (2022) <arXiv:2207.12484> "Core Shrinkage Covariance Estimation for Matrix-variate data".

r-clinicalomicsdbr 1.0.5
Propagated dependencies: r-r6@2.6.1 r-jsonlite@2.0.0 r-httr2@1.2.1 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/bzhanglab/clinicalomicsdbR
Licenses: Expat
Build system: r
Synopsis: Interface with the 'ClinicalOmicsDB' API, Allowing for Easy Data Downloading and Importing
Description:

This package provides an interface to the ClinicalOmicsDB API, allowing for easy data downloading and importing. ClinicalOmicsDB is a database of clinical and omics data from cancer patients. The database is accessible at <http://trials.linkedomics.org>.

r-cohortsurvival 1.1.0
Propagated dependencies: r-tidyr@1.3.1 r-tibble@3.3.0 r-survival@3.8-3 r-stringr@1.6.0 r-rlang@1.1.6 r-purrr@1.2.0 r-patientprofiles@1.4.5 r-omopgenerics@1.3.6 r-glue@1.8.0 r-dplyr@1.1.4 r-dbi@1.2.3 r-clock@0.7.3 r-cli@3.6.5 r-cdmconnector@2.3.0 r-broom@1.0.10
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://darwin-eu-dev.github.io/CohortSurvival/
Licenses: FSDG-compatible
Build system: r
Synopsis: Estimate Survival from Common Data Model Cohorts
Description:

Estimate survival using data mapped to the Observational Medical Outcomes Partnership common data model. Survival can be estimated based on user-defined study cohorts.

r-contsurvplot 0.2.3
Propagated dependencies: r-rlang@1.1.6 r-riskregression@2025.09.17 r-ggplot2@4.0.1 r-foreach@1.5.2 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/RobinDenz1/contsurvplot
Licenses: GPL 3+
Build system: r
Synopsis: Visualize the Effect of a Continuous Variable on a Time-to-Event Outcome
Description:

Graphically display the (causal) effect of a continuous variable on a time-to-event outcome using multiple different types of plots based on g-computation. Those functions include, among others, survival area plots, survival contour plots, survival quantile plots and 3D surface plots. Due to the use of g-computation, all plot allow confounder-adjustment naturally. For details, see Robin Denz, Nina Timmesfeld (2023) <doi:10.1097/EDE.0000000000001630>.

r-cfr 0.2.0
Propagated dependencies: r-checkmate@2.3.3
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/epiverse-trace/cfr
Licenses: Expat
Build system: r
Synopsis: Estimate Disease Severity and Case Ascertainment
Description:

Estimate the severity of a disease and ascertainment of cases, as discussed in Nishiura et al. (2009) <doi:10.1371/journal.pone.0006852>.

r-cdrcr 0.1.1
Propagated dependencies: r-tidyselect@1.2.1 r-tidyr@1.3.1 r-sf@1.0-23 r-rlist@0.4.6.2 r-rlang@1.1.6 r-rjson@0.2.23 r-purrr@1.2.0 r-magrittr@2.0.4 r-jsonlite@2.0.0 r-httr@1.4.7 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=cdrcR
Licenses: GPL 3
Build system: r
Synopsis: Load 'CDRC' Data
Description:

This package provides a wrapper for the CDRC API that returns data frames or sf of CDRC data. The API web reference is:<https://api.cdrc.ac.uk/swagger/index.html>.

r-connected 1.1
Propagated dependencies: r-reshape2@1.4.5 r-lfe@3.1.1 r-lattice@0.22-7
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://kwstat.github.io/connected/
Licenses: GPL 2+
Build system: r
Synopsis: Visualize and Improve Connectedness of Factors in Tables
Description:

Visualize the connectedness of factors in two-way tables. Perform two-way filtering to improve the degree of connectedness. See Weeks & Williams (1964) <doi:10.1080/00401706.1964.10490188>.

r-clustassess 1.1.0
Propagated dependencies: r-vioplot@0.5.1 r-uwot@0.2.4 r-stringr@1.6.0 r-shinywidgets@0.9.0 r-shinylp@1.1.3 r-shinyjs@2.1.0 r-shiny@1.11.1 r-seurat@5.3.1 r-rlang@1.1.6 r-reshape2@1.4.5 r-rcppeigen@0.3.4.0.2 r-rcpp@1.1.0 r-rann@2.6.2 r-qualpalr@2.0.0 r-progress@1.2.3 r-plotly@4.11.0 r-paletteer@1.6.0 r-matrixstats@1.5.0 r-matrix@1.7-4 r-leiden@0.4.3.1 r-jsonlite@2.0.0 r-igraph@2.2.1 r-gprofiler2@0.2.4 r-gmedian@1.2.7 r-glue@1.8.0 r-ggtext@0.1.2 r-ggrepel@0.9.6 r-ggrastr@1.0.2 r-ggplot2@4.0.1 r-ggnewscale@0.5.2 r-foreach@1.5.2 r-fastcluster@1.3.0 r-dt@0.34.0 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/Core-Bioinformatics/ClustAssess
Licenses: Expat
Build system: r
Synopsis: Tools for Assessing Clustering
Description:

This package provides a set of tools for evaluating clustering robustness using proportion of ambiguously clustered pairs (Senbabaoglu et al. (2014) <doi:10.1038/srep06207>), as well as similarity across methods and method stability using element-centric clustering comparison (Gates et al. (2019) <doi:10.1038/s41598-019-44892-y>). Additionally, this package enables stability-based parameter assessment for graph-based clustering pipelines typical in single-cell data analysis.

r-comclim 0.9.6
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=comclim
Licenses: GPL 3
Build system: r
Synopsis: Community Climate Statistics
Description:

Computes community climate statistics for volume and mismatch using species climate niches either unscaled or scaled relative to a regional species pool. These statistics can be used to describe biogeographic patterns and infer community assembly processes. Includes a vignette outlining usage.

r-crt2power 1.2.2
Propagated dependencies: r-tidyverse@2.0.0 r-tidyr@1.3.1 r-tibble@3.3.0 r-tableone@0.13.2 r-rootsolve@1.8.2.4 r-mvtnorm@1.3-3 r-knitr@1.50 r-foreach@1.5.2 r-dplyr@1.1.4 r-devtools@2.4.6
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/melodyaowen/crt2power
Licenses: GPL 3
Build system: r
Synopsis: Designing Cluster-Randomized Trials with Two Continuous Co-Primary Outcomes
Description:

This package provides methods for powering cluster-randomized trials with two continuous co-primary outcomes using five key design techniques. Includes functions for calculating required sample size and statistical power. For more details on methodology, see Owen et al. (2025) <doi:10.1002/sim.70015>, Yang et al. (2022) <doi:10.1111/biom.13692>, Pocock et al. (1987) <doi:10.2307/2531989>, Vickerstaff et al. (2019) <doi:10.1186/s12874-019-0754-4>, and Li et al. (2020) <doi:10.1111/biom.13212>.

r-conjurer 1.7.1
Propagated dependencies: r-jsonlite@2.0.0 r-httr@1.4.7
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://www.foyi.co.nz/posts/documentation/documentationconjurer/
Licenses: Expat
Build system: r
Synopsis: Parametric Method for Generating Synthetic Data
Description:

Generates synthetic data distributions to enable testing various modelling techniques in ways that real data does not allow. Noise can be added in a controlled manner such that the data seems real. This methodology is generic and therefore benefits both the academic and industrial research.

r-covid19tunisia 0.1.0
Propagated dependencies: r-tidyr@1.3.1 r-stringr@1.6.0 r-readr@2.1.6 r-magrittr@2.0.4 r-lubridate@1.9.4 r-knitr@1.50 r-glue@1.8.0 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/MounaBelaid/covid19tunisia
Licenses: Expat
Build system: r
Synopsis: Cases of COVID-19 in Tunisia
Description:

Data personally collected about the spread of COVID-19 (SARS-COV-2) in Tunisia <https://github.com/MounaBelaid/covid19datatunisia>.

r-c2c 0.1.0
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/mitchest/c2c/
Licenses: GPL 3
Build system: r
Synopsis: Compare Two Classifications or Clustering Solutions of Varying Structure
Description:

Compare two classifications or clustering solutions that may or may not have the same number of classes, and that might have hard or soft (fuzzy, probabilistic) membership. Calculate various metrics to assess how the clusters compare to each other. The calculations are simple, but provide a handy tool for users unfamiliar with matrix multiplication. This package is not geared towards traditional accuracy assessment for classification/ mapping applications - the motivating use case is for comparing a probabilistic clustering solution to a set of reference or existing class labels that could have any number of classes (that is, without having to degrade the probabilistic clustering to hard classes).

r-ctshiny2 0.1.0
Propagated dependencies: r-shiny@1.11.1 r-rpart-plot@3.1.4 r-rpart@4.1.24 r-rmarkdown@2.30 r-rhandsontable@0.3.8 r-party@1.3-18 r-e1071@1.7-16 r-dplyr@1.1.4 r-caret@7.0-1
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=CTShiny2
Licenses: GPL 2
Build system: r
Synopsis: Interactive Document for Working with Classification Tree Analysis
Description:

An interactive document on the topic of classification tree analysis using rmarkdown and shiny packages. Runtime examples are provided in the package function as well as at <https://kartikeyab.shinyapps.io/CTShiny/>.

r-correctr 0.3.1
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://hendersontrent.github.io/correctR/
Licenses: Expat
Build system: r
Synopsis: Corrected Test Statistics for Comparing Machine Learning Models on Correlated Samples
Description:

Calculate a set of corrected test statistics for cases when samples are not independent, such as when classification accuracy values are obtained over resamples or through k-fold cross-validation, as proposed by Nadeau and Bengio (2003) <doi:10.1023/A:1024068626366> and presented in Bouckaert and Frank (2004) <doi:10.1007/978-3-540-24775-3_3>.

r-ctablerseh 1.1.2
Propagated dependencies: r-survey@4.4-8
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=ctablerseh
Licenses: GPL 3+
Build system: r
Synopsis: Processing Survey Data with Confidence Intervals Like 'SPSS' Software
Description:

Processes survey data and displays estimation results along with the relative standard error in a table, including the number of samples and also uses a t-distribution approach to compute confidence intervals, similar to SPSS (Statistical Package for the Social Sciences) software.

r-cglasso 2.0.7
Propagated dependencies: r-mass@7.3-65 r-igraph@2.2.1
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=cglasso
Licenses: GPL 2+
Build system: r
Synopsis: Conditional Graphical LASSO for Gaussian Graphical Models with Censored and Missing Values
Description:

Conditional graphical lasso estimator is an extension of the graphical lasso proposed to estimate the conditional dependence structure of a set of p response variables given q predictors. This package provides suitable extensions developed to study datasets with censored and/or missing values. Standard conditional graphical lasso is available as a special case. Furthermore, the package provides an integrated set of core routines for visualization, analysis, and simulation of datasets with censored and/or missing values drawn from a Gaussian graphical model. Details about the implemented models can be found in Augugliaro et al. (2023) <doi: 10.18637/jss.v105.i01>, Augugliaro et al. (2020b) <doi: 10.1007/s11222-020-09945-7>, Augugliaro et al. (2020a) <doi: 10.1093/biostatistics/kxy043>, Yin et al. (2001) <doi: 10.1214/11-AOAS494> and Stadler et al. (2012) <doi: 10.1007/s11222-010-9219-7>.

r-crmpack 2.1.0
Propagated dependencies: r-tidyselect@1.2.1 r-tibble@3.3.0 r-survival@3.8-3 r-rlang@1.1.6 r-rjags@4-17 r-rdpack@2.6.4 r-parallelly@1.45.1 r-mvtnorm@1.3-3 r-magrittr@2.0.4 r-lifecycle@1.0.4 r-knitr@1.50 r-kableextra@1.4.0 r-gridextra@2.3 r-ggplot2@4.0.1 r-gensa@1.1.15 r-futile-logger@1.4.3 r-dplyr@1.1.4 r-checkmate@2.3.3
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/openpharma/crmPack
Licenses: GPL 2+
Build system: r
Synopsis: Object-Oriented Implementation of Dose Escalation Designs
Description:

This package implements a wide range of dose escalation designs. The focus is on model-based designs, ranging from classical and modern continual reassessment methods (CRMs) based on dose-limiting toxicity endpoints to dual-endpoint designs taking into account a biomarker/efficacy outcome. Bayesian inference is performed via MCMC sampling in JAGS, and it is easy to setup a new design with custom JAGS code. However, it is also possible to implement 3+3 designs for comparison or models with non-Bayesian estimation. The whole package is written in a modular form in the S4 class system, making it very flexible for adaptation to new models, escalation or stopping rules. Further details are presented in Sabanés Bové et al. (2019) <doi:10.18637/jss.v089.i10>.

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