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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-gnorm 1.0.0
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: http://github.com/maryclare/gnorm
Licenses: GPL 2+
Build system: r
Synopsis: Generalized Normal/Exponential Power Distribution
Description:

This package provides functions for obtaining generalized normal/exponential power distribution probabilities, quantiles, densities and random deviates. The generalized normal/exponential power distribution was introduced by Subbotin (1923) and rediscovered by Nadarajah (2005). The parametrization given by Nadarajah (2005) <doi:10.1080/02664760500079464> is used.

r-ggvolcano 0.1.4
Propagated dependencies: r-shiny@1.11.1 r-golem@0.5.1 r-ggrepel@0.9.6 r-ggplot2@4.0.1 r-config@0.3.2
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=ggvolcano
Licenses: Expat
Build system: r
Synopsis: Publication-Ready Volcano Plots
Description:

This package provides publication-ready volcano plots for visualizing differential expression results, commonly used in RNA-seq and similar analyses. This tool helps create high-quality visual representations of data using the ggplot2 framework Wickham (2016) <doi:10.1007/978-3-319-24277-4>.

r-ggmrscu 0.1.0
Propagated dependencies: r-tidyr@1.3.1 r-rlang@1.1.6 r-purrr@1.2.0 r-patchwork@1.3.2 r-ggplot2@4.0.1 r-dplyr@1.1.4 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=ggmRSCU
Licenses: GPL 3+
Build system: r
Synopsis: Visualizing Multi-Species Relative Synonymous Codon Usage and Extensible Data Exploration
Description:

Facilitates efficient visualization of Relative Synonymous Codon Usage patterns across species. Based on analytical outputs from codonW', MEGA', and Phylosuite', it supports multi-species RSCU comparisons and allows users to explore visual analysis of structurally similar datasets.

r-getquandldata 1.0.0
Propagated dependencies: r-readr@2.1.6 r-purrr@1.2.0 r-memoise@2.0.1 r-jsonlite@2.0.0 r-fs@1.6.6 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/msperlin/GetQuandlData/
Licenses: GPL 2
Build system: r
Synopsis: Fast and Cached Import of Data from 'Quandl' Using the 'json API'
Description:

Imports time series data from the Quandl database <https://data.nasdaq.com/>. The package uses the json api at <https://data.nasdaq.com/search>, local caching ('memoise package) and the tidy format by default. Also allows queries of databases, allowing the user to see which time series are available for each database id. In short, it is an alternative to package Quandl', with faster data importation in the tidy/long format.

r-glmulti 1.0.8
Dependencies: openjdk@25
Propagated dependencies: r-rjava@1.0-11 r-leaps@3.2
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=glmulti
Licenses: GPL 2+
Build system: r
Synopsis: Model Selection and Multimodel Inference Made Easy
Description:

Automated model selection and model-averaging. Provides a wrapper for glm and other functions, automatically generating all possible models (under constraints set by the user) with the specified response and explanatory variables, and finding the best models in terms of some Information Criterion (AIC, AICc or BIC). Can handle very large numbers of candidate models. Features a Genetic Algorithm to find the best models when an exhaustive screening of the candidates is not feasible.

r-generaloaxaca 1.0
Propagated dependencies: r-boot@1.3-32
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=GeneralOaxaca
Licenses: GPL 2+
Build system: r
Synopsis: Blinder-Oaxaca Decomposition for Generalized Linear Model
Description:

Perform the Blinder-Oaxaca decomposition for generalized linear model with bootstrapped standard errors. The twofold and threefold decomposition are given, even the generalized linear model output in each group.

r-ggrounded 0.0.3
Propagated dependencies: r-gridgeometry@0.4-0 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/botan/ggrounded
Licenses: Expat
Build system: r
Synopsis: Rounded Bar Plots
Description:

This package creates bar plots with rounded corners using ggplot2'. The code in this package was adapted from a solution provided by Stack Overflow user sthoch in the following post <https://stackoverflow.com/questions/62176038/r-ggplot2-bar-chart-with-round-corners-on-top-of-bar>.

r-gulfm 0.5.0
Propagated dependencies: r-matrixstats@1.5.0 r-mass@7.3-65
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=GulFM
Licenses: Expat
Build system: r
Synopsis: General Unilateral Load Estimator for Two-Layer Latent Factor Models
Description:

This package implements general unilateral loading estimator for two-layer latent factor models with smooth, element-wise factor transformations. We provide data simulation, loading estimation,finite-sample error bounds, and diagnostic tools for zero-mean and sub-Gaussian assumptions. A unified interface is given for evaluating estimation accuracy and cosine similarity. The philosophy of the package is described in Guo G. (2026) <doi:10.1016/j.apm.2025.116280>.

r-gooser 0.1.2
Propagated dependencies: r-yaml@2.3.10 r-systemfonts@1.3.1 r-shiny@1.11.1 r-rstudioapi@0.17.1 r-rappdirs@0.3.3 r-r6@2.6.1 r-purrr@1.2.0 r-promises@1.5.0 r-processx@3.8.6 r-miniui@0.1.2 r-magrittr@2.0.4 r-later@1.4.4 r-knitr@1.50 r-jsonlite@2.0.0 r-here@1.0.2 r-glue@1.8.0 r-ggplot2@4.0.1 r-future-apply@1.20.0 r-future@1.68.0 r-fs@1.6.6 r-digest@0.6.39 r-dbi@1.2.3 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=gooseR
Licenses: Expat
Build system: r
Synopsis: R Integration for 'Goose' AI
Description:

Seamless integration between R and Goose AI capabilities including memory management, visualization enhancements, and workflow automation. Save R objects to Goose memory, apply Block branding to visualizations, and manage data science project workflows. For more information about Goose AI, see <https://github.com/block/goose>.

r-groundhog 3.4.0
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://groundhogr.com/
Licenses: GPL 3
Build system: r
Synopsis: Version-Control for CRAN, GitHub, and GitLab Packages
Description:

Make R scripts reproducible, by ensuring that every time a given script is run, the same version of the used packages are loaded (instead of whichever version the user running the script happens to have installed). This is achieved by using the command groundhog.library() instead of the base command library(), and including a date in the call. The date is used to call on the same version of the package every time (the most recent version available at that date). Load packages from CRAN, GitHub, or Gitlab.

r-ghs 0.1
Propagated dependencies: r-mass@7.3-65
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=GHS
Licenses: GPL 2
Build system: r
Synopsis: Graphical Horseshoe MCMC Sampler Using Data Augmented Block Gibbs Sampler
Description:

Draw posterior samples to estimate the precision matrix for multivariate Gaussian data. Posterior means of the samples is the graphical horseshoe estimate by Li, Bhadra and Craig(2017) <arXiv:1707.06661>. The function uses matrix decomposition and variable change from the Bayesian graphical lasso by Wang(2012) <doi:10.1214/12-BA729>, and the variable augmentation for sampling under the horseshoe prior by Makalic and Schmidt(2016) <arXiv:1508.03884>. Structure of the graphical horseshoe function was inspired by the Bayesian graphical lasso function using blocked sampling, authored by Wang(2012) <doi:10.1214/12-BA729>.

r-gimap 1.1.2
Propagated dependencies: r-vroom@1.6.6 r-tidyr@1.3.1 r-stringr@1.6.0 r-rmarkdown@2.30 r-readr@2.1.6 r-purrr@1.2.0 r-pheatmap@1.0.13 r-openssl@2.3.4 r-magrittr@2.0.4 r-jsonlite@2.0.0 r-janitor@2.2.1 r-httr@1.4.7 r-ggplot2@4.0.1 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/FredHutch/gimap
Licenses: GPL 3
Build system: r
Synopsis: Calculate Genetic Interactions for Paired CRISPR Targets
Description:

Helps find meaningful patterns in complex genetic experiments. First gimap takes data from paired CRISPR (Clustered regularly interspaced short palindromic repeats) screens that has been pre-processed to counts table of paired gRNA (guide Ribonucleic Acid) reads. The input data will have cell counts for how well cells grow (or don't grow) when different genes or pairs of genes are disabled. The output of the gimap package is genetic interaction scores which are the distance between the observed CRISPR score and the expected CRISPR score. The expected CRISPR scores are what we expect for the CRISPR values to be for two unrelated genes. The further away an observed CRISPR score is from its expected score the more we suspect genetic interaction. The work in this package is based off of original research from the Alice Berger lab at Fred Hutchinson Cancer Center (2021) <doi:10.1016/j.celrep.2021.109597>.

r-ggrain 0.1.2
Propagated dependencies: r-vctrs@0.6.5 r-rlang@1.1.6 r-ggpp@0.5.9 r-ggplot2@4.0.1 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/njudd/ggrain
Licenses: Expat
Build system: r
Synopsis: Rainclouds Geom for 'ggplot2'
Description:

The geom_rain() function adds different geoms together using ggplot2 to create raincloud plots.

r-grcdesigns 1.0.0
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=GRCdesigns
Licenses: GPL 2+
Build system: r
Synopsis: Generalized Row-Column Designs
Description:

When the number of treatments is large with limited experimental resources then Row-Column(RC) designs with multiple units per cell can be used. These designs are called Generalized Row-Column (GRC) designs and are defined as designs with v treatments in p rows and q columns such that the intersection of each row and column (cell) consists of k experimental units. For example (Bailey & Monod (2001)<doi:10.1111/1467-9469.00235>), to conduct an experiment for comparing 4 treatments using 4 plants with leaves at 2 different heights row-column design with two units per cell can be used. A GRC design is said to be structurally complete if corresponding to the intersection of each row and column, there appears at least two treatments. A GRC design is said to be structurally incomplete if corresponding to the intersection of any row and column, there is at least one cell which does not contain any treatment.

r-ggfixest 0.4.0
Propagated dependencies: r-scales@1.4.0 r-marginaleffects@0.31.0 r-legendry@0.2.4 r-ggplot2@4.0.1 r-fixest@0.13.2 r-dreamerr@1.5.0
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://grantmcdermott.com/ggfixest/
Licenses: GPL 3
Build system: r
Synopsis: Dedicated 'ggplot2' Methods for 'fixest' Objects
Description:

This package provides ggplot2 equivalents of fixest::coefplot() and fixest::iplot(), for producing nice coefficient plots and interaction plots. Enables some additional functionality and convenience features, including grouped multi-'fixest object faceting and programmatic updates to existing plots (e.g., themes and aesthetics).

r-geboes-score 1.0.0
Propagated dependencies: r-checkmate@2.3.3
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://billdenney.github.io/geboes.score/
Licenses: GPL 3+
Build system: r
Synopsis: Evaluate the Geboes Score for Histology in Ulcerative Colitis
Description:

Evaluate and validate the Geboes score for histological assessment of inflammation in ulcerative colitis. The original Geboes score from Geboes, et al. (2000) <doi:10.1136/gut.47.3.404>, binary version from Li, et al. (2019) <doi:10.1093/ecco-jcc/jjz022>, and continuous version from Magro, et al. (2020) <doi:10.1093/ecco-jcc/jjz123> are all described and implemented.

r-gadjid 0.1.0
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/CausalDisco/gadjid
Licenses: FSDG-compatible
Build system: r
Synopsis: Graph Adjustment Identification Distances for Causal Graphs
Description:

Make efficient Rust implementations of graph adjustment identification distances available in R. These distances (based on ancestor, optimal, and parent adjustment) count how often the respective adjustment identification strategy leads to causal inferences that are incorrect relative to a ground-truth graph when applied to a candidate graph instead. See also Henckel, Würtzen, Weichwald (2024) <doi:10.48550/arXiv.2402.08616>.

r-gamlssx 1.0.2
Propagated dependencies: r-nieve@0.1.3 r-gamlss-dist@6.1-1 r-gamlss@5.5-0
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://paulnorthrop.github.io/gamlssx/
Licenses: GPL 3+
Build system: r
Synopsis: Generalized Additive Extreme Value Models for Location, Scale and Shape
Description:

Fits generalized additive models for the location, scale and shape parameters of a generalized extreme value response distribution. The methodology is based on Rigby, R.A. and Stasinopoulos, D.M. (2005), <doi:10.1111/j.1467-9876.2005.00510.x> and implemented using functions from the gamlss package <doi:10.32614/CRAN.package.gamlss>.

r-geocomplexity 0.2.1
Propagated dependencies: r-tibble@3.3.0 r-terra@1.8-86 r-sf@1.0-23 r-sdsfun@0.8.1 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-purrr@1.2.0 r-magrittr@2.0.4 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://ausgis.github.io/geocomplexity/
Licenses: GPL 3
Build system: r
Synopsis: Mitigating Spatial Bias Through Geographical Complexity
Description:

The geographical complexity of individual variables can be characterized by the differences in local attribute variables, while the common geographical complexity of multiple variables can be represented by fluctuations in the similarity of vectors composed of multiple variables. In spatial regression tasks, the goodness of fit can be improved by incorporating a geographical complexity representation vector during modeling, using a geographical complexity-weighted spatial weight matrix, or employing local geographical complexity kernel density. Similarly, in spatial sampling tasks, samples can be selected more effectively by using a method that weights based on geographical complexity. By optimizing performance in spatial regression and spatial sampling tasks, the spatial bias of the model can be effectively reduced.

r-gbifdb 1.0.0
Propagated dependencies: r-duckdbfs@0.1.2 r-dplyr@1.1.4 r-arrow@22.0.0
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://docs.ropensci.org/gbifdb/
Licenses: FSDG-compatible
Build system: r
Synopsis: High Performance Interface to 'GBIF'
Description:

This package provides a high performance interface to the Global Biodiversity Information Facility, GBIF'. In contrast to rgbif', which can access small subsets of GBIF data through web-based queries to a central server, gbifdb provides enhanced performance for R users performing large-scale analyses on servers and cloud computing providers, providing full support for arbitrary SQL or dplyr operations on the complete GBIF data tables (now over 1 billion records, and over a terabyte in size). gbifdb accesses a copy of the GBIF data in parquet format, which is already readily available in commercial computing clouds such as the Amazon Open Data portal and the Microsoft Planetary Computer, or can be accessed directly without downloading, or downloaded to any server with suitable bandwidth and storage space. The high-performance techniques for local and remote access are described in <https://duckdb.org/why_duckdb> and <https://arrow.apache.org/docs/r/articles/fs.html> respectively.

r-gjls2 0.2.0
Propagated dependencies: r-quantreg@6.1 r-plyr@1.8.9 r-nlme@3.1-168 r-moments@0.14.1 r-mcmcpack@1.7-1 r-mass@7.3-65 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=gJLS2
Licenses: GPL 3+
Build system: r
Synopsis: Generalized Joint Location and Scale Framework for Association Testing
Description:

An update to the Joint Location-Scale (JLS) testing framework that identifies associated SNPs, gene-sets and pathways with main and/or interaction effects on quantitative traits (Soave et al., 2015; <doi:10.1016/j.ajhg.2015.05.015>). The JLS method simultaneously tests the null hypothesis of equal mean and equal variance across genotypes, by aggregating association evidence from the individual location/mean-only and scale/variance-only tests using Fisher's method. The generalized joint location-scale (gJLS) framework has been developed to deal specifically with sample correlation and group uncertainty (Soave and Sun, 2017; <doi:10.1111/biom.12651>). The current release: gJLS2, include additional functionalities that enable analyses of X-chromosome genotype data through novel methods for location (Chen et al., 2021; <doi:10.1002/gepi.22422>) and scale (Deng et al., 2019; <doi:10.1002/gepi.22247>).

r-gcxgclab 1.1.0
Propagated dependencies: r-zoo@1.8-14 r-rdpack@2.6.4 r-ptw@1.9-16 r-nls-multstart@2.0.0 r-nilde@1.1-7 r-ncdf4@1.24 r-ggplot2@4.0.1 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://cran.r-project.org/package=gcxgclab
Licenses: GPL 3+
Build system: r
Synopsis: GCxGC Preprocessing and Analysis
Description:

This package provides complete detailed preprocessing of two-dimensional gas chromatogram (GCxGC) samples. Baseline correction, smoothing, peak detection, and peak alignment. Also provided are some analysis functions, such as finding extracted ion chromatograms, finding mass spectral data, targeted analysis, and nontargeted analysis with either the National Institute of Standards and Technology Mass Spectral Library or with the mass data. There are also several visualization methods provided for each step of the preprocessing and analysis.

r-growthrates 0.8.5
Propagated dependencies: r-lattice@0.22-7 r-fme@1.3.6.4 r-desolve@1.40
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/tpetzoldt/growthrates
Licenses: GPL 2+
Build system: r
Synopsis: Estimate Growth Rates from Experimental Data
Description:

This package provides a collection of methods to determine growth rates from experimental data, in particular from batch experiments and plate reader trials.

r-gsw 1.2-0
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: http://teos-10.github.io/GSW-R/
Licenses: GPL 2+ FSDG-compatible
Build system: r
Synopsis: Gibbs Sea Water Functions
Description:

This package provides an interface to the Gibbs SeaWater ('TEOS-10') C library, version 3.06-16-0 (commit 657216dd4f5ea079b5f0e021a4163e2d26893371', dated 2022-10-11, available at <https://github.com/TEOS-10/GSW-C>, which stems from Matlab and other code written by members of Working Group 127 of SCOR'/'IAPSO (Scientific Committee on Oceanic Research / International Association for the Physical Sciences of the Oceans).

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