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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-spotr 0.1.0
Propagated dependencies: r-rcpp@1.1.0 r-mgcv@1.9-4
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=spotr
Licenses: GPL 3+
Build system: r
Synopsis: Estimate Spatial Population Indices from Ecological Abundance Data
Description:

Compute relative or absolute population trends across space and time using predictions from models fitted to ecological population abundance data, as described in Knape (2025) <doi:10.1016/j.ecolind.2025.113435>. The package supports models fitted by mgcv or brms', and draws from posterior predictive distributions.

r-snvecr 3.10.1
Propagated dependencies: r-tidyselect@1.2.1 r-tibble@3.3.0 r-stringr@1.6.0 r-rlang@1.1.6 r-readr@2.1.6 r-purrr@1.2.0 r-glue@1.8.0 r-dplyr@1.1.4 r-desolve@1.40 r-cli@3.6.5 r-backports@1.5.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://japhir.github.io/snvecR/
Licenses: GPL 3+
Build system: r
Synopsis: Calculate Earth’s Obliquity and Precession in the Past
Description:

Easily calculate precession and obliquity from an orbital solution (defaults to ZB18a from Zeebe and Lourens (2019) <doi:10.1126/science.aax0612>) and assumed or reconstructed values for tidal dissipation (Td) and dynamical ellipticity (Ed). This is a translation and adaptation of the C'-code in the supplementary material to Zeebe and Lourens (2022) <doi:10.1029/2021PA004349>, with further details on the methodology described in Zeebe (2022) <doi:10.3847/1538-3881/ac80f8>. The name of the C'-routine is snvec', which refers to the key units of computation: spin vector s and orbit normal vector n.

r-sdwd 1.0.5
Propagated dependencies: r-matrix@1.7-4
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=sdwd
Licenses: GPL 2
Build system: r
Synopsis: Sparse Distance Weighted Discrimination
Description:

Formulates a sparse distance weighted discrimination (SDWD) for high-dimensional classification and implements a very fast algorithm for computing its solution path with the L1, the elastic-net, and the adaptive elastic-net penalties. More details about the methodology SDWD is seen on Wang and Zou (2016) (<doi:10.1080/10618600.2015.1049700>).

r-spatentropy 2.2-4
Propagated dependencies: r-spatstat-random@3.4-3 r-spatstat-geom@3.6-1 r-spatstat@3.4-1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=SpatEntropy
Licenses: GPL 3
Build system: r
Synopsis: Spatial Entropy Measures
Description:

The heterogeneity of spatial data presenting a finite number of categories can be measured via computation of spatial entropy. Functions are available for the computation of the main entropy and spatial entropy measures in the literature. They include the traditional version of Shannon's entropy (Shannon, 1948 <doi:10.1002/j.1538-7305.1948.tb01338.x>), Batty's spatial entropy (Batty, 1974 <doi:10.1111/j.1538-4632.1974.tb01014.x>), O'Neill's entropy (O'Neill et al., 1998 <doi:10.1007/BF00162741>), Li and Reynolds contagion index (Li and Reynolds, 1993 <doi:10.1007/BF00125347>), Karlstrom and Ceccato's entropy (Karlstrom and Ceccato, 2002 <https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-61351>), Leibovici's entropy (Leibovici, 2009 <doi:10.1007/978-3-642-03832-7_24>), Parresol and Edwards entropy (Parresol and Edwards, 2014 <doi:10.3390/e16041842>) and Altieri's entropy (Altieri et al., 2018, <doi:10.1007/s10651-017-0383-1>). Full references for all measures can be found under the topic SpatEntropy'. The package is able to work with lattice and point data. The updated version works with the updated spatstat package (>= 3.0-2).

r-sith 1.1.0
Propagated dependencies: r-scatterplot3d@0.3-44 r-rcpp@1.1.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/phillipnicol/SITH
Licenses: GPL 2+
Build system: r
Synopsis: Spatial Model of Intra-Tumor Heterogeneity
Description:

This package implements a three-dimensional stochastic model of cancer growth and mutation similar to the one described in Waclaw et al. (2015) <doi:10.1038/nature14971>. Allows for interactive 3D visualizations of the simulated tumor. Provides a comprehensive summary of the spatial distribution of mutants within the tumor. Contains functions which create synthetic sequencing datasets from the generated tumor.

r-soundshape 1.3.2
Propagated dependencies: r-tuner@1.4.7 r-stringr@1.6.0 r-seewave@2.2.4 r-reshape2@1.4.5 r-plot3d@1.4.2 r-geomorph@4.0.10 r-abind@1.4-8
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/p-rocha/SoundShape
Licenses: GPL 3
Build system: r
Synopsis: Sound Waves Onto Morphometric Data
Description:

Implement a promising, and yet little explored protocol for bioacoustical analysis, the eigensound method by MacLeod, Krieger and Jones (2013) <doi:10.4404/hystrix-24.1-6299>. Eigensound is a multidisciplinary method focused on the direct comparison between stereotyped sounds from different species. SoundShape', in turn, provide the tools required for anyone to go from sound waves to Principal Components Analysis, using tools extracted from traditional bioacoustics (i.e. tuneR and seewave packages), geometric morphometrics (i.e. geomorph package) and multivariate analysis (e.g. stats package). For more information, please see Rocha and Romano (2021) and check SoundShape repository on GitHub for news and updates <https://github.com/p-rocha/SoundShape>.

r-survrm2 1.0-4
Propagated dependencies: r-survival@3.8-3
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=survRM2
Licenses: GPL 2
Build system: r
Synopsis: Comparing Restricted Mean Survival Time
Description:

This package performs two-sample comparisons using the restricted mean survival time (RMST) as a summary measure of the survival time distribution. Three kinds of between-group contrast metrics (i.e., the difference in RMST, the ratio of RMST and the ratio of the restricted mean time lost (RMTL)) are computed. It performs an ANCOVA-type covariate adjustment as well as unadjusted analyses for those measures.

r-sigora 3.1.1
Propagated dependencies: r-slam@0.1-55
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/wolski/sigora
Licenses: GPL 3
Build system: r
Synopsis: Signature Overrepresentation Analysis
Description:

Pathway Analysis is statistically linking observations on the molecular level to biological processes or pathways on the systems(i.e., organism, organ, tissue, cell) level. Traditionally, pathway analysis methods regard pathways as collections of single genes and treat all genes in a pathway as equally informative. However, this can lead to identifying spurious pathways as statistically significant since components are often shared amongst pathways. SIGORA seeks to avoid this pitfall by focusing on genes or gene pairs that are (as a combination) specific to a single pathway. In relying on such pathway gene-pair signatures (Pathway-GPS), SIGORA inherently uses the status of other genes in the experimental context to identify the most relevant pathways. The current version allows for pathway analysis of human and mouse datasets. In addition, it contains pre-computed Pathway-GPS data for pathways in the KEGG and Reactome pathway repositories and mechanisms for extracting GPS for user-supplied repositories.

r-scbiclust 1.0.2
Propagated dependencies: r-sparcl@1.0.4 r-sigclust@1.1.0.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=SCBiclust
Licenses: Expat
Build system: r
Synopsis: Identifies Mean, Variance, and Hierarchically Clustered Biclusters
Description:

Identifies a bicluster, a submatrix of the data such that the features and observations within the submatrix differ from those not contained in submatrix, using a two-step method. In the first step, observations in the bicluster are identified to maximize the sum of weighted between cluster feature differences. The method is described in Helgeson et al. (2020) <doi:10.1111/biom.13136>. SCBiclust can be used to identify biclusters which differ based on feature means, feature variances, or more general differences.

r-stablelearner 0.1-7
Propagated dependencies: r-ranger@0.17.0 r-randomforest@4.7-1.2 r-partykit@1.2-24 r-party@1.3-18 r-mass@7.3-65 r-e1071@1.7-16
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=stablelearner
Licenses: GPL 2 GPL 3
Build system: r
Synopsis: Stability Assessment of Statistical Learning Methods
Description:

Graphical and computational methods that can be used to assess the stability of results from supervised statistical learning.

r-statar 0.7.7
Propagated dependencies: r-tidyselect@1.2.1 r-stringr@1.6.0 r-rlang@1.1.6 r-matrixstats@1.5.0 r-lazyeval@0.2.2 r-ggplot2@4.0.1 r-dplyr@1.1.4 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/matthieugomez/statar
Licenses: GPL 2
Build system: r
Synopsis: Tools Inspired by 'Stata' to Manipulate Tabular Data
Description:

This package provides a set of tools inspired by Stata to explore data.frames ('summarize', tabulate', xtile', pctile', binscatter', elapsed quarters/month, lead/lag).

r-stocks 1.1.4
Propagated dependencies: r-zoo@1.8-14 r-ttr@0.24.4 r-rcpp@1.1.0 r-rcolorbrewer@1.1-3 r-rbenchmark@1.0.0 r-quantmod@0.4.28 r-lubridate@1.9.4 r-hmisc@5.2-4 r-dvmisc@1.1.4
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=stocks
Licenses: GPL 3
Build system: r
Synopsis: Stock Market Analysis
Description:

This package provides functions for analyzing stocks or other investments. Main features are loading and aligning historical data for ticker symbols, calculating performance metrics for individual funds or portfolios (e.g. annualized growth, maximum drawdown, Sharpe/Sortino ratio), and creating graphs. C++ code is used to improve processing speed where possible.

r-stats4teaching 0.1.0
Propagated dependencies: r-rstatix@0.7.3 r-pwr@1.3-0 r-psych@2.5.6 r-nortest@1.0-4 r-mvn@6.3 r-mass@7.3-65 r-knitr@1.50 r-clustergeneration@1.3.8 r-car@3.1-3 r-asbio@1.12-2
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=stats4teaching
Licenses: GPL 3
Build system: r
Synopsis: Simulate Pedagogical Statistical Data
Description:

Univariate and multivariate normal data simulation. They also supply a brief summary of the analysis for each experiment/design: - Independent samples. - One-way and two-way Anova. - Paired samples (T-Test & Regression). - Repeated measures (Anova & Multiple Regression). - Clinical Assay.

r-ssw 0.2.1
Dependencies: python@3.11.14
Propagated dependencies: r-reticulate@1.44.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://nanx.me/ssw-r/
Licenses: Expat
Build system: r
Synopsis: Striped Smith-Waterman Algorithm for Sequence Alignment using SIMD
Description:

This package provides an R interface for SSW (Striped Smith-Waterman) via its Python binding ssw-py'. SSW is a fast C and C++ implementation of the Smith-Waterman algorithm for pairwise sequence alignment using Single-Instruction-Multiple-Data (SIMD) instructions. SSW enhances the standard algorithm by efficiently returning alignment information and suboptimal alignment scores. The core SSW library offers performance improvements for various bioinformatics tasks, including protein database searches, short-read alignments, primary and split-read mapping, structural variant detection, and read-overlap graph generation. These features make SSW particularly useful for genomic applications. Zhao et al. (2013) <doi:10.1371/journal.pone.0082138> developed the original C and C++ implementation.

r-statgraph 1.0.6
Propagated dependencies: r-rarpack@0.11-0 r-mvtnorm@1.3-3 r-mass@7.3-65 r-igraph@2.2.1 r-foreach@1.5.2 r-doparallel@1.0.17 r-cluster@2.1.8.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://www.ime.usp.br/~fujita/software.html
Licenses: GPL 3+
Build system: r
Synopsis: Statistical Methods for Graphs
Description:

This package contains statistical methods to analyze graphs, such as graph parameter estimation, model selection based on the Graph Information Criterion, statistical tests to discriminate two or more populations of graphs, correlation between graphs, and clustering of graphs. References: Takahashi et al. (2012) <doi:10.1371/journal.pone.0049949>, Fujita et al. (2017) <doi:10.3389/fnins.2017.00066>, Fujita et al. (2017) <doi:10.1016/j.csda.2016.11.016>, Fujita et al. (2019) <doi:10.1093/comnet/cnz028>.

r-simile 1.3.4
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=Simile
Licenses: FSDG-compatible
Build system: r
Synopsis: Interact with Simile Models
Description:

Allows a Simile model saved as a compiled binary to be loaded, parameterized, executed and interrogated. This version works with Simile v6 on.

r-stratifiedmedicine 1.0.5
Propagated dependencies: r-survival@3.8-3 r-ranger@0.17.0 r-partykit@1.2-24 r-mvtnorm@1.3-3 r-glmnet@4.1-10 r-ggplot2@4.0.1 r-ggparty@1.0.0.1 r-dplyr@1.1.4 r-coin@1.4-3
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/thomasjemielita/StratifiedMedicine
Licenses: GPL 3
Build system: r
Synopsis: Stratified Medicine
Description:

This package provides a toolkit for stratified medicine, subgroup identification, and precision medicine. Current tools include (1) filtering models (reduce covariate space), (2) patient-level estimate models (counterfactual patient-level quantities, such as the conditional average treatment effect), (3) subgroup identification models (find subsets of patients with similar treatment effects), and (4) treatment effect estimation and inference (for the overall population and discovered subgroups). These tools can be customized and are directly used in PRISM (patient response identifiers for stratified medicine; Jemielita and Mehrotra 2019 <arXiv:1912.03337>. This package is in beta and will be continually updated.

r-scorpion 1.3.0
Propagated dependencies: r-rann@2.6.2 r-pbapply@1.7-4 r-matrix@1.7-4 r-irlba@2.3.5.1 r-igraph@2.2.1 r-dplyr@1.1.4 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=SCORPION
Licenses: GPL 3
Build system: r
Synopsis: Single Cell Oriented Reconstruction of PANDA Individual Optimized Networks
Description:

Constructs gene regulatory networks from single-cell gene expression data using the PANDA (Passing Attributes between Networks for Data Assimilation) algorithm.

r-sparselrmatrix 0.1.0
Propagated dependencies: r-rspectra@0.16-2 r-matrix@1.7-4
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://rohelab.github.io/sparseLRMatrix/
Licenses: Expat
Build system: r
Synopsis: Represent and Use Sparse + Low Rank Matrices
Description:

This package provides an S4 class for representing and interacting with sparse plus rank matrices. At the moment the implementation is quite spare, but the plan is eventually subclass Matrix objects.

r-subvis 2.0.2
Propagated dependencies: r-shiny@1.11.1 r-biostrings@2.78.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=SubVis
Licenses: GPL 3
Build system: r
Synopsis: Visual Exploration of Protein Alignments Resulting from Multiple Substitution Matrices
Description:

Substitution matrices are important parameters in protein alignment algorithms. These matrices represent the likelihood that an amino acid will be substituted for another during mutation. This tool allows users to apply predefined and custom matrices and then explore the resulting alignments with interactive visualizations. SubVis requires the availability of a web browser.

r-shinygovstyle 0.1.1
Propagated dependencies: r-stringr@1.6.0 r-shinyjs@2.1.0 r-shiny@1.11.1 r-purrr@1.2.0 r-magrittr@2.0.4 r-jsonlite@2.0.0 r-htmltools@0.5.8.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/dfe-analytical-services/shinyGovstyle
Licenses: GPL 3
Build system: r
Synopsis: Custom Gov Style Inputs for Shiny
Description:

Collection of shiny application styling that are the based on the GOV.UK Design System. See <https://design-system.service.gov.uk/components/> for details.

r-saehb-me-beta 1.1.0
Propagated dependencies: r-stringr@1.6.0 r-rjags@4-17 r-coda@0.19-4.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/ratihrodliyah/saeHB.ME.beta
Licenses: GPL 3
Build system: r
Synopsis: SAE with Measurement Error using HB under Beta Distribution
Description:

Implementation of Small Area Estimation (SAE) using Hierarchical Bayesian (HB) Method when auxiliary variable measured with error under Beta Distribution. The rjags package is employed to obtain parameter estimates. For the references, see J.N.K & Molina (2015) <doi:10.1002/9781118735855>, Ybarra and Sharon (2008) <doi:10.1093/biomet/asn048>, and Ntzoufras (2009, ISBN-10: 1118210352).

r-streamsampler 0.1.0
Propagated dependencies: r-slider@0.3.3
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/Kyle-Hurley/streamsampler
Licenses: CC0
Build system: r
Synopsis: Characterize and Subsample Stream Data
Description:

Characterize daily stream discharge and water quality data and subsample water quality data. Provide dates, discharge, and water quality measurements and streamsampler can find gaps, get summary statistics, and subsample according to common stream sampling protocols. Stream sampling protocols are described in Lee et al. (2016) <doi:10.1016/j.jhydrol.2016.08.059> and Lee et al. (2019) <doi:10.3133/sir20195084>.

r-swcrtdesign 4.1
Propagated dependencies: r-lmertest@3.1-3 r-lme4@1.1-37 r-glmmtmb@1.1.13
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=swCRTdesign
Licenses: GPL 2
Build system: r
Synopsis: Stepped Wedge Cluster Randomized Trial (SW CRT) Design
Description:

This package provides a set of tools for examining the design and analysis aspects of stepped wedge cluster randomized trials (SW CRT) based on a repeated cross-sectional or cohort sampling scheme (Hussey MA and Hughes JP (2007) Contemporary Clinical Trials 28:182-191).

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