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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-pgmm 1.2.8
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=pgmm
Licenses: GPL 2+
Build system: r
Synopsis: Parsimonious Gaussian Mixture Models
Description:

Carries out model-based clustering or classification using parsimonious Gaussian mixture models. McNicholas and Murphy (2008) <doi:10.1007/s11222-008-9056-0>, McNicholas (2010) <doi:10.1016/j.jspi.2009.11.006>, McNicholas and Murphy (2010) <doi:10.1093/bioinformatics/btq498>, McNicholas et al. (2010) <doi:10.1016/j.csda.2009.02.011>.

r-proverbs 0.4.0
Propagated dependencies: r-stringr@1.6.0 r-rvest@1.0.5 r-purrr@1.2.0 r-lubridate@1.9.4 r-httr2@1.2.1 r-glue@1.8.0 r-crayon@1.5.3 r-cli@3.6.5 r-checkmate@2.3.3
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/bradlindblad/proverbs
Licenses: Expat
Build system: r
Synopsis: Print a Daily Bible Proverb to Console
Description:

This package provides a simple package to grab a Bible proverb corresponding to the day of the month.

r-permubiome 1.3.2
Propagated dependencies: r-rlang@1.1.6 r-matrix@1.7-4 r-gridextra@2.3 r-ggplot2@4.0.1 r-dplyr@1.1.4 r-dabestr@2025.3.15
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=permubiome
Licenses: GPL 3
Build system: r
Synopsis: Permutation Based Test for Biomarker Discovery in Microbiome Data
Description:

The permubiome R package was created to perform a permutation-based non-parametric analysis on microbiome data for biomarker discovery aims. This test executes thousands of comparisons in a pairwise manner, after a random shuffling of data into the different groups of study with a prior selection of the microbiome features with the largest variation among groups. Previous to the permutation test itself, data can be normalized according to different methods proposed to handle microbiome data ('proportions or Anders'). The median-based differences between groups resulting from the multiple simulations are fitted to a normal distribution with the aim to calculate their significance. A multiple testing correction based on Benjamini-Hochberg method (fdr) is finally applied to extract the differentially presented features between groups of your dataset. LATEST UPDATES: v1.1 and olders incorporates function to parse COLUMN format; v1.2 and olders incorporates -optimize- function to maximize evaluation of features with largest inter-class variation; v1.3 and olders includes the -size.effect- function to perform estimation statistics using the bootstrap-coupled approach implemented in the dabestr (>=0.3.0) R package. Current v1.3.2 fixed bug with "Class" recognition and updated dabestr functions.

r-paleobuddy 1.1.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/brpetrucci/paleobuddy
Licenses: GPL 3
Build system: r
Synopsis: Simulating Diversification Dynamics
Description:

Simulation of species diversification, fossil records, and phylogenies. While the literature on species birth-death simulators is extensive, including important software like paleotree and APE', we concluded there were interesting gaps to be filled regarding possible diversification scenarios. Here we strove for flexibility over focus, implementing a large array of regimens for users to experiment with and combine. In this way, paleobuddy can be used in complement to other simulators as a flexible jack of all trades, or, in the case of scenarios implemented only here, can allow for robust and easy simulations for novel situations. Environmental data modified from that in RPANDA': Morlon H. et al (2016) <doi:10.1111/2041-210X.12526>.

r-polypatex 0.9.2
Propagated dependencies: r-gtools@3.9.5
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=PolyPatEx
Licenses: FSDG-compatible
Build system: r
Synopsis: Paternity Exclusion in Autopolyploid Species
Description:

This package provides functions to perform paternity exclusion via allele matching, in autopolyploid species having ploidy 4, 6, or 8. The marker data used can be genotype data (copy numbers known) or allelic phenotype data (copy numbers not known).

r-piecemaker 1.0.2
Propagated dependencies: r-stringr@1.6.0 r-stringi@1.8.7 r-rlang@1.1.6 r-glue@1.8.0 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/macmillancontentscience/piecemaker
Licenses: FSDG-compatible
Build system: r
Synopsis: Tools for Preparing Text for Tokenizers
Description:

Tokenizers break text into pieces that are more usable by machine learning models. Many tokenizers share some preparation steps. This package provides those shared steps, along with a simple tokenizer.

r-pannotator 1.0.0.4
Propagated dependencies: r-stringr@1.6.0 r-shinywidgets@0.9.0 r-shinythemes@1.2.0 r-shinyjs@2.1.0 r-shinyhelper@0.3.2 r-shinyfiles@0.9.3 r-shiny@1.11.1 r-sf@1.0-23 r-scales@1.4.0 r-readr@2.1.6 r-magrittr@2.0.4 r-leafpm@0.1.0 r-leaflet-extras@2.0.1 r-leaflet@2.2.3 r-jsonlite@2.0.0 r-jsonify@1.2.3 r-jpeg@0.1-11 r-htmlwidgets@1.6.4 r-golem@0.5.1 r-ggplot2@4.0.1 r-geojsonsf@2.0.5 r-exiftoolr@0.2.8 r-dplyr@1.1.4 r-configr@0.3.5 r-config@0.3.2 r-colourpicker@1.3.0 r-bslib@0.9.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/NunzioKnerr/pannotator_package_source
Licenses: GPL 3+
Build system: r
Synopsis: Visualisation and Annotation of 360 Degree Imagery
Description:

This package provides a customisable R shiny app for immersively visualising, mapping and annotating panospheric (360 degree) imagery. The flexible interface allows annotation of any geocoded images using up to 4 user specified dropdown menus. The app uses leaflet to render maps that display the geo-locations of images and panellum <https://pannellum.org/>, a lightweight panorama viewer for the web, to render images in virtual 360 degree viewing mode. Key functions include the ability to draw on & export parts of 360 images for downstream applications. Users can also draw polygons and points on map imagery related to the panoramic images and export them for further analysis. Downstream applications include using annotations to train Artificial Intelligence/Machine Learning (AI/ML) models and geospatial modelling and analysis of camera based survey data.

r-pas 1.2.5
Propagated dependencies: r-glmnet@4.1-10
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: http://statgen.ucr.edu
Licenses: GPL 2+
Build system: r
Synopsis: Polygenic Analysis System (PAS)
Description:

An R package for polygenic trait analysis.

r-pooh 0.3-2
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: http://www.stat.umn.edu/geyer/pooh/
Licenses: Expat
Build system: r
Synopsis: Partial Orders and Relations
Description:

Finds equivalence classes corresponding to a symmetric relation or undirected graph. Finds total order consistent with partial order or directed graph (so-called topological sort).

r-powerpls 0.2.1
Propagated dependencies: r-simukde@1.3.0 r-proc@1.19.0.1 r-nipals@1.0 r-mvtnorm@1.3-3 r-mass@7.3-65 r-ks@1.15.1 r-foreach@1.5.2 r-fksum@1.0.1 r-compositions@2.0-9 r-caret@7.0-1
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/angeella/powerPLS
Licenses: GPL 2+
Build system: r
Synopsis: Power Analysis for PLS Classification
Description:

It estimates power and sample size for Partial Least Squares-based methods described in Andreella, et al., (2024), <doi:10.48550/arXiv.2403.10289>.

r-pinp 0.0.11
Propagated dependencies: r-rmarkdown@2.30 r-knitr@1.50
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/eddelbuettel/pinp
Licenses: GPL 3
Build system: r
Synopsis: 'pinp' is not 'PNAS'
Description:

This package provides a PNAS'-alike style for rmarkdown', derived from the Proceedings of the National Academy of Sciences of the United States of America ('PNAS') LaTeX style, and adapted for use with markdown and pandoc'.

r-pcfactorstan 1.5.4
Propagated dependencies: r-stanheaders@2.32.10 r-rstantools@2.5.0 r-rstan@2.32.7 r-reshape2@1.4.5 r-rcppparallel@5.1.11-1 r-rcppeigen@0.3.4.0.2 r-rcpp@1.1.0 r-mvtnorm@1.3-3 r-loo@2.8.0 r-lifecycle@1.0.4 r-igraph@2.2.1 r-bh@1.87.0-1
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/jpritikin/pcFactorStan
Licenses: GPL 3+
Build system: r
Synopsis: Stan Models for the Paired Comparison Factor Model
Description:

This package provides convenience functions and pre-programmed Stan models related to the paired comparison factor model. Its purpose is to make fitting paired comparison data using Stan easy. This package is described in Pritikin (2020) <doi:10.1016/j.heliyon.2020.e04821>.

r-prettycols 1.1.0
Propagated dependencies: r-lifecycle@1.0.4 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://nrennie.rbind.io/PrettyCols/
Licenses: CC0
Build system: r
Synopsis: Pretty Colour Palettes
Description:

Defines aesthetically pleasing colour palettes.

r-pathfindr 2.7.0
Dependencies: openjdk@25
Propagated dependencies: r-rmarkdown@2.30 r-r-utils@2.13.0 r-pathfindr-data@2.1.0 r-msigdbr@25.1.1 r-knitr@1.50 r-igraph@2.2.1 r-httr@1.4.7 r-ggupset@0.4.1 r-ggraph@2.2.2 r-ggplot2@4.0.1 r-fpc@2.2-13 r-foreach@1.5.2 r-doparallel@1.0.17 r-dbi@1.2.3 r-annotationdbi@1.72.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://egeulgen.github.io/pathfindR/
Licenses: Expat
Build system: r
Synopsis: Enrichment Analysis Utilizing Active Subnetworks
Description:

Enrichment analysis enables researchers to uncover mechanisms underlying a phenotype. However, conventional methods for enrichment analysis do not take into account protein-protein interaction information, resulting in incomplete conclusions. pathfindR is a tool for enrichment analysis utilizing active subnetworks. The main function identifies active subnetworks in a protein-protein interaction network using a user-provided list of genes and associated p values. It then performs enrichment analyses on the identified subnetworks, identifying enriched terms (i.e. pathways or, more broadly, gene sets) that possibly underlie the phenotype of interest. pathfindR also offers functionalities to cluster the enriched terms and identify representative terms in each cluster, to score the enriched terms per sample and to visualize analysis results. The enrichment, clustering and other methods implemented in pathfindR are described in detail in Ulgen E, Ozisik O, Sezerman OU. 2019. pathfindR': An R Package for Comprehensive Identification of Enriched Pathways in Omics Data Through Active Subnetworks. Front. Genet. <doi:10.3389/fgene.2019.00858>.

r-polytree 0.0.1
Propagated dependencies: r-igraph@2.2.1 r-foci@0.1.3
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=PolyTree
Licenses: Expat
Build system: r
Synopsis: Estimate Causal Polytree from Data
Description:

Given a data matrix with rows representing data vectors and columns representing variables, produces a directed polytree for the underlying causal structure. Based on the algorithm developed in Chatterjee and Vidyasagar (2022) <arxiv:2209.07028>. The method is fully nonparametric, making no use of linearity assumptions, and especially useful when the number of variables is large.

r-panalysis 2.0
Propagated dependencies: r-ggplot2@4.0.1 r-coin@1.4-3
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=pAnalysis
Licenses: GPL 2
Build system: r
Synopsis: Benchmarking and Rescaling R2 using Noise Percentile Analysis
Description:

This package provides the tools needed to benchmark the R2 value corresponding to a certain acceptable noise level while also providing a rescaling function based on that noise level yielding a new value of R2 we refer to as R2k which is independent of both the number of degrees of freedom and the noise distribution function.

r-posir 0.1.2
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/Chukyhenry/PosiR
Licenses: Expat
Build system: r
Synopsis: Post-Selection Inference via Simultaneous Confidence Intervals
Description:

Post-selection inference in linear regression models, constructing simultaneous confidence intervals across a user-specified universe of models. Implements the methodology described in Kuchibhotla, Kolassa, and Kuffner (2022) "Post-Selection Inference" <doi:10.1146/annurev-statistics-100421-044639> to ensure valid inference after model selection, with applications in high-dimensional settings like Lasso selection.

r-pedalfast-data 1.0.2
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=pedalfast.data
Licenses: GPL 2
Build system: r
Synopsis: PEDALFAST Data
Description:

Data files and documentation for PEDiatric vALidation oF vAriableS in TBI (PEDALFAST). The data was used in "Functional Status Scale in Children With Traumatic Brain Injury: A Prospective Cohort Study" by Bennett, Dixon, et al (2016) <doi:10.1097/PCC.0000000000000934>.

r-panelhetero 1.0.1
Propagated dependencies: r-rearrangement@2.1 r-kernsmooth@2.23-26 r-ggplot2@4.0.1 r-boot@1.3-32
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://tkhdyanagi.github.io/panelhetero/
Licenses: Expat
Build system: r
Synopsis: Panel Data Analysis with Heterogeneous Dynamics
Description:

Understanding the dynamics of potentially heterogeneous variables is important in statistical applications. This package provides tools for estimating the degree of heterogeneity across cross-sectional units in the panel data analysis. The methods are developed by Okui and Yanagi (2019) <doi:10.1016/j.jeconom.2019.04.036> and Okui and Yanagi (2020) <doi:10.1093/ectj/utz019>.

r-promethee123 0.1.0
Propagated dependencies: r-ggplot2@4.0.1 r-cowplot@1.2.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=promethee123
Licenses: GPL 3
Build system: r
Synopsis: PROMETHEE I, II, and III Methods
Description:

The PROMETHEE method is a multi-criteria decision-making method addressing with outranking problems. The method establishes a preference structure between the alternatives, having a preference function for each criterion. IN this context, three variants of the method is carried out: PROMETHEE I (Partial Outranking), PROMETHEE II (Total Outranking), and PROMETHEE III (Outranking by Intervals).

r-pogromcydanych 1.7.1
Propagated dependencies: r-smarterpoland@1.8.1 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=PogromcyDanych
Licenses: GPL 3
Build system: r
Synopsis: DataCrunchers (PogromcyDanych) is the Massive Online Open Course that Brings R and Statistics to the People
Description:

The data sets used in the online course ,,PogromcyDanych''. You can process data in many ways. The course Data Crunchers will introduce you to this variety. For this reason we will work on datasets of different size (from several to several hundred thousand rows), with various level of complexity (from two to two thousand columns) and prepared in different formats (text data, quantitative data and qualitative data). All of these data sets were gathered in a single big package called PogromcyDanych to facilitate access to them. It contains all sorts of data sets such as data about offer prices of cars, results of opinion polls, information about changes in stock market indices, data about names given to newborn babies, ski jumping results or information about outcomes of breast cancer patients treatment.

r-pcalls 1.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=pcalls
Licenses: GPL 3
Build system: r
Synopsis: Pricing of Different Types of Call
Description:

Compute the price of different types of call using different methods. The types available are Vanilla European Calls, Vanilla American Calls and American Digital Calls. Available methods are Montecarlo Simulation, Montecarlo Simulation with Antithetic Variates, Black-Scholes and the Binary Tree.

r-popgenhelpr 1.4.2
Propagated dependencies: r-vcfr@1.15.0 r-terra@1.8-86 r-spdep@1.4-1 r-sf@1.0-23 r-scatterpie@0.2.6 r-rlang@1.1.6 r-reshape2@1.4.5 r-magrittr@2.0.4 r-ggspatial@1.1.10 r-ggplot2@4.0.1 r-geodata@0.6-6 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://kfarleigh.github.io/PopGenHelpR/
Licenses: GPL 3+
Build system: r
Synopsis: Streamline Population Genomic and Genetic Analyses
Description:

Estimate commonly used population genomic statistics and generate publication quality figures. PopGenHelpR uses vcf, geno (012), and csv files to generate output.

r-peakram 1.0.2
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: http://github.com/tpq/peakRAM
Licenses: GPL 2
Build system: r
Synopsis: Monitor the Total and Peak RAM Used by an Expression or Function
Description:

When working with big data sets, RAM conservation is critically important. However, it is not always enough to just monitor the size of the objects created. So-called "copy-on-modify" behavior, characteristic of R, means that some expressions or functions may require an unexpectedly large amount of RAM overhead. For example, replacing a single value in a matrix duplicates that matrix in the back-end, making this task require twice as much RAM as that used by the matrix itself. This package makes it easy to monitor the total and peak RAM used so that developers can quickly identify and eliminate RAM hungry code.

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