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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-shadowr 0.0.2
Propagated dependencies: r-rselenium@1.7.9
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/ricilandolt/shadowr
Licenses: ASL 2.0
Build system: r
Synopsis: Selenium Plugin to Manage Multi Level Shadow Elements on Web Page
Description:

Shadow Document Object Model is a web standard that offers component style and markup encapsulation. It is a critically important piece of the Web Components story as it ensures that a component will work in any environment even if other CSS or JavaScript is at play on the page. Custom HTML tags can't be directly identified with selenium tools, because Selenium doesn't provide any way to deal with shadow elements. Using this plugin you can handle any custom HTML tags.

r-superpixelimagesegmentation 1.0.6
Propagated dependencies: r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-r6@2.6.1 r-openimager@1.3.0 r-lattice@0.22-7 r-clusterr@1.3.5
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/mlampros/SuperpixelImageSegmentation
Licenses: GPL 3
Build system: r
Synopsis: Superpixel Image Segmentation
Description:

Image Segmentation using Superpixels, Affinity Propagation and Kmeans Clustering. The R code is based primarily on the article "Image Segmentation using SLIC Superpixels and Affinity Propagation Clustering, Bao Zhou, International Journal of Science and Research (IJSR), 2013" <https://www.ijsr.net/archive/v4i4/SUB152869.pdf>.

r-survrm2perm 0.1.0
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=survRM2perm
Licenses: GPL 2
Build system: r
Synopsis: Permutation Test for Comparing Restricted Mean Survival Time
Description:

This package performs the permutation test using difference in the restricted mean survival time (RMST) between groups as a summary measure of the survival time distribution. When the sample size is less than 50 per group, it has been shown that there is non-negligible inflation of the type I error rate in the commonly used asymptotic test for the RMST comparison. Generally, permutation tests can be useful in such a situation. However, when we apply the permutation test for the RMST comparison, particularly in small sample situations, there are some cases where the survival function in either group cannot be defined due to censoring in the permutation process. Horiguchi and Uno (2020) <doi:10.1002/sim.8565> have examined six workable solutions to handle this numerical issue. It performs permutation tests with implementation of the six methods outlined in the paper when the numerical issue arises during the permutation process. The result of the asymptotic test is also provided for a reference.

r-spatialcovariance 0.6-9
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=spatialCovariance
Licenses: GPL 2+ GPL 3+
Build system: r
Synopsis: Computation of Spatial Covariance Matrices for Data on Rectangles
Description:

This package provides functions that compute the spatial covariance matrix for the matern and power classes of spatial models, for data that arise on rectangular units. This code can also be used for the change of support problem and for spatial data that arise on irregularly shaped regions like counties or zipcodes by laying a fine grid of rectangles and aggregating the integrals in a form of Riemann integration.

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-scriptmapr 0.0.3
Propagated dependencies: r-stringr@1.6.0 r-rcy3@2.30.0 r-formatr@1.14 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=ScriptMapR
Licenses: Expat
Build system: r
Synopsis: R Script Visualization in Cytoscape
Description:

Displays the content of a R script into the Cytoscape network-visualization app <https://cytoscape.org/>.

r-shinymaterial 1.2.0
Propagated dependencies: r-shiny@1.11.1 r-sass@0.4.10 r-jsonlite@2.0.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://ericrayanderson.github.io/shinymaterial/
Licenses: GPL 3 FSDG-compatible
Build system: r
Synopsis: Implement Material Design in Shiny Applications
Description:

Allows shiny developers to incorporate UI elements based on Google's Material design. See <https://material.io/guidelines/> for more information.

r-smdic 0.1.6
Propagated dependencies: r-survminer@0.5.1 r-survival@3.8-3 r-samr@3.0 r-rcolorbrewer@1.1-3 r-preprocesscore@1.72.0 r-pracma@2.4.6 r-pheatmap@1.0.13 r-mass@7.3-65 r-maftools@2.26.0 r-gsva@2.4.1 r-e1071@1.7-16 r-backports@1.5.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=SMDIC
Licenses: GPL 2+
Build system: r
Synopsis: Identification of Somatic Mutation-Driven Immune Cells
Description:

This package provides a computing tool is developed to automated identify somatic mutation-driven immune cells. The operation modes including: i) inferring the relative abundance matrix of tumor-infiltrating immune cells and integrating it with a particular gene mutation status, ii) detecting differential immune cells with respect to the gene mutation status and converting the abundance matrix of significant differential immune cell into two binary matrices (one for up-regulated and one for down-regulated), iii) identifying somatic mutation-driven immune cells by comparing the gene mutation status with each immune cell in the binary matrices across all samples, and iv) visualization of immune cell abundance of samples in different mutation status..

r-smile 1.1.0
Dependencies: proj@9.3.1 geos@3.12.1 gdal@3.8.2
Propagated dependencies: r-sf@1.0-23 r-rcppeigen@0.3.4.0.2 r-rcpp@1.1.0 r-numderiv@2016.8-1.1 r-mvtnorm@1.3-3 r-matrix@1.7-4
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://lcgodoy.me/smile/
Licenses: GPL 3
Build system: r
Synopsis: Spatial Misalignment: Interpolation, Linkage, and Estimation
Description:

This package provides functions to estimate, predict and interpolate areal data. For estimation and prediction we assume areal data is an average of an underlying continuous spatial process as in Moraga et al. (2017) <doi:10.1016/j.spasta.2017.04.006>, Johnson et al. (2020) <doi:10.1186/s12942-020-00200-w>, and Wilson and Wakefield (2020) <doi:10.1093/biostatistics/kxy041>. The interpolation methodology is (mostly) based on Goodchild and Lam (1980, ISSN:01652273).

r-ssgraph 1.16
Propagated dependencies: r-bdgraph@2.74
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://www.uva.nl/profile/a.mohammadi
Licenses: GPL 2+
Build system: r
Synopsis: Bayesian Graph Structure Learning using Spike-and-Slab Priors
Description:

Bayesian estimation for undirected graphical models using spike-and-slab priors. The package handles continuous, discrete, and mixed data.

r-svdialogstcltk 1.0.1
Propagated dependencies: r-svgui@1.0.2 r-svdialogs@1.1.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/SciViews/svDialogstcltk
Licenses: GPL 2
Build system: r
Synopsis: 'SciViews::R' - Standard Dialog Boxes using Tcl/Tk
Description:

Reimplementation of the svDialogs dialog boxes in Tcl/Tk.

r-synr 1.0.0
Propagated dependencies: r-ggplot2@4.0.1 r-dbscan@1.2.3 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://datalowe.github.io/synr/
Licenses: Expat
Build system: r
Synopsis: Explore and Process Synesthesia Consistency Test Data
Description:

Explore synesthesia consistency test data, calculate consistency scores, and classify participant data as valid or invalid.

r-scape 2.3.5
Propagated dependencies: r-lattice@0.22-7 r-hmisc@5.2-4 r-coda@0.19-4.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/arni-magnusson/scape
Licenses: GPL 3
Build system: r
Synopsis: Statistical Catch-at-Age Plotting Environment
Description:

Import, plot, and diagnose results from statistical catch-at-age models, used in fisheries stock assessment.

r-svycoxme 1.0.0
Propagated dependencies: r-survival@3.8-3 r-survey@4.4-8 r-rcpp@1.1.0 r-parallelly@1.45.1 r-matrix@1.7-4 r-lme4@1.1-37 r-future@1.68.0 r-coxme@2.2-22
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/bdrayton/svycoxme
Licenses: GPL 3+
Build system: r
Synopsis: Mixed-Effects Cox Models for Complex Samples
Description:

Mixed-effect proportional hazards models for multistage stratified, cluster-sampled, unequally weighted survey samples. Provides variance estimation by Taylor series linearisation or replicate weights.

r-scgoclust 0.2.1
Propagated dependencies: r-tidyr@1.3.1 r-tibble@3.3.0 r-slanter@0.2-0 r-seurat@5.3.1 r-networkd3@0.4.1 r-matrix@1.7-4 r-magrittr@2.0.4 r-limma@3.66.0 r-dplyr@1.1.4 r-biomart@2.66.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/Papatheodorou-Group/scGOclust
Licenses: GPL 3+
Build system: r
Synopsis: Measuring Cell Type Similarity with Gene Ontology in Single-Cell RNA-Seq
Description:

Traditional methods for analyzing single cell RNA-seq datasets focus solely on gene expression, but this package introduces a novel approach that goes beyond this limitation. Using Gene Ontology terms as features, the package allows for the functional profile of cell populations, and comparison within and between datasets from the same or different species. Our approach enables the discovery of previously unrecognized functional similarities and differences between cell types and has demonstrated success in identifying cell types functional correspondence even between evolutionarily distant species.

r-seecolor 0.2.0
Propagated dependencies: r-stringr@1.6.0 r-rstudioapi@0.17.1 r-purrr@1.2.0 r-magrittr@2.0.4 r-ggplot2@4.0.1 r-fansi@1.0.7 r-dplyr@1.1.4 r-crayon@1.5.3
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/lovestat/seecolor
Licenses: Expat
Build system: r
Synopsis: View Colors Used in R Objects in the Console
Description:

Output colors used in literal vectors, palettes and plot objects (ggplot).

r-sgmrfmix 0.3.0
Propagated dependencies: r-zoo@1.8-14 r-tidyr@1.3.1 r-mvtnorm@1.3-3 r-glasso@1.11 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=sGMRFmix
Licenses: Expat
Build system: r
Synopsis: Sparse Gaussian Markov Random Field Mixtures for Anomaly Detection
Description:

An implementation of sparse Gaussian Markov random field mixtures presented by Ide et al. (2016) <doi:10.1109/ICDM.2016.0119>. It provides a novel anomaly detection method for multivariate noisy sensor data. It can automatically handle multiple operational modes. And it can also compute variable-wise anomaly scores.

r-scaper 0.2.0
Propagated dependencies: r-xml2@1.5.0 r-vam@1.1.0 r-stringr@1.6.0 r-seuratobject@5.2.0 r-seurat@5.3.1 r-magrittr@2.0.4 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=scaper
Licenses: GPL 2+
Build system: r
Synopsis: Single Cell Transcriptomics-Level Cytokine Activity Prediction and Estimation
Description:

Generates cell-level cytokine activity estimates using relevant information from gene sets constructed with the CytoSig and the Reactome databases and scored using the modified Variance-adjusted Mahalanobis (VAM) framework for single-cell RNA-sequencing (scRNA-seq) data. CytoSig database is described in: Jiang at al., (2021) <doi:10.1038/s41592-021-01274-5>. Reactome database is described in: Gillespie et al., (2021) <doi:10.1093/nar/gkab1028>. The VAM method is outlined in: Frost (2020) <doi:10.1093/nar/gkaa582>.

r-summarytabl 0.2.1
Propagated dependencies: r-tidyr@1.3.1 r-tibble@3.3.0 r-rlang@1.1.6 r-purrr@1.2.0 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://anyamemensah.github.io/summarytabl/
Licenses: Expat
Build system: r
Synopsis: Generate Summary Tables for Categorical, Ordinal, and Continuous Data
Description:

This package provides functions for tabulating and summarizing categorical, multiple response, ordinal, and continuous variables in R data frames. Makes it easy to create clear, structured summary tables, so you spend less time wrangling data and more time interpreting it.

r-sparseltseigen 0.2.0.1
Propagated dependencies: r-robusthd@0.8.4 r-rcppeigen@0.3.4.0.2 r-rcpp@1.1.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=sparseLTSEigen
Licenses: GPL 2+
Build system: r
Synopsis: RcppEigen back end for sparse least trimmed squares regression
Description:

Use RcppEigen to fit least trimmed squares regression models with an L1 penalty in order to obtain sparse models.

r-snschart 1.4.0
Propagated dependencies: r-mass@7.3-65
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=SNSchart
Licenses: Expat
Build system: r
Synopsis: Sequential Normal Scores in Statistical Process Management
Description:

The methods discussed in this package are new non-parametric methods based on sequential normal scores SNS (Conover et al (2017) <doi:10.1080/07474946.2017.1360091>), designed for sequences of observations, usually time series data, which may occur singly or in batches, and may be univariate or multivariate. These methods are designed to detect changes in the process, which may occur as changes in location (mean or median), changes in scale (standard deviation, or variance), or other changes of interest in the distribution of the observations, over the time observed. They usually apply to large data sets, so computations need to be simple enough to be done in a reasonable time on a computer, and easily updated as each new observation (or batch of observations) becomes available. Some examples and more detail in SNS is presented in the work by Conover et al (2019) <arXiv:1901.04443>.

r-scatr 1.0.1
Propagated dependencies: r-r6@2.6.1 r-jmvcore@2.7.7 r-ggstance@0.3.7 r-ggridges@0.5.7 r-ggplot2@4.0.1 r-cowplot@1.2.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/raviselker/scatr
Licenses: GPL 2+
Build system: r
Synopsis: Create Scatter Plots with Marginal Density or Box Plots
Description:

Allows you to make clean, good-looking scatter plots with the option to easily add marginal density or box plots on the axes. It is also available as a module for jamovi (see <https://www.jamovi.org> for more information). Scatr is based on the cowplot package by Claus O. Wilke and the ggplot2 package by Hadley Wickham.

r-smoothtail 2.0.6
Propagated dependencies: r-logcondens@2.1.8
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: http://www.kasparrufibach.ch
Licenses: GPL 2+
Build system: r
Synopsis: Smooth Estimation of GPD Shape Parameter
Description:

Given independent and identically distributed observations X(1), ..., X(n) from a Generalized Pareto distribution with shape parameter gamma in [-1,0], offers several estimates to compute estimates of gamma. The estimates are based on the principle of replacing the order statistics by quantiles of a distribution function based on a log--concave density function. This procedure is justified by the fact that the GPD density is log--concave for gamma in [-1,0].

r-srvyr 1.3.1
Propagated dependencies: r-vctrs@0.6.5 r-tidyselect@1.2.1 r-tidyr@1.3.1 r-tibble@3.3.0 r-survey@4.4-8 r-rlang@1.1.6 r-magrittr@2.0.4 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: http://gdfe.co/srvyr/
Licenses: GPL 2 GPL 3
Build system: r
Synopsis: 'dplyr'-Like Syntax for Summary Statistics of Survey Data
Description:

Use piping, verbs like group_by and summarize', and other dplyr inspired syntactic style when calculating summary statistics on survey data using functions from the survey package.

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Total results: 69112