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

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-todor 0.1.2
Propagated dependencies: r-stringr@1.6.0 r-rstudioapi@0.17.1 r-rex@1.2.1 r-r-utils@2.13.0
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://cran.r-project.org/package=todor
Licenses: Expat
Build system: r
Synopsis: Find All TODO Comments and More
Description:

This is a simple addin to RStudio that finds all TODO', FIX ME', CHANGED etc. comments in your project and shows them as a markers list.

r-tidypopgen 0.4.3
Dependencies: zlib@1.3.1
Propagated dependencies: r-vctrs@0.6.5 r-upsetr@1.4.0 r-tidyselect@1.2.1 r-tidyr@1.3.1 r-tibble@3.3.0 r-sf@1.0-23 r-runner@0.4.4 r-rmio@0.4.0 r-rlang@1.1.6 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-patchwork@1.3.2 r-mass@7.3-65 r-ggplot2@4.0.1 r-generics@0.1.4 r-foreach@1.5.2 r-dplyr@1.1.4 r-bigstatsr@1.6.2 r-bigsnpr@1.12.21 r-bigparallelr@0.3.2
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/EvolEcolGroup/tidypopgen
Licenses: GPL 3+
Build system: r
Synopsis: Tidy Population Genetics
Description:

We provide a tidy grammar of population genetics, facilitating the manipulation and analysis of data on biallelic single nucleotide polymorphisms (SNPs). tidypopgen scales to very large genetic datasets by storing genotypes on disk, and performing operations on them in chunks, without ever loading all data in memory. The full functionalities of the package are described in Carter et al. (2025) <doi:10.1111/2041-210x.70204>.

r-tidylpa 1.1.0
Propagated dependencies: r-tibble@3.3.0 r-mplusautomation@1.2 r-mix@1.0-13 r-mclust@6.1.2 r-gtable@0.3.6 r-ggplot2@4.0.1 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://data-edu.github.io/tidyLPA/
Licenses: Expat
Build system: r
Synopsis: Easily Carry Out Latent Profile Analysis (LPA) Using Open-Source or Commercial Software
Description:

An interface to the mclust package to easily carry out latent profile analysis ("LPA"). Provides functionality to estimate commonly-specified models. Follows a tidy approach, in that output is in the form of a data frame that can subsequently be computed on. Also has functions to interface to the commercial MPlus software via the MplusAutomation package.

r-tdavec 0.1.41
Propagated dependencies: r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/uislambekov/TDAvec
Licenses: GPL 2+
Build system: r
Synopsis: Vector Summaries of Persistence Diagrams
Description:

This package provides tools for computing various vector summaries of persistence diagrams studied in Topological Data Analysis. For improved computational efficiency, all code for the vector summaries is written in C++ using the Rcpp and RcppArmadillo packages.

r-trenchr 1.1.1
Propagated dependencies: r-zoo@1.8-14 r-rdpack@2.6.4 r-msm@1.8.2 r-desolve@1.40
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://trenchproject.github.io/TrenchR/
Licenses: Expat
Build system: r
Synopsis: Tools for Microclimate and Biophysical Ecology
Description:

This package provides tools for translating environmental change into organismal response. Microclimate models to vertically scale weather station data to organismal heights. The biophysical modeling tools include both general models for heat flows and specific models to predict body temperatures for a variety of ectothermic taxa. Additional functions model and temporally partition air and soil temperatures and solar radiation. Utility functions estimate the organismal and environmental parameters needed for biophysical ecology. TrenchR focuses on relatively simple and modular functions so users can create transparent and flexible biophysical models. Many functions are derived from Gates (1980) <doi:10.1007/978-1-4612-6024-0> and Campbell and Norman (1988) <isbn:9780387949376>.

r-threshr 1.0.7
Propagated dependencies: r-rust@1.4.4 r-revdbayes@1.5.6
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://paulnorthrop.github.io/threshr/
Licenses: GPL 2+
Build system: r
Synopsis: Threshold Selection and Uncertainty for Extreme Value Analysis
Description:

This package provides functions for the selection of thresholds for use in extreme value models, based mainly on the methodology in Northrop, Attalides and Jonathan (2017) <doi:10.1111/rssc.12159>. It also performs predictive inferences about future extreme values, based either on a single threshold or on a weighted average of inferences from multiple thresholds, using the revdbayes package <https://cran.r-project.org/package=revdbayes>. At the moment only the case where the data can be treated as independent identically distributed observations is considered.

r-teal-data 0.8.0
Propagated dependencies: r-teal-code@0.7.1 r-rlang@1.1.6 r-lifecycle@1.0.4 r-checkmate@2.3.3
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://insightsengineering.github.io/teal.data/
Licenses: ASL 2.0
Build system: r
Synopsis: Data Model for 'teal' Applications
Description:

This package provides a teal_data class as a unified data model for teal applications focusing on reproducibility and relational data.

r-trip 1.10.0
Propagated dependencies: r-viridis@0.6.5 r-traipse@0.3.0 r-spatstat-geom@3.6-1 r-spatstat-explore@3.6-0 r-sp@2.2-0 r-rlang@1.1.6 r-reproj@0.7.0 r-raster@3.6-32 r-mass@7.3-65 r-glue@1.8.0 r-geodist@0.1.1 r-dplyr@1.1.4 r-crsmeta@0.3.0
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/Trackage/trip
Licenses: GPL 3
Build system: r
Synopsis: Tracking Data
Description:

Access and manipulate spatial tracking data, with straightforward coercion from and to other formats. Filter for speed and create time spent maps from tracking data. There are coercion methods to convert between trip and ltraj from adehabitatLT', and between trip and psp and ppp from spatstat'. Trip objects can be created from raw or grouped data frames, and from types in the sp', sf', amt', trackeR', mousetrap', and other packages, Sumner, MD (2011) <https://figshare.utas.edu.au/articles/thesis/The_tag_location_problem/23209538>.

r-thestats 0.1.0
Propagated dependencies: r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/analyticsresearchlab/thestats
Licenses: GPL 3
Build system: r
Synopsis: R Package for Exploring Turkish Higher Education Statistics
Description:

This package provides a user-friendly R data package that is intended to make Turkish higher education statistics more accessible.

r-theft 0.8.2
Propagated dependencies: r-tsibble@1.2.0 r-tsfeatures@1.1.1 r-tidyr@1.3.1 r-rlang@1.1.6 r-reticulate@1.44.1 r-rcatch22@0.2.3 r-r-matlab@3.7.0 r-purrr@1.2.0 r-feasts@0.5.0 r-fabletools@0.6.0 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://hendersontrent.github.io/theft/
Licenses: Expat
Build system: r
Synopsis: Tools for Handling Extraction of Features from Time Series
Description:

Consolidates and calculates different sets of time-series features from multiple R and Python packages including Rcatch22 Henderson, T. (2021) <doi:10.5281/zenodo.5546815>, feasts O'Hara-Wild, M., Hyndman, R., and Wang, E. (2021) <https://CRAN.R-project.org/package=feasts>, tsfeatures Hyndman, R., Kang, Y., Montero-Manso, P., Talagala, T., Wang, E., Yang, Y., and O'Hara-Wild, M. (2020) <https://CRAN.R-project.org/package=tsfeatures>, tsfresh Christ, M., Braun, N., Neuffer, J., and Kempa-Liehr A.W. (2018) <doi:10.1016/j.neucom.2018.03.067>, TSFEL Barandas, M., et al. (2020) <doi:10.1016/j.softx.2020.100456>, and Kats Facebook Infrastructure Data Science (2021) <https://facebookresearch.github.io/Kats/>.

r-tgs 1.0.1
Propagated dependencies: r-rjson@0.2.23 r-minet@3.68.0 r-ggm@2.5.2 r-foreach@1.5.2 r-doparallel@1.0.17 r-bnstruct@1.0.15
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://www.biorxiv.org/content/early/2018/06/14/272484
Licenses: FSDG-compatible
Build system: r
Synopsis: Rapid Reconstruction of Time-Varying Gene Regulatory Networks
Description:
Rapid advancements in high-throughput gene sequencing technologies have resulted in genome-scale time-series datasets. Uncovering the underlying temporal sequence of gene regulatory events in the form of time-varying gene regulatory networks demands accurate and computationally efficient algorithms. Such an algorithm is TGS'. It is proposed in Saptarshi Pyne, Alok Ranjan Kumar, and Ashish Anand. Rapid reconstruction of time-varying gene regulatory networks. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 17(1):278{291, Jan-Feb 2020. The TGS algorithm is shown to consume only 29 minutes for a microarray dataset with 4028 genes. This package provides an implementation of the TGS algorithm and its variants.
r-t4transport 0.1.8
Propagated dependencies: r-rdpack@2.6.4 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://www.kisungyou.com/T4transport/
Licenses: Expat
Build system: r
Synopsis: Tools for Computational Optimal Transport
Description:

Transport theory has seen much success in many fields of statistics and machine learning. We provide a variety of algorithms to compute Wasserstein distance, barycenter, and others. See Peyré and Cuturi (2019) <doi:10.1561/2200000073> for the general exposition to the study of computational optimal transport.

r-tempcont 0.1.0
Propagated dependencies: r-nlme@3.1-168
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/burriach/tempcont
Licenses: GPL 2+
Build system: r
Synopsis: Temporal Contributions on Trends using Mixed Models
Description:

Method to estimate the effect of the trend in predictor variables on the observed trend of the response variable using mixed models with temporal autocorrelation. See Fernández-Martà nez et al. (2017 and 2019) <doi:10.1038/s41598-017-08755-8> <doi:10.1038/s41558-018-0367-7>.

r-tsgsis 0.1
Propagated dependencies: r-mass@7.3-65 r-glmnet@4.1-10
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://cran.r-project.org/package=TSGSIS
Licenses: GPL 2+
Build system: r
Synopsis: Two Stage-Grouped Sure Independence Screening
Description:

To provide a high dimensional grouped variable selection approach for detection of whole-genome SNP effects and SNP-SNP interactions, as described in Fang et al. (2017, under review).

r-tabxplor 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-stringr@1.6.0 r-stringi@1.8.7 r-rlang@1.1.6 r-purrr@1.2.0 r-pillar@1.11.1 r-magrittr@2.0.4 r-kableextra@1.4.0 r-forcats@1.0.1 r-dplyr@1.1.4 r-desctools@0.99.60 r-data-table@1.17.8 r-crayon@1.5.3 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/BriceNocenti/tabxplor
Licenses: GPL 3+
Build system: r
Synopsis: User-Friendly Tables with Color Helpers for Data Exploration
Description:

Make it easy to deal with multiple cross-tables in data exploration, by creating them, manipulating them, and adding color helpers to highlight important informations (differences from totals, comparisons between lines or columns, contributions to variance, confidence intervals, odds ratios, etc.). All functions are pipe-friendly and render data frames which can be easily manipulated. In the same time, time-taking operations are done with data.table to go faster with big dataframes. Tables can be exported with formats and colors to Excel', plot and html.

r-tfarima 0.4.1
Propagated dependencies: r-zoo@1.8-14 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-quadprog@1.5-8 r-numderiv@2016.8-1.1 r-nnls@1.6 r-mass@7.3-65
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/gallegoj/tfarima
Licenses: GPL 2+
Build system: r
Synopsis: Transfer Function and ARIMA Models
Description:

Build customized transfer function and ARIMA models with multiple operators and parameter restrictions. Provides tools for model identification, estimation using exact or conditional maximum likelihood, diagnostic checking, automatic outlier detection, calendar effects, forecasting, and seasonal adjustment. The new version also supports unobserved component ARIMA model specification and estimation for structural time series analysis.

r-twfeivdecomp 0.1.0
Propagated dependencies: r-magrittr@2.0.4 r-formula@1.2-5 r-dplyr@1.1.4 r-aer@1.2-15
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/shomiyaji/twfeiv-decomp
Licenses: Expat
Build system: r
Synopsis: Instrumented Difference-in-Differences Decomposition
Description:

This package implements a decomposition of the two-way fixed effects instrumental variable estimator into all possible Wald difference-in-differences estimators. Provides functions to summarize the contribution of different cohort comparisons to the overall two-way fixed effects instrumental variable estimate, with or without controls. The method is described in Miyaji (2024) <doi:10.48550/arXiv.2405.16467>.

r-tidynorm 0.4.0
Propagated dependencies: r-tidyselect@1.2.1 r-tidyr@1.3.1 r-stringr@1.6.0 r-rlang@1.1.6 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-purrr@1.2.0 r-options@0.3.1 r-glue@1.8.0 r-dplyr@1.1.4 r-cli@3.6.5 r-checkmate@2.3.3
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://jofrhwld.github.io/tidynorm/
Licenses: GPL 3+
Build system: r
Synopsis: Tools for Tidy Vowel Normalization
Description:

An implementation of tidy speaker vowel normalization. This includes generic functions for defining new normalization methods for points, formant tracks, and Discrete Cosine Transform coefficients, as well as convenience functions implementing established normalization methods. References for the implemented methods are: Johnson, Keith (2020) <doi:10.5334/labphon.196> Lobanov, Boris (1971) <doi:10.1121/1.1912396> Nearey, Terrance M. (1978) <https://sites.ualberta.ca/~tnearey/Nearey1978_compressed.pdf> Syrdal, Ann K., and Gopal, H. S. (1986) <doi:10.1121/1.393381> Watt, Dominic, and Fabricius, Anne (2002) <https://www.latl.leeds.ac.uk/article/evaluation-of-a-technique-for-improving-the-mapping-of-multiple-speakers-vowel-spaces-in-the-f1-f2-plane/>.

r-tlars 1.0.1
Propagated dependencies: r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/jasinmachkour/tlars
Licenses: GPL 3+
Build system: r
Synopsis: The T-LARS Algorithm: Early-Terminated Forward Variable Selection
Description:

Computes the solution path of the Terminating-LARS (T-LARS) algorithm. The T-LARS algorithm is a major building block of the T-Rex selector (see R package TRexSelector'). The package is based on the papers Machkour, Muma, and Palomar (2022) <arXiv:2110.06048>, Efron, Hastie, Johnstone, and Tibshirani (2004) <doi:10.1214/009053604000000067>, and Tibshirani (1996) <doi:10.1111/j.2517-6161.1996.tb02080.x>.

r-trnslate 0.0.3
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: <https://marioma.me?i=soft>
Licenses: GPL 2+
Build system: r
Synopsis: Translate R Code in Source Files
Description:

Evaluate inline or chunks of R code in template files and replace with their output modifying the resulting template.

r-tufterhandout 1.2.1
Propagated dependencies: r-rmarkdown@2.30 r-knitr@1.50
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: http://sachsmc.github.io/tufterhandout
Licenses: Expat
Build system: r
Synopsis: Tufte-style html document format for rmarkdown
Description:

Custom template and output formats for use with rmarkdown. Produce Edward Tufte-style handouts in html formats with full support for rmarkdown features.

r-topolow 2.0.1
Propagated dependencies: r-rlang@1.1.6 r-reshape2@1.4.5 r-lifecycle@1.0.4 r-lhs@1.2.0 r-ggplot2@4.0.1 r-future@1.68.0 r-filelock@1.0.3 r-dplyr@1.1.4 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/omid-arhami/topolow
Licenses: Modified BSD
Build system: r
Synopsis: Force-Directed Euclidean Embedding of Dissimilarity Data
Description:

This package provides a robust implementation of Topolow algorithm. It embeds objects into a low-dimensional Euclidean space from a matrix of pairwise dissimilarities, even when the data do not satisfy metric or Euclidean axioms. The package is particularly well-suited for sparse, incomplete, and censored (thresholded) datasets such as antigenic relationships. The core is a physics-inspired, gradient-free optimization framework that models objects as particles in a physical system, where observed dissimilarities define spring rest lengths and unobserved pairs exert repulsive forces. The package also provides functions specific to antigenic mapping to transform cross-reactivity and binding affinity measurements into accurate spatial representations in a phenotype space. Key features include: * Robust Embedding from Sparse Data: Effectively creates complete and consistent maps (in optimal dimensions) even with high proportions of missing data (e.g., >95%). * Physics-Inspired Optimization: Models objects (e.g., antigens, landmarks) as particles connected by springs (for measured dissimilarities) and subject to repulsive forces (for missing dissimilarities), and simulates the physical system using laws of mechanics, reducing the need for complex gradient computations. * Automatic Dimensionality Detection: Employs a likelihood-based approach to determine the optimal number of dimensions for the embedding/map, avoiding distortions common in methods with fixed low dimensions. * Noise and Bias Reduction: Naturally mitigates experimental noise and bias through its network-based, error-dampening mechanism. * Antigenic Velocity Calculation (for antigenic data): Introduces and quantifies "antigenic velocity," a vector that describes the rate and direction of antigenic drift for each pathogen isolate. This can help identify cluster transitions and potential lineage replacements. * Broad Applicability: Analyzes data from various objects that their dissimilarity may be of interest, ranging from complex biological measurements such as continuous and relational phenotypes, antibody-antigen interactions, and protein folding to abstract concepts, such as customer perception of different brands. Methods are described in the context of bioinformatics applications in Arhami and Rohani (2025a) <doi:10.1093/bioinformatics/btaf372>, and mathematical proofs and Euclidean embedding details are in Arhami and Rohani (2025b) <doi:10.48550/arXiv.2508.01733>.

r-topologyr 0.1.2
Propagated dependencies: r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/IsadoreNabi/topologyR
Licenses: Expat
Build system: r
Synopsis: Topological Connectivity Analysis for Numeric Data
Description:

Description: Implementation of topological data analysis methods based on graph-theoretic approaches for discovering topological structures in data. The core algorithm constructs topological spaces from graphs following Nada et al. (2018) <doi:10.1002/mma.4726> "New types of topological structures via graphs".

r-tip 0.1.0
Propagated dependencies: r-rlang@1.1.6 r-network@1.19.0 r-mniw@1.0.2 r-laplacesdemon@16.1.6 r-igraph@2.2.1 r-ggplot2@4.0.1 r-ggally@2.4.0 r-foreach@1.5.2 r-doparallel@1.0.17 r-changepoint@2.3
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://cran.r-project.org/package=tip
Licenses: Expat
Build system: r
Synopsis: Bayesian Clustering Using the Table Invitation Prior (TIP)
Description:

Cluster data without specifying the number of clusters using the Table Invitation Prior (TIP) introduced in the paper "Clustering Gene Expression Using the Table Invitation Prior" by Charles W. Harrison, Qing He, and Hsin-Hsiung Huang (2022) <doi:10.3390/genes13112036>. TIP is a Bayesian prior that uses pairwise distance and similarity information to cluster vectors, matrices, or tensors.

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