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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-idsl-mxp 2.0
Propagated dependencies: r-xml2@1.5.0 r-base64enc@0.1-3
Channel: guix-cran
Location: guix-cran/packages/i.scm (guix-cran packages i)
Home page: https://cran.r-project.org/package=IDSL.MXP
Licenses: Expat
Build system: r
Synopsis: Parser for mzML, mzXML, and netCDF Files (Mass Spectrometry Data)
Description:

This package provides a tiny parser to extract mass spectra data and metadata table of mass spectrometry acquisition properties from mzML, mzXML and netCDF files introduced in <doi:10.1021/acs.jproteome.2c00120>.

r-ipcwk 1.0
Propagated dependencies: r-survival@3.8-3 r-mass@7.3-65
Channel: guix-cran
Location: guix-cran/packages/i.scm (guix-cran packages i)
Home page: https://cran.r-project.org/package=IPCWK
Licenses: GPL 2+
Build system: r
Synopsis: Kendall's Tau Partial Corr. for Survival Trait and Biomarkers
Description:

We propose the inverse probability-of-censoring weighted (IPCW) Kendall's tau to measure the association of the survival trait with biomarkers and Kendall's partial correlation to reflect the relationship of the survival trait with interaction variable conditional on main effects, as described in Wang and Chen (2020) <doi:10.1093/bioinformatics/btaa017>.

r-ictest 0.3-6
Propagated dependencies: r-zoo@1.8-14 r-xts@0.14.1 r-survey@4.4-8 r-rcpproll@0.3.1 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-progress@1.2.3 r-png@0.1-8 r-mvtnorm@1.3-3 r-jade@2.0-4 r-icsnp@1.1-2 r-ics@1.4-2 r-ggplot2@4.0.1 r-ggally@2.4.0
Channel: guix-cran
Location: guix-cran/packages/i.scm (guix-cran packages i)
Home page: https://cran.r-project.org/package=ICtest
Licenses: GPL 2+
Build system: r
Synopsis: Estimating and Testing the Number of Interesting Components in Linear Dimension Reduction
Description:

For different linear dimension reduction methods like principal components analysis (PCA), independent components analysis (ICA) and supervised linear dimension reduction tests and estimates for the number of interesting components (ICs) are provided.

r-ipbase 0.1.1
Propagated dependencies: r-jsonlite@2.0.0 r-httr@1.4.7
Channel: guix-cran
Location: guix-cran/packages/i.scm (guix-cran packages i)
Home page: https://ipbase.com
Licenses: Expat
Build system: r
Synopsis: Client for the 'ipbase.com' IP Geolocation API
Description:

An R client for the ipbase.com IP Geolocation API. The API requires registration of an API key. Basic features are free, some require a paid subscription. You can find the full API documentation at <https://ipbase.com/docs> .

r-imfor 0.1.0
Propagated dependencies: r-tidyverse@2.0.0 r-nlme@3.1-168 r-minpack-lm@1.2-4 r-metrics@0.1.4 r-ggpubr@0.6.2 r-ggplot2@4.0.1 r-caret@7.0-1
Channel: guix-cran
Location: guix-cran/packages/i.scm (guix-cran packages i)
Home page: https://cran.r-project.org/package=ImFoR
Licenses: GPL 3
Build system: r
Synopsis: Non-Linear Height Diameter Models for Forestry
Description:

Tree height is an important dendrometric variable and forms the basis of vertical structure of a forest stand. This package will help to fit and validate various non-linear height diameter models for assessing the underlying relationship that exists between tree height and diameter at breast height in case of conifer trees. This package has been implemented on Naslund, Curtis, Michailoff, Meyer, Power, Michaelis-Menten and Wykoff non linear models using algorithm of Huang et al. (1992) <doi:10.1139/x92-172> and Zeide et al. (1993) <doi:10.1093/forestscience/39.3.594>.

r-icbiomark 0.1.4
Propagated dependencies: r-purrr@1.2.0 r-prroc@1.4 r-matrixstats@1.5.0 r-matrix@1.7-4 r-latex2exp@0.9.6 r-glmnet@4.1-10 r-ggplot2@4.0.1 r-gglasso@1.6 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/i.scm (guix-cran packages i)
Home page: https://cran.r-project.org/package=ICBioMark
Licenses: Expat
Build system: r
Synopsis: Data-Driven Design of Targeted Gene Panels for Estimating Immunotherapy Biomarkers
Description:

Implementation of the methodology proposed in Data-driven design of targeted gene panels for estimating immunotherapy biomarkers', Bradley and Cannings (2021) <arXiv:2102.04296>. This package allows the user to fit generative models of mutation from an annotated mutation dataset, and then further to produce tunable linear estimators of exome-wide biomarkers. It also contains functions to simulate mutation annotated format (MAF) data, as well as to analyse the output and performance of models.

r-icsoutlier 0.4-1
Propagated dependencies: r-mvtnorm@1.3-3 r-moments@0.14.1 r-ics@1.4-2
Channel: guix-cran
Location: guix-cran/packages/i.scm (guix-cran packages i)
Home page: https://cran.r-project.org/package=ICSOutlier
Licenses: GPL 2+
Build system: r
Synopsis: Outlier Detection Using Invariant Coordinate Selection
Description:

Multivariate outlier detection is performed using invariant coordinates where the package offers different methods to choose the appropriate components. ICS is a general multivariate technique with many applications in multivariate analysis. ICSOutlier offers a selection of functions for automated detection of outliers in the data based on a fitted ICS object or by specifying the dataset and the scatters of interest. The current implementation targets data sets with only a small percentage of outliers.

r-ibdfindr 0.3.1
Propagated dependencies: r-ribd@1.7.1 r-pedtools@2.10.0 r-ibdsim2@2.3.2 r-ggplot2@4.0.1 r-forrel@1.8.1
Channel: guix-cran
Location: guix-cran/packages/i.scm (guix-cran packages i)
Home page: https://github.com/magnusdv/ibdfindr
Licenses: GPL 3+
Build system: r
Synopsis: HMM Toolkit for Inferring IBD Segments from SNP Genotypes
Description:

This package implements continuous-time hidden Markov models (HMMs) to infer identity-by-descent (IBD) segments shared by two individuals from their single-nucleotide polymorphism (SNP) genotypes. Provides posterior probabilities at each marker (forward-backward algorithm), prediction of IBD segments (Viterbi algorithm), and functions for visualising results. Supports both autosomal data and X-chromosomal data.

r-irtgui 0.2
Propagated dependencies: r-writexl@1.5.4 r-wrightmap@1.4 r-shinydashboard@0.7.3 r-shinycssloaders@1.1.0 r-shiny@1.11.1 r-readxl@1.4.5 r-psych@2.5.6 r-mirt@1.45.1 r-magrittr@2.0.4 r-irtoys@0.2.2
Channel: guix-cran
Location: guix-cran/packages/i.scm (guix-cran packages i)
Home page: https://cran.r-project.org/package=irtGUI
Licenses: GPL 3+
Build system: r
Synopsis: Item Response Theory Analysis with a Graphic User Interface
Description:

Performing Item Response Theory analysis such as parameter estimation, ability estimation, data generation, item and model fit analyse, local independence assumption, dimensionality assumption, wright map, characteristic and information curves under various models with a user-friendly Graphic User Interface.

r-ifatools 0.23
Propagated dependencies: r-shiny@1.11.1 r-rpf@1.0.15 r-reshape2@1.4.5 r-openmx@2.22.10 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/i.scm (guix-cran packages i)
Home page: https://github.com/jpritikin/ifaTools
Licenses: AGPL 3+
Build system: r
Synopsis: Toolkit for Item Factor Analysis with 'OpenMx'
Description:

Tools, tutorials, and demos of Item Factor Analysis using OpenMx'. This software is described in Pritikin & Falk (2020) <doi:10.1177/0146621620929431>.

r-infotrad 1.2
Propagated dependencies: r-nloptr@2.2.1
Channel: guix-cran
Location: guix-cran/packages/i.scm (guix-cran packages i)
Home page: https://cran.r-project.org/package=InfoTrad
Licenses: GPL 3
Build system: r
Synopsis: Calculates the Probability of Informed Trading (PIN)
Description:

Estimates the probability of informed trading (PIN) initially introduced by Easley et. al. (1996) <doi:10.1111/j.1540-6261.1996.tb04074.x> . Contribution of the package is that it uses likelihood factorizations of Easley et. al. (2010) <doi:10.1017/S0022109010000074> (EHO factorization) and Lin and Ke (2011) <doi:10.1016/j.finmar.2011.03.001> (LK factorization). Moreover, the package uses different estimation algorithms. Specifically, the grid-search algorithm proposed by Yan and Zhang (2012) <doi:10.1016/j.jbankfin.2011.08.003> , hierarchical agglomerative clustering approach proposed by Gan et. al. (2015) <doi:10.1080/14697688.2015.1023336> and later extended by Ersan and Alici (2016) <doi:10.1016/j.intfin.2016.04.001> .

r-infiniumpurify 1.3.1
Propagated dependencies: r-matrixstats@1.5.0
Channel: guix-cran
Location: guix-cran/packages/i.scm (guix-cran packages i)
Home page: https://cran.r-project.org/package=InfiniumPurify
Licenses: GPL 2
Build system: r
Synopsis: Estimate and Account for Tumor Purity in Cancer Methylation Data Analysis
Description:

The proportion of cancer cells in solid tumor sample, known as the tumor purity, has adverse impact on a variety of data analyses if not properly accounted for. We develop InfiniumPurify', which is a comprehensive R package for estimating and accounting for tumor purity based on DNA methylation Infinium 450k array data. InfiniumPurify provides functionalities for tumor purity estimation. In addition, it can perform differential methylation detection and tumor sample clustering with the consideration of tumor purities.

r-iar 1.3.2
Propagated dependencies: r-zoo@1.8-14 r-s7@0.2.1 r-rdpack@2.6.4 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/i.scm (guix-cran packages i)
Home page: https://github.com/felipeelorrieta
Licenses: GPL 2
Build system: r
Synopsis: Irregularly Observed Autoregressive Models
Description:

Data sets, functions and scripts with examples to implement autoregressive models for irregularly observed time series. The models available in this package are the irregular autoregressive model (Eyheramendy et al.(2018) <doi:10.1093/mnras/sty2487>), the complex irregular autoregressive model (Elorrieta et al.(2019) <doi:10.1051/0004-6361/201935560>) and the bivariate irregular autoregressive model (Elorrieta et al.(2021) <doi:10.1093/mnras/stab1216>).

r-iss 1.0.0
Propagated dependencies: r-rdpack@2.6.4
Channel: guix-cran
Location: guix-cran/packages/i.scm (guix-cran packages i)
Home page: https://cran.r-project.org/package=ISS
Licenses: GPL 3+
Build system: r
Synopsis: Isotonic Subgroup Selection
Description:

Methodology for subgroup selection in the context of isotonic regression including methods for sub-Gaussian errors, classification, homoscedastic Gaussian errors and quantile regression. See the documentation of ISS(). Details can be found in the paper by Müller, Reeve, Cannings and Samworth (2023) <arXiv:2305.04852v2>.

r-investr 1.4.2
Propagated dependencies: r-nlme@3.1-168
Channel: guix-cran
Location: guix-cran/packages/i.scm (guix-cran packages i)
Home page: https://github.com/bgreenwell/investr
Licenses: GPL 2+
Build system: r
Synopsis: Inverse Estimation/Calibration Functions
Description:

This package provides functions to facilitate inverse estimation (e.g., calibration) in linear, generalized linear, nonlinear, and (linear) mixed-effects models. A generic function is also provided for plotting fitted regression models with or without confidence/prediction bands that may be of use to the general user. For a general overview of these methods, see Greenwell and Schubert Kabban (2014) <doi:10.32614/RJ-2014-009>.

r-icellr 1.7.0
Propagated dependencies: r-uwot@0.2.4 r-shiny@1.11.1 r-scatterplot3d@0.3-44 r-rtsne@0.17 r-reshape@0.8.10 r-rcpp@1.1.0 r-rcolorbrewer@1.1-3 r-rann@2.6.2 r-progress@1.2.3 r-png@0.1-8 r-plyr@1.8.9 r-plotly@4.11.0 r-pheatmap@1.0.13 r-nbclust@3.0.1 r-matrix@1.7-4 r-knitr@1.50 r-jsonlite@2.0.0 r-igraph@2.2.1 r-htmlwidgets@1.6.4 r-hmisc@5.2-4 r-hdf5r@1.3.12 r-gridextra@2.3 r-ggrepel@0.9.6 r-ggpubr@0.6.2 r-ggplot2@4.0.1 r-ggdendro@0.2.0 r-data-table@1.17.8 r-ape@5.8-1
Channel: guix-cran
Location: guix-cran/packages/i.scm (guix-cran packages i)
Home page: https://github.com/rezakj/iCellR
Licenses: GPL 2
Build system: r
Synopsis: Analyzing High-Throughput Single Cell Sequencing Data
Description:

This package provides a toolkit that allows scientists to work with data from single cell sequencing technologies such as scRNA-seq, scVDJ-seq, scATAC-seq, CITE-Seq and Spatial Transcriptomics (ST). Single (i) Cell R package ('iCellR') provides unprecedented flexibility at every step of the analysis pipeline, including normalization, clustering, dimensionality reduction, imputation, visualization, and so on. Users can design both unsupervised and supervised models to best suit their research. In addition, the toolkit provides 2D and 3D interactive visualizations, differential expression analysis, filters based on cells, genes and clusters, data merging, normalizing for dropouts, data imputation methods, correcting for batch differences, pathway analysis, tools to find marker genes for clusters and conditions, predict cell types and pseudotime analysis. See Khodadadi-Jamayran, et al (2020) <doi:10.1101/2020.05.05.078550> and Khodadadi-Jamayran, et al (2020) <doi:10.1101/2020.03.31.019109> for more details.

r-ivtools 2.3.0
Propagated dependencies: r-survival@3.8-3 r-rcpp@1.1.0 r-numderiv@2016.8-1.1 r-nleqslv@3.3.5 r-data-table@1.17.8 r-ahaz@1.15.1
Channel: guix-cran
Location: guix-cran/packages/i.scm (guix-cran packages i)
Home page: https://cran.r-project.org/package=ivtools
Licenses: LGPL 3+
Build system: r
Synopsis: Instrumental Variables
Description:

This package contains tools for instrumental variables estimation. Currently, non-parametric bounds, two-stage estimation and G-estimation are implemented. Balke, A. and Pearl, J. (1997) <doi:10.2307/2965583>, Vansteelandt S., Bowden J., Babanezhad M., Goetghebeur E. (2011) <doi:10.1214/11-STS360>.

r-interleave 0.1.2
Propagated dependencies: r-rcpp@1.1.0 r-geometries@0.2.5
Channel: guix-cran
Location: guix-cran/packages/i.scm (guix-cran packages i)
Home page: https://cran.r-project.org/package=interleave
Licenses: Expat
Build system: r
Synopsis: Converts Tabular Data to Interleaved Vectors
Description:

Converts matrices and lists of matrices into a single vector by interleaving their values. That is, each element of the result vector is filled from the input matrices one row at a time. This is the same as transposing a matrix, then removing the dimension attribute, but is designed to operate on matrices in nested list structures.

r-immunarch 0.10.3
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-stringdist@0.9.15 r-scales@1.4.0 r-rlist@0.4.6.2 r-rlang@1.1.6 r-reshape2@1.4.5 r-readr@2.1.6 r-rcpp@1.1.0 r-purrr@1.2.0 r-plyr@1.8.9 r-pheatmap@1.0.13 r-patchwork@1.3.2 r-magrittr@2.0.4 r-lifecycle@1.0.4 r-immundata@0.0.5 r-glue@1.8.0 r-ggthemes@5.1.0 r-ggsci@4.1.0 r-ggplot2@4.0.1 r-duckplyr@1.1.3 r-dtplyr@1.3.2 r-dplyr@1.1.4 r-doparallel@1.0.17 r-dbplyr@2.5.1 r-data-table@1.17.8 r-cli@3.6.5 r-circlize@0.4.16 r-checkmate@2.3.3 r-ape@5.8-1 r-airr@1.5.0
Channel: guix-cran
Location: guix-cran/packages/i.scm (guix-cran packages i)
Home page: https://immunomind.github.io/docs/
Licenses: ASL 2.0
Build system: r
Synopsis: Multi-Modal Immune Repertoire Analytics for Immunotherapy and Vaccine Design in R
Description:

This package provides a comprehensive analytics framework for building reproducible pipelines on T-cell and B-cell immune receptor repertoire data. Delivers multi-modal immune profiling (bulk, single-cell, CITE-seq/AbSeq, spatial, immunogenicity data), feature engineering (ML-ready feature tables and matrices), and biomarker discovery workflows (cohort comparisons, longitudinal tracking, repertoire similarity, enrichment). Provides a user-friendly interface to widely used AIRR methods â clonality/diversity, V(D)J usage, similarity, annotation, tracking, and many more. Think Scanpy or Seurat, but for AIRR data, a.k.a. Adaptive Immune Receptor Repertoire, VDJ-seq, RepSeq, or VDJ sequencing data. A successor to our previously published "tcR" R package (Nazarov 2015).

r-ilrcm 0.2.0
Propagated dependencies: r-scales@1.4.0 r-rlang@1.1.6 r-ggplot2@4.0.1 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/i.scm (guix-cran packages i)
Home page: https://cran.r-project.org/package=ILRCM
Licenses: GPL 3
Build system: r
Synopsis: Convert Irregular Longitudinal Data to Regular Intervals and Perform Clustering
Description:

Convert irregularly spaced longitudinal data into regular intervals for further analysis, and perform clustering using advanced machine learning techniques. The package is designed for handling complex longitudinal datasets, optimizing them for research in healthcare, demography, and other fields requiring temporal data modeling.

r-irishdirectorates 1.5
Propagated dependencies: r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0
Channel: guix-cran
Location: guix-cran/packages/i.scm (guix-cran packages i)
Home page: https://cran.r-project.org/package=IrishDirectorates
Licenses: GPL 3
Build system: r
Synopsis: Dynamic Bipartite Latent Space Model to Analyse Irish Companies' Boards from 2003 to 2013
Description:

This package provides the dataset and an implementation of the method illustrated in Friel, N., Rastelli, R., Wyse, J. and Raftery, A.E. (2016) <DOI:10.1073/pnas.1606295113>.

r-iced 0.0.1
Propagated dependencies: r-stringr@1.6.0 r-mass@7.3-65 r-lavaan@0.6-20 r-knitr@1.50 r-boot@1.3-32
Channel: guix-cran
Location: guix-cran/packages/i.scm (guix-cran packages i)
Home page: https://github.com/sdparsons/ICED
Licenses: Expat
Build system: r
Synopsis: IntraClass Effect Decomposition
Description:

Estimate test-retest reliability for complex sampling strategies and extract variances using IntraClass Effect Decomposition. Developed by Brandmaier et al. (2018) "Assessing reliability in neuroimaging research through intra-class effect decomposition (ICED)" <doi:10.7554/eLife.35718> Also includes functions to simulate data based on sampling strategy. Unofficial version release name: "Good work squirrels".

r-ihpdr 1.2.1
Propagated dependencies: r-xml2@1.5.0 r-tidyr@1.3.1 r-rvest@1.0.5 r-rlang@1.1.6 r-readxl@1.4.5 r-purrr@1.2.0 r-magrittr@2.0.4 r-lubridate@1.9.4 r-httr@1.4.7 r-dplyr@1.1.4 r-curl@7.0.0
Channel: guix-cran
Location: guix-cran/packages/i.scm (guix-cran packages i)
Home page: https://github.com/kvasilopoulos/ihpdr
Licenses: GPL 3
Build system: r
Synopsis: Download Data from the International House Price Database
Description:

Web scraping the <https://www.dallasfed.org> for up-to-date data on international house prices and exuberance indicators. Download data in tidy format.

r-intsdm 2.1.2
Propagated dependencies: r-units@1.0-0 r-tidyterra@1.0.0 r-terra@1.8-86 r-sf@1.0-23 r-rgbif@3.8.4 r-r6@2.6.1 r-pointedsdms@2.1.4 r-inlabru@2.13.0 r-giscor@1.0.1 r-ggplot2@4.0.1 r-geodata@0.6-6 r-fmesher@0.5.0 r-blockcv@3.2-0
Channel: guix-cran
Location: guix-cran/packages/i.scm (guix-cran packages i)
Home page: https://cran.r-project.org/package=intSDM
Licenses: GPL 3+
Build system: r
Synopsis: Reproducible Integrated Species Distribution Models Across Norway using 'INLA'
Description:

Integration of disparate datasets is needed in order to make efficient use of all available data and thereby address the issues currently threatening biodiversity. Data integration is a powerful modeling framework which allows us to combine these datasets together into a single model, yet retain the strengths of each individual dataset. We therefore introduce the package, intSDM': an R package designed to help ecologists develop a reproducible workflow of integrated species distribution models, using data both provided from the user as well as data obtained freely online. An introduction to data integration methods is discussed in Issac, Jarzyna, Keil, Dambly, Boersch-Supan, Browning, Freeman, Golding, Guillera-Arroita, Henrys, Jarvis, Lahoz-Monfort, Pagel, Pescott, Schmucki, Simmonds and Oâ Hara (2020) <doi:10.1016/j.tree.2019.08.006>.

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