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r-multbxxc 1.0.3
Propagated dependencies: r-rmumps@5.2.1-30 r-rcpparmadillo@14.0.2-1 r-rcpp@1.0.13-1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/sgsokol/influx/
Licenses: GPL 2+
Synopsis: Auxiliary Routines for Influx Software
Description:

This package contains auxiliary routines for influx software. This packages is not intended to be used directly. Influx was published here: Sokol et al. (2012) <doi:10.1093/bioinformatics/btr716>.

r-multisom 1.3
Propagated dependencies: r-kohonen@3.0.12 r-class@7.3-22
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://sites.google.com/site/malikacharrad/research/multisom-package
Licenses: GPL 2
Synopsis: Clustering a Data Set using Multi-SOM Algorithm
Description:

This package implements two versions of the algorithm namely: stochastic and batch. The package determines also the best number of clusters and offers to the user the best clustering scheme from different results.

r-multivar 1.1.0
Propagated dependencies: r-vars@1.6-1 r-reshape2@1.4.4 r-rcpparmadillo@14.0.2-1 r-rcpp@1.0.13-1 r-matrix@1.7-1 r-mass@7.3-61 r-glmnet@4.1-8 r-ggplot2@3.5.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=multivar
Licenses: GPL 2+
Synopsis: Penalized Estimation of Multiple-Subject Vector Autoregressive (multi-VAR) Models
Description:

This package provides functions for simulating, estimating and forecasting stationary Vector Autoregressive (VAR) models for multiple subject data using the penalized multi-VAR framework in Fisher, Kim and Pipiras (2020) <arXiv:2007.05052>.

r-multifit 1.1.1
Propagated dependencies: r-rcpparmadillo@14.0.2-1 r-rcpp@1.0.13-1 r-data-table@1.16.2
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=MultiFit
Licenses: CC0
Synopsis: Multiscale Fisher's Independence Test for Multivariate Dependence
Description:

Test for independence of two random vectors, learn and report the dependency structure. For more information, see Gorsky, Shai and Li Ma, Multiscale Fisher's Independence Test for Multivariate Dependence, Biometrika, accepted, January 2022.

emacs-muse 3.20.2
Channel: guix
Location: gnu/packages/emacs-xyz.scm (gnu packages emacs-xyz)
Home page: https://www.gnu.org/software/emacs-muse
Licenses: GPL 3+
Synopsis: Authoring and publishing environment for Emacs
Description:

Emacs Muse (also known as Muse) is an authoring and publishing environment for Emacs. It simplifies the process of writing documents and publishing them to various output formats such as HTML, LaTeX, or PDF.

r-multirng 1.2.4
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=MultiRNG
Licenses: GPL 2 GPL 3
Synopsis: Multivariate Pseudo-Random Number Generation
Description:

Pseudo-random number generation for 11 multivariate distributions: Normal, t, Uniform, Bernoulli, Hypergeometric, Beta (Dirichlet), Multinomial, Dirichlet-Multinomial, Laplace, Wishart, and Inverted Wishart. The details of the method are explained in Demirtas (2004) <DOI:10.22237/jmasm/1099268340>.

r-multiway 1.0-7
Propagated dependencies: r-cmls@1.0-1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=multiway
Licenses: GPL 2+
Synopsis: Component Models for Multi-Way Data
Description:

Fits multi-way component models via alternating least squares algorithms with optional constraints. Fit models include N-way Canonical Polyadic Decomposition, Individual Differences Scaling, Multiway Covariates Regression, Parallel Factor Analysis (1 and 2), Simultaneous Component Analysis, and Tucker Factor Analysis.

r-multiocc 0.2.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=multiocc
Licenses: GPL 2
Synopsis: Fits Multivariate Spatio-Temporal Occupancy Model
Description:

Spatio-temporal multivariate occupancy models can handle multiple species in occupancy models. This method for fitting such models is described in Hepler and Erhardt (2021) "A spatiotemporal model for multivariate occupancy data" <https://onlinelibrary.wiley.com/doi/abs/10.1002/env.2657>.

r-multcomp 1.4-26
Propagated dependencies: r-codetools@0.2-20 r-mvtnorm@1.3-2 r-sandwich@3.1-1 r-survival@3.7-0 r-th-data@1.1-2
Channel: guix
Location: gnu/packages/cran.scm (gnu packages cran)
Home page: https://cran.r-project.org/web/packages/multcomp/
Licenses: GPL 2
Synopsis: Simultaneous inference in general parametric models
Description:

Simultaneous tests and confidence intervals for general linear hypotheses in parametric models, including linear, generalized linear, linear mixed effects, and survival models. The package includes demos reproducing analyzes presented in the book "Multiple Comparisons Using R" (Bretz, Hothorn, Westfall, 2010, CRC Press).

r-multinma 0.8.0
Propagated dependencies: r-truncdist@1.0-2 r-tidyr@1.3.1 r-tibble@3.2.1 r-survival@3.7-0 r-stringr@1.5.1 r-stanheaders@2.32.10 r-rstantools@2.4.0 r-rstan@2.32.6 r-rlang@1.1.4 r-rdpack@2.6.1 r-rcppparallel@5.1.9 r-rcppeigen@0.3.4.0.2 r-rcpp@1.0.13-1 r-randtoolbox@2.0.5 r-purrr@1.0.2 r-matrix@1.7-1 r-igraph@2.1.1 r-glue@1.8.0 r-ggraph@2.2.1 r-ggplot2@3.5.1 r-ggdist@3.3.2 r-forcats@1.0.0 r-dplyr@1.1.4 r-copula@1.1-6 r-bh@1.84.0-0 r-bayesplot@1.11.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://dmphillippo.github.io/multinma/
Licenses: GPL 3
Synopsis: Bayesian Network Meta-Analysis of Individual and Aggregate Data
Description:

Network meta-analysis and network meta-regression models for aggregate data, individual patient data, and mixtures of both individual and aggregate data using multilevel network meta-regression as described by Phillippo et al. (2020) <doi:10.1111/rssa.12579>. Models are estimated in a Bayesian framework using Stan'.

r-multibac 1.16.0
Propagated dependencies: r-ggplot2@3.5.1 r-matrix@1.7-1 r-multiassayexperiment@1.32.0 r-pcamethods@1.98.0 r-plotrix@3.8-4 r-ropls@1.38.0
Channel: guix
Location: gnu/packages/bioconductor.scm (gnu packages bioconductor)
Home page: https://bioconductor.org/packages/MultiBaC
Licenses: GPL 3
Synopsis: Multiomic batch effect correction
Description:

MultiBaC is a strategy to correct batch effects from multiomic datasets distributed across different labs or data acquisition events. MultiBaC is able to remove batch effects across different omics generated within separate batches provided that at least one common omic data type is included in all the batches considered.

r-multidoe 0.9.4
Propagated dependencies: r-pracma@2.4.4 r-plotly@4.10.4 r-magrittr@2.0.3 r-ggplot2@3.5.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/andreamelloncelli/multiDoE
Licenses: FSDG-compatible
Synopsis: Multi-Criteria Design of Experiments for Optimal Design
Description:

Multi-criteria design of experiments algorithm that simultaneously optimizes up to six different criteria ('I', Id', D', Ds', A and As'). The algorithm finds the optimal Pareto front and, if requested, selects a possible symmetrical design on it. The symmetrical design is selected based on two techniques: minimum distance with the Utopia point or the TOPSIS approach.

orca-music 0-1.e55b8fd
Dependencies: ncurses@6.2.20210619 portmidi@217 alsa-plugins@1.2.2 alsa-plugins@1.2.2
Channel: guix
Location: gnu/packages/music.scm (gnu packages music)
Home page: https://100r.co/site/orca.html
Licenses: Expat
Synopsis: Musical live-coding environment
Description:

This is the C implementation of the ORCĪ› language and terminal livecoding environment. It's designed to be power efficient. It can handle large files, even if your terminal is small.

Orca is not a synthesizer, but a flexible livecoding environment capable of sending MIDI, OSC, and UDP to your audio/visual interfaces like Ableton, Renoise, VCV Rack, or SuperCollider.

r-multimir 1.28.0
Propagated dependencies: r-xml@3.99-0.17 r-tibble@3.2.1 r-rcurl@1.98-1.16 r-purrr@1.0.2 r-dplyr@1.1.4 r-biocgenerics@0.52.0 r-annotationdbi@1.68.0
Channel: guix-bioc
Location: guix-bioc/packages/m.scm (guix-bioc packages m)
Home page: https://github.com/KechrisLab/multiMiR
Licenses: Expat
Synopsis: Integration of multiple microRNA-target databases with their disease and drug associations
Description:

This package provides a collection of microRNAs/targets from external resources, including validated microRNA-target databases (miRecords, miRTarBase and TarBase), predicted microRNA-target databases (DIANA-microT, ElMMo, MicroCosm, miRanda, miRDB, PicTar, PITA and TargetScan) and microRNA-disease/drug databases (miR2Disease, Pharmaco-miR VerSe and PhenomiR).

r-multicmp 1.1
Propagated dependencies: r-numderiv@2016.8-1.1
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: http://dx.doi.org/10.1016/j.jmva.2016.04.007
Licenses: GPL 3
Synopsis: Flexible Modeling of Multivariate Count Data via the Multivariate Conway-Maxwell-Poisson Distribution
Description:

This package provides a toolkit containing statistical analysis models motivated by multivariate forms of the Conway-Maxwell-Poisson (COM-Poisson) distribution for flexible modeling of multivariate count data, especially in the presence of data dispersion. Currently the package only supports bivariate data, via the bivariate COM-Poisson distribution described in Sellers et al. (2016) <doi:10.1016/j.jmva.2016.04.007>. Future development will extend the package to higher-dimensional data.

r-multiroc 1.1.1
Propagated dependencies: r-zoo@1.8-12 r-magrittr@2.0.3 r-boot@1.3-31
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=multiROC
Licenses: GPL 3
Synopsis: Calculating and Visualizing ROC and PR Curves Across Multi-Class Classifications
Description:

This package provides tools to solve real-world problems with multiple classes classifications by computing the areas under ROC and PR curve via micro-averaging and macro-averaging. The vignettes of this package can be found via <https://github.com/WandeRum/multiROC>. The methodology is described in V. Van Asch (2013) <https://www.clips.uantwerpen.be/~vincent/pdf/microaverage.pdf> and Pedregosa et al. (2011) <http://scikit-learn.org/stable/auto_examples/model_selection/plot_roc.html>.

r-musicnmr 1.0
Propagated dependencies: r-seewave@2.2.3
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=musicNMR
Licenses: GPL 2+
Synopsis: Conversion of Nuclear Magnetic Resonance Spectra in Audio Files
Description:

This package provides a collection of functions for converting and visualization the free induction decay of mono dimensional nuclear magnetic resonance (NMR) spectra into an audio file. It facilitates the conversion of Bruker datasets in files WAV. The sound of NMR signals could provide an alternative to the current representation of the individual metabolic fingerprint and supply equally significant information. The package includes also NMR spectra of the urine samples provided by four healthy donors. Based on Cacciatore S, Saccenti E, Piccioli M. Hypothesis: the sound of the individual metabolic phenotype? Acoustic detection of NMR experiments. OMICS. 2015;19(3):147-56. <doi:10.1089/omi.2014.0131>.

r-musicxml 1.0.1
Propagated dependencies: r-xml2@1.3.6
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=musicXML
Licenses: GPL 3
Synopsis: Data Sonification using 'musicXML'
Description:

This package provides a set of tools to facilitate data sonification and handle the musicXML format <https://usermanuals.musicxml.com/MusicXML/Content/XS-MusicXML.htm>. Several classes are defined for basic musical objects such as note pitch, note duration, note, measure and score. Moreover, sonification utilities functions are provided, e.g. to map data into musical attributes such as pitch, loudness or duration. A typical sonification workflow hence looks like: get data; map them to musical attributes; create and write the musicXML score, which can then be further processed using specialized music software (e.g. MuseScore', GuitarPro', etc.). Examples can be found in the blog <https://globxblog.github.io/>, the presentation by Renard and Le Bescond (2022, <https://hal.science/hal-03710340v1>) or the poster by Renard et al. (2023, <https://hal.inrae.fr/hal-04388845v1>).

r-multimix 1.0-10
Propagated dependencies: r-mvtnorm@1.3-2
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/jmcurran/multimix
Licenses: GPL 2+
Synopsis: Fit Mixture Models Using the Expectation Maximisation (EM) Algorithm
Description:

This package provides a set of functions which use the Expectation Maximisation (EM) algorithm (Dempster, A. P., Laird, N. M., and Rubin, D. B. (1977) <doi:10.1111/j.2517-6161.1977.tb01600.x> Maximum likelihood from incomplete data via the EM algorithm, Journal of the Royal Statistical Society, 39(1), 1--22) to take a finite mixture model approach to clustering. The package is designed to cluster multivariate data that have categorical and continuous variables and that possibly contain missing values. The method is described in Hunt, L. and Jorgensen, M. (1999) <doi:10.1111/1467-842X.00071> Australian & New Zealand Journal of Statistics 41(2), 153--171 and Hunt, L. and Jorgensen, M. (2003) <doi:10.1016/S0167-9473(02)00190-1> Mixture model clustering for mixed data with missing information, Computational Statistics & Data Analysis, 41(3-4), 429--440.

r-multpois 0.3.3
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://github.com/wobbrock/multpois/
Licenses: GPL 2+
Synopsis: Analyze Nominal Response Data with the Multinomial-Poisson Trick
Description:

Dichotomous responses having two categories can be analyzed with stats::glm() or lme4::glmer() using the family=binomial option. Unfortunately, polytomous responses with three or more unordered categories cannot be analyzed similarly because there is no analogous family=multinomial option. For between-subjects data, nnet::multinom() can address this need, but it cannot handle random factors and therefore cannot handle repeated measures. To address this gap, we transform nominal response data into counts for each categorical alternative. These counts are then analyzed using (mixed) Poisson regression as per Baker (1994) <doi:10.2307/2348134>. Omnibus analyses of variance can be run along with post hoc pairwise comparisons. For users wishing to analyze nominal responses from surveys or experiments, the functions in this package essentially act as though stats::glm() or lme4::glmer() provide a family=multinomial option.

r-multtest 2.62.0
Propagated dependencies: r-biobase@2.66.0 r-biocgenerics@0.52.0 r-mass@7.3-61 r-survival@3.7-0
Channel: guix
Location: gnu/packages/bioconductor.scm (gnu packages bioconductor)
Home page: https://bioconductor.org/packages/multtest
Licenses: LGPL 3
Synopsis: Resampling-based multiple hypothesis testing
Description:

This package can do non-parametric bootstrap and permutation resampling-based multiple testing procedures (including empirical Bayes methods) for controlling the family-wise error rate (FWER), generalized family-wise error rate (gFWER), tail probability of the proportion of false positives (TPPFP), and false discovery rate (FDR). Several choices of bootstrap-based null distribution are implemented (centered, centered and scaled, quantile-transformed). Single-step and step-wise methods are available. Tests based on a variety of T- and F-statistics (including T-statistics based on regression parameters from linear and survival models as well as those based on correlation parameters) are included. When probing hypotheses with T-statistics, users may also select a potentially faster null distribution which is multivariate normal with mean zero and variance covariance matrix derived from the vector influence function. Results are reported in terms of adjusted P-values, confidence regions and test statistic cutoffs. The procedures are directly applicable to identifying differentially expressed genes in DNA microarray experiments.

r-musicatk 2.0.0
Propagated dependencies: r-variantannotation@1.52.0 r-uwot@0.2.2 r-txdb-hsapiens-ucsc-hg38-knowngene@3.20.0 r-txdb-hsapiens-ucsc-hg19-knowngene@3.2.2 r-topicmodels@0.2-17 r-tidyverse@2.0.0 r-tidyr@1.3.1 r-tibble@3.2.1 r-summarizedexperiment@1.36.0 r-stringr@1.5.1 r-stringi@1.8.4 r-shiny@1.8.1 r-scales@1.3.0 r-s4vectors@0.44.0 r-rlang@1.1.4 r-plotly@4.10.4 r-philentropy@0.9.0 r-nmf@0.28 r-mcmcprecision@0.4.0 r-matrixtests@0.2.3 r-matrix@1.7-1 r-mass@7.3-61 r-magrittr@2.0.3 r-maftools@2.22.0 r-iranges@2.40.0 r-gtools@3.9.5 r-gridextra@2.3 r-ggrepel@0.9.6 r-ggpubr@0.6.0 r-ggplot2@3.5.1 r-genomicranges@1.58.0 r-genomicfeatures@1.58.0 r-genomeinfodb@1.42.0 r-factoextra@1.0.7 r-dplyr@1.1.4 r-decomptumor2sig@2.22.0 r-data-table@1.16.2 r-conclust@1.1 r-complexheatmap@2.22.0 r-cluster@2.1.6 r-bsgenome-mmusculus-ucsc-mm9@1.4.0 r-bsgenome-mmusculus-ucsc-mm10@1.4.3 r-bsgenome-hsapiens-ucsc-hg38@1.4.5 r-bsgenome-hsapiens-ucsc-hg19@1.4.3 r-bsgenome@1.74.0 r-biostrings@2.74.0
Channel: guix-bioc
Location: guix-bioc/packages/m.scm (guix-bioc packages m)
Home page: https://bioconductor.org/packages/musicatk
Licenses: LGPL 3
Synopsis: Mutational Signature Comprehensive Analysis Toolkit
Description:

Mutational signatures are carcinogenic exposures or aberrant cellular processes that can cause alterations to the genome. We created musicatk (MUtational SIgnature Comprehensive Analysis ToolKit) to address shortcomings in versatility and ease of use in other pre-existing computational tools. Although many different types of mutational data have been generated, current software packages do not have a flexible framework to allow users to mix and match different types of mutations in the mutational signature inference process. Musicatk enables users to count and combine multiple mutation types, including SBS, DBS, and indels. Musicatk calculates replication strand, transcription strand and combinations of these features along with discovery from unique and proprietary genomic feature associated with any mutation type. Musicatk also implements several methods for discovery of new signatures as well as methods to infer exposure given an existing set of signatures. Musicatk provides functions for visualization and downstream exploratory analysis including the ability to compare signatures between cohorts and find matching signatures in COSMIC V2 or COSMIC V3.

r-multiscan 1.66.0
Propagated dependencies: r-biobase@2.66.0
Channel: guix-bioc
Location: guix-bioc/packages/m.scm (guix-bioc packages m)
Home page: https://bioconductor.org/packages/multiscan
Licenses: GPL 2+
Synopsis: R package for combining multiple scans
Description:

Estimates gene expressions from several laser scans of the same microarray.

Total results: 472