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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.

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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-rta10probeset-db 8.8.0
Propagated dependencies: r-org-rn-eg-db@3.22.0 r-annotationdbi@1.72.0
Channel: guix-bioc
Location: guix-bioc/packages/r.scm (guix-bioc packages r)
Home page: https://bioconductor.org/packages/rta10probeset.db
Licenses: Artistic License 2.0
Build system: r
Synopsis: Affymetrix rta10 annotation data (chip rta10probeset)
Description:

Affymetrix rta10 annotation data (chip rta10probeset) assembled using data from public repositories.

r-rgug4130a-db 3.2.3
Propagated dependencies: r-org-rn-eg-db@3.22.0 r-annotationdbi@1.72.0
Channel: guix-bioc
Location: guix-bioc/packages/r.scm (guix-bioc packages r)
Home page: https://bioconductor.org/packages/rgug4130a.db
Licenses: Artistic License 2.0
Build system: r
Synopsis: Agilent Rat annotation data (chip rgug4130a)
Description:

Agilent Rat annotation data (chip rgug4130a) assembled using data from public repositories.

r-rscudo 1.26.0
Propagated dependencies: r-summarizedexperiment@1.40.0 r-stringr@1.6.0 r-s4vectors@0.48.0 r-igraph@2.2.1 r-biocgenerics@0.56.0 r-biobase@2.70.0
Channel: guix-bioc
Location: guix-bioc/packages/r.scm (guix-bioc packages r)
Home page: https://github.com/Matteo-Ciciani/scudo
Licenses: GPL 3
Build system: r
Synopsis: Signature-based Clustering for Diagnostic Purposes
Description:

SCUDO (Signature-based Clustering for Diagnostic Purposes) is a rank-based method for the analysis of gene expression profiles for diagnostic and classification purposes. It is based on the identification of sample-specific gene signatures composed of the most up- and down-regulated genes for that sample. Starting from gene expression data, functions in this package identify sample-specific gene signatures and use them to build a graph of samples. In this graph samples are joined by edges if they have a similar expression profile, according to a pre-computed similarity matrix. The similarity between the expression profiles of two samples is computed using a method similar to GSEA. The graph of samples can then be used to perform community clustering or to perform supervised classification of samples in a testing set.

r-rbsurv 2.68.0
Propagated dependencies: r-survival@3.8-3 r-biobase@2.70.0
Channel: guix-bioc
Location: guix-bioc/packages/r.scm (guix-bioc packages r)
Home page: http://www.korea.ac.kr/~stat2242/
Licenses: GPL 2+
Build system: r
Synopsis: Robust likelihood-based survival modeling with microarray data
Description:

This package selects genes associated with survival.

r-rnits 1.44.0
Propagated dependencies: r-reshape2@1.4.5 r-qvalue@2.42.0 r-limma@3.66.0 r-impute@1.84.0 r-ggplot2@4.0.1 r-boot@1.3-32 r-biobase@2.70.0 r-affy@1.88.0
Channel: guix-bioc
Location: guix-bioc/packages/r.scm (guix-bioc packages r)
Home page: https://bioconductor.org/packages/Rnits
Licenses: GPL 3
Build system: r
Synopsis: R Normalization and Inference of Time Series data
Description:

R/Bioconductor package for normalization, curve registration and inference in time course gene expression data.

r-rgu34a-db 3.13.0
Propagated dependencies: r-org-rn-eg-db@3.22.0 r-annotationdbi@1.72.0
Channel: guix-bioc
Location: guix-bioc/packages/r.scm (guix-bioc packages r)
Home page: https://bioconductor.org/packages/rgu34a.db
Licenses: Artistic License 2.0
Build system: r
Synopsis: Affymetrix Affymetrix RG_U34A Array annotation data (chip rgu34a)
Description:

Affymetrix Affymetrix RG_U34A Array annotation data (chip rgu34a) assembled using data from public repositories.

r-ragene11stprobeset-db 8.8.0
Propagated dependencies: r-org-rn-eg-db@3.22.0 r-annotationdbi@1.72.0
Channel: guix-bioc
Location: guix-bioc/packages/r.scm (guix-bioc packages r)
Home page: https://bioconductor.org/packages/ragene11stprobeset.db
Licenses: Artistic License 2.0
Build system: r
Synopsis: Affymetrix ragene11 annotation data (chip ragene11stprobeset)
Description:

Affymetrix ragene11 annotation data (chip ragene11stprobeset) assembled using data from public repositories.

r-rprimer 1.14.0
Propagated dependencies: r-shinyfeedback@0.4.0 r-shinycssloaders@1.1.0 r-shiny@1.11.1 r-s4vectors@0.48.0 r-reshape2@1.4.5 r-patchwork@1.3.2 r-mathjaxr@1.8-0 r-iranges@2.44.0 r-ggplot2@4.0.1 r-dt@0.34.0 r-bslib@0.9.0 r-biostrings@2.78.0
Channel: guix-bioc
Location: guix-bioc/packages/r.scm (guix-bioc packages r)
Home page: https://github.com/sofpn/rprimer
Licenses: GPL 3
Build system: r
Synopsis: Design Degenerate Oligos from a Multiple DNA Sequence Alignment
Description:

Functions, workflow, and a Shiny application for visualizing sequence conservation and designing degenerate primers, probes, and (RT)-(q/d)PCR assays from a multiple DNA sequence alignment. The results can be presented in data frame format and visualized as dashboard-like plots. For more information, please see the package vignette.

r-rain 1.44.0
Propagated dependencies: r-multtest@2.66.0 r-gmp@0.7-5
Channel: guix-bioc
Location: guix-bioc/packages/r.scm (guix-bioc packages r)
Home page: https://bioconductor.org/packages/rain
Licenses: GPL 2
Build system: r
Synopsis: Rhythmicity Analysis Incorporating Non-parametric Methods
Description:

This package uses non-parametric methods to detect rhythms in time series. It deals with outliers, missing values and is optimized for time series comprising 10-100 measurements. As it does not assume expect any distinct waveform it is optimal or detecting oscillating behavior (e.g. circadian or cell cycle) in e.g. genome- or proteome-wide biological measurements such as: micro arrays, proteome mass spectrometry, or metabolome measurements.

r-ramwas 1.34.0
Propagated dependencies: r-rsamtools@2.26.0 r-kernsmooth@2.23-26 r-glmnet@4.1-10 r-genomicalignments@1.46.0 r-filematrix@1.3 r-digest@0.6.39 r-biostrings@2.78.0 r-biomart@2.66.0 r-biocgenerics@0.56.0
Channel: guix-bioc
Location: guix-bioc/packages/r.scm (guix-bioc packages r)
Home page: https://bioconductor.org/packages/ramwas/
Licenses: LGPL 3
Build system: r
Synopsis: Fast Methylome-Wide Association Study Pipeline for Enrichment Platforms
Description:

This package provides a complete toolset for methylome-wide association studies (MWAS). It is specifically designed for data from enrichment based methylation assays, but can be applied to other data as well. The analysis pipeline includes seven steps: (1) scanning aligned reads from BAM files, (2) calculation of quality control measures, (3) creation of methylation score (coverage) matrix, (4) principal component analysis for capturing batch effects and detection of outliers, (5) association analysis with respect to phenotypes of interest while correcting for top PCs and known covariates, (6) annotation of significant findings, and (7) multi-marker analysis (methylation risk score) using elastic net. Additionally, RaMWAS include tools for joint analysis of methlyation and genotype data. This work is published in Bioinformatics, Shabalin et al. (2018) <doi:10.1093/bioinformatics/bty069>.

r-raerdata 1.8.0
Propagated dependencies: r-singlecellexperiment@1.32.0 r-rtracklayer@1.70.0 r-rsamtools@2.26.0 r-experimenthub@3.0.0 r-biocgenerics@0.56.0
Channel: guix-bioc
Location: guix-bioc/packages/r.scm (guix-bioc packages r)
Home page: https://github.com/rnabioco/raerdata
Licenses: Expat
Build system: r
Synopsis: collection of datasets for use with raer package
Description:

raerdata is an ExperimentHub package that provides a collection of files useful for demostrating functionality in the raer package. Datasets include 10x genomics scRNA-seq, bulk RNA-seq, and paired whole-genome and RNA-seq data. Additionally databases of human and mouse RNA editing sites are provided.

r-rhesus-db0 3.22.0
Propagated dependencies: r-annotationdbi@1.72.0
Channel: guix-bioc
Location: guix-bioc/packages/r.scm (guix-bioc packages r)
Home page: https://bioconductor.org/packages/rhesus.db0
Licenses: Artistic License 2.0
Build system: r
Synopsis: Base Level Annotation databases for rhesus
Description:

Base annotation databases for rhesus, intended ONLY to be used by AnnotationDbi to produce regular annotation packages.

r-rigraphlib 1.2.0
Propagated dependencies: r-biocmake@1.2.0
Channel: guix-bioc
Location: guix-bioc/packages/r.scm (guix-bioc packages r)
Home page: https://github.com/libscran/Rigraphlib
Licenses: GPL 3
Build system: r
Synopsis: igraph library as an R package
Description:

Vendors the igraph C source code and builds it into a static library. Other Bioconductor packages can link to libigraph.a in their own C/C++ code. This is intended for packages wrapping C/C++ libraries that depend on the igraph C library and cannot be easily adapted to use the igraph R package.

r-rarevariantvis 2.38.0
Propagated dependencies: r-variantannotation@1.56.0 r-txdb-hsapiens-ucsc-hg19-knowngene@3.22.1 r-summarizedexperiment@1.40.0 r-s4vectors@0.48.0 r-phastcons100way-ucsc-hg19@3.7.2 r-iranges@2.44.0 r-gtools@3.9.5 r-googlevis@0.7.3 r-genomicscores@2.22.0 r-genomicranges@1.62.0 r-genomicfeatures@1.62.0 r-genomeinfodb@1.46.0 r-bsgenome-hsapiens-ucsc-hg19@1.4.3 r-bsgenome@1.78.0 r-biocgenerics@0.56.0
Channel: guix-bioc
Location: guix-bioc/packages/r.scm (guix-bioc packages r)
Home page: https://bioconductor.org/packages/RareVariantVis
Licenses: Artistic License 2.0
Build system: r
Synopsis: suite for analysis of rare genomic variants in whole genome sequencing data
Description:

Second version of RareVariantVis package aims to provide comprehensive information about rare variants for your genome data. It annotates, filters and presents genomic variants (especially rare ones) in a global, per chromosome way. For discovered rare variants CRISPR guide RNAs are designed, so the user can plan further functional studies. Large structural variants, including copy number variants are also supported. Package accepts variants directly from variant caller - for example GATK or Speedseq. Output of package are lists of variants together with adequate visualization. Visualization of variants is performed in two ways - standard that outputs png figures and interactive that uses JavaScript d3 package. Interactive visualization allows to analyze trio/family data, for example in search for causative variants in rare Mendelian diseases, in point-and-click interface. The package includes homozygous region caller and allows to analyse whole human genomes in less than 30 minutes on a desktop computer. RareVariantVis disclosed novel causes of several rare monogenic disorders, including one with non-coding causative variant - keratolythic winter erythema.

r-rgraph2js 1.38.0
Propagated dependencies: r-whisker@0.4.1 r-rjson@0.2.23 r-graph@1.88.0 r-digest@0.6.39
Channel: guix-bioc
Location: guix-bioc/packages/r.scm (guix-bioc packages r)
Home page: https://bioconductor.org/packages/RGraph2js
Licenses: GPL 2
Build system: r
Synopsis: Convert a Graph into a D3js Script
Description:

Generator of web pages which display interactive network/graph visualizations with D3js, jQuery and Raphael.

r-regionalpcs 1.8.0
Channel: guix-bioc
Location: guix-bioc/packages/r.scm (guix-bioc packages r)
Home page: https://github.com/tyeulalio/regionalpcs
Licenses: Expat
Build system: r
Synopsis: Summarizing Regional Methylation with Regional Principal Components Analysis
Description:

This package provides functions to summarize DNA methylation data using regional principal components. Regional principal components are computed using principal components analysis within genomic regions to summarize the variability in methylation levels across CpGs. The number of principal components is chosen using either the Marcenko-Pasteur or Gavish-Donoho method to identify relevant signal in the data.

r-reconsi 1.22.0
Propagated dependencies: r-reshape2@1.4.5 r-phyloseq@1.54.0 r-matrixstats@1.5.0 r-matrix@1.7-4 r-ks@1.15.1 r-ggplot2@4.0.1
Channel: guix-bioc
Location: guix-bioc/packages/r.scm (guix-bioc packages r)
Home page: https://bioconductor.org/packages/reconsi
Licenses: GPL 2
Build system: r
Synopsis: Resampling Collapsed Null Distributions for Simultaneous Inference
Description:

Improves simultaneous inference under dependence of tests by estimating a collapsed null distribution through resampling. Accounting for the dependence between tests increases the power while reducing the variability of the false discovery proportion. This dependence is common in genomics applications, e.g. when combining flow cytometry measurements with microbiome sequence counts.

r-rae230a-db 3.13.0
Propagated dependencies: r-org-rn-eg-db@3.22.0 r-annotationdbi@1.72.0
Channel: guix-bioc
Location: guix-bioc/packages/r.scm (guix-bioc packages r)
Home page: https://bioconductor.org/packages/rae230a.db
Licenses: Artistic License 2.0
Build system: r
Synopsis: Affymetrix Affymetrix RAE230A Array annotation data (chip rae230a)
Description:

Affymetrix Affymetrix RAE230A Array annotation data (chip rae230a) assembled using data from public repositories.

r-rattoxfxcdf 2.18.0
Propagated dependencies: r-annotationdbi@1.72.0
Channel: guix-bioc
Location: guix-bioc/packages/r.scm (guix-bioc packages r)
Home page: https://bioconductor.org/packages/rattoxfxcdf
Licenses: LGPL 2.0+
Build system: r
Synopsis: rattoxfxcdf
Description:

This package provides a package containing an environment representing the RatToxFX.cdf file.

r-raex10sttranscriptcluster-db 8.8.0
Propagated dependencies: r-org-rn-eg-db@3.22.0 r-annotationdbi@1.72.0
Channel: guix-bioc
Location: guix-bioc/packages/r.scm (guix-bioc packages r)
Home page: https://bioconductor.org/packages/raex10sttranscriptcluster.db
Licenses: Artistic License 2.0
Build system: r
Synopsis: Affymetrix raex10 annotation data (chip raex10sttranscriptcluster)
Description:

Affymetrix raex10 annotation data (chip raex10sttranscriptcluster) assembled using data from public repositories.

r-ragene21sttranscriptcluster-db 8.8.0
Propagated dependencies: r-org-rn-eg-db@3.22.0 r-annotationdbi@1.72.0
Channel: guix-bioc
Location: guix-bioc/packages/r.scm (guix-bioc packages r)
Home page: https://bioconductor.org/packages/ragene21sttranscriptcluster.db
Licenses: Artistic License 2.0
Build system: r
Synopsis: Affymetrix ragene21 annotation data (chip ragene21sttranscriptcluster)
Description:

Affymetrix ragene21 annotation data (chip ragene21sttranscriptcluster) assembled using data from public repositories.

r-rnaeditr 1.20.0
Propagated dependencies: r-survival@3.8-3 r-seqinfo@1.0.0 r-s4vectors@0.48.0 r-plyr@1.8.9 r-logistf@1.26.1 r-iranges@2.44.0 r-genomicranges@1.62.0 r-corrplot@0.95 r-bumphunter@1.52.0 r-biocgenerics@0.56.0
Channel: guix-bioc
Location: guix-bioc/packages/r.scm (guix-bioc packages r)
Home page: https://github.com/TransBioInfoLab/rnaEditr
Licenses: GPL 3
Build system: r
Synopsis: Statistical analysis of RNA editing sites and hyper-editing regions
Description:

RNAeditr analyzes site-specific RNA editing events, as well as hyper-editing regions. The editing frequencies can be tested against binary, continuous or survival outcomes. Multiple covariate variables as well as interaction effects can also be incorporated in the statistical models.

r-reactomegsa 1.24.1
Channel: guix-bioc
Location: guix-bioc/packages/r.scm (guix-bioc packages r)
Home page: https://github.com/reactome/ReactomeGSA
Licenses: Expat
Build system: r
Synopsis: Client for the Reactome Analysis Service for comparative multi-omics gene set analysis
Description:

The ReactomeGSA packages uses Reactome's online analysis service to perform a multi-omics gene set analysis. The main advantage of this package is, that the retrieved results can be visualized using REACTOME's powerful webapplication. Since Reactome's analysis service also uses R to perfrom the actual gene set analysis you will get similar results when using the same packages (such as limma and edgeR) locally. Therefore, if you only require a gene set analysis, different packages are more suited.

r-rqt 1.36.0
Channel: guix-bioc
Location: guix-bioc/packages/r.scm (guix-bioc packages r)
Home page: https://github.com/izhbannikov/rqt
Licenses: GPL 2+ GPL 3+
Build system: r
Synopsis: rqt: utilities for gene-level meta-analysis
Description:

Despite the recent advances of modern GWAS methods, it still remains an important problem of addressing calculation an effect size and corresponding p-value for the whole gene rather than for single variant. The R- package rqt offers gene-level GWAS meta-analysis. For more information, see: "Gene-set association tests for next-generation sequencing data" by Lee et al (2016), Bioinformatics, 32(17), i611-i619, <doi:10.1093/bioinformatics/btw429>.

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Total results: 69112