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

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-ribor 1.22.0
Channel: guix-bioc
Location: guix-bioc/packages/r.scm (guix-bioc packages r)
Home page: https://bioconductor.org/packages/ribor
Licenses: GPL 3
Build system: r
Synopsis: An R Interface for Ribo Files
Description:

The ribor package provides an R Interface for .ribo files. It provides functionality to read the .ribo file, which is of HDF5 format, and performs common analyses on its contents.

r-rtcga-rppa 1.38.0
Propagated dependencies: r-rtcga@1.40.0
Channel: guix-bioc
Location: guix-bioc/packages/r.scm (guix-bioc packages r)
Home page: https://bioconductor.org/packages/RTCGA.RPPA
Licenses: GPL 2
Build system: r
Synopsis: RPPA datasets from The Cancer Genome Atlas Project
Description:

Package provides RPPA datasets from The Cancer Genome Atlas Project for all available cohorts types from http://gdac.broadinstitute.org/. Data format is explained here https://wiki.nci.nih.gov/display/TCGA/Protein+Array +Data+Format+Specification?src=search.

r-rcm 1.26.0
Propagated dependencies: r-vgam@1.1-13 r-tseries@0.10-58 r-tensor@1.5.1 r-reshape2@1.4.5 r-rcolorbrewer@1.1-3 r-phyloseq@1.54.0 r-nleqslv@3.3.5 r-mass@7.3-65 r-ggplot2@4.0.1 r-edger@4.8.0 r-alabama@2023.1.0
Channel: guix-bioc
Location: guix-bioc/packages/r.scm (guix-bioc packages r)
Home page: https://bioconductor.org/packages/release/bioc/vignettes/RCM/inst/doc/RCMvignette.html/
Licenses: GPL 2
Build system: r
Synopsis: Fit row-column association models with the negative binomial distribution for the microbiome
Description:

Combine ideas of log-linear analysis of contingency table, flexible response function estimation and empirical Bayes dispersion estimation for explorative visualization of microbiome datasets. The package includes unconstrained as well as constrained analysis. In addition, diagnostic plot to detect lack of fit are available.

r-rols 3.6.1
Propagated dependencies: r-jsonlite@2.0.0 r-httr2@1.2.1 r-biobase@2.70.0
Channel: guix-bioc
Location: guix-bioc/packages/r.scm (guix-bioc packages r)
Home page: http://lgatto.github.io/rols/
Licenses: GPL 2
Build system: r
Synopsis: An R interface to the Ontology Lookup Service
Description:

The rols package is an interface to the Ontology Lookup Service (OLS) to access and query hundred of ontolgies directly from R.

r-rnaseqsamplesizedata 1.42.0
Propagated dependencies: r-edger@4.8.0
Channel: guix-bioc
Location: guix-bioc/packages/r.scm (guix-bioc packages r)
Home page: https://bioconductor.org/packages/RnaSeqSampleSizeData
Licenses: GPL 2+
Build system: r
Synopsis: RnaSeqSampleSizeData
Description:

RnaSeqSampleSizeData package provides the read counts and dispersion distribution from real RNA-seq experiments. It can be used by RnaSeqSampleSize package to estimate sample size and power for RNA-seq experiment design.

r-rhdf5client 1.32.0
Propagated dependencies: r-rjson@0.2.23 r-httr@1.4.7 r-delayedarray@0.36.0 r-data-table@1.17.8
Channel: guix-bioc
Location: guix-bioc/packages/r.scm (guix-bioc packages r)
Home page: https://bioconductor.org/packages/rhdf5client
Licenses: Artistic License 2.0
Build system: r
Synopsis: Access HDF5 content from HDF Scalable Data Service
Description:

This package provides functionality for reading data from HDF Scalable Data Service from within R. The HSDSArray function bridges from HSDS to the user via the DelayedArray interface. Bioconductor manages an open HSDS instance graciously provided by John Readey of the HDF Group.

r-rbiopaxparser 2.50.0
Propagated dependencies: r-xml@3.99-0.20 r-data-table@1.17.8
Channel: guix-bioc
Location: guix-bioc/packages/r.scm (guix-bioc packages r)
Home page: https://github.com/frankkramer-lab/rBiopaxParser
Licenses: GPL 2+
Build system: r
Synopsis: Parses BioPax files and represents them in R
Description:

Parses BioPAX files and represents them in R, at the moment BioPAX level 2 and level 3 are supported.

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-rtca 1.62.0
Propagated dependencies: r-rcolorbrewer@1.1-3 r-gtools@3.9.5 r-biobase@2.70.0
Channel: guix-bioc
Location: guix-bioc/packages/r.scm (guix-bioc packages r)
Home page: http://code.google.com/p/xcelligence/
Licenses: LGPL 3
Build system: r
Synopsis: Open-source toolkit to analyse data from xCELLigence System (RTCA)
Description:

Import, analyze and visualize data from Roche(R) xCELLigence RTCA systems. The package imports real-time cell electrical impedance data into R. As an alternative to commercial software shipped along the system, the Bioconductor package RTCA provides several unique transformation (normalization) strategies and various visualization tools.

r-reusedata 1.10.0
Propagated dependencies: r-yaml@2.3.10 r-s4vectors@0.48.0 r-rcwlpipelines@1.26.0 r-rcwl@1.26.0 r-jsonlite@2.0.0 r-biocfilecache@3.0.0 r-basilisk@1.22.0
Channel: guix-bioc
Location: guix-bioc/packages/r.scm (guix-bioc packages r)
Home page: https://github.com/rworkflow/ReUseData
Licenses: GPL 3
Build system: r
Synopsis: Reusable and reproducible Data Management
Description:

ReUseData is an _R/Bioconductor_ software tool to provide a systematic and versatile approach for standardized and reproducible data management. ReUseData facilitates transformation of shell or other ad hoc scripts for data preprocessing into workflow-based data recipes. Evaluation of data recipes generate curated data files in their generic formats (e.g., VCF, bed). Both recipes and data are cached using database infrastructure for easy data management and reuse. Prebuilt data recipes are available through ReUseData portal ("https://rcwl.org/dataRecipes/") with full annotation and user instructions. Pregenerated data are available through ReUseData cloud bucket that is directly downloadable through "getCloudData()".

r-rnbeads-mm10 2.18.0
Propagated dependencies: r-genomicranges@1.62.0
Channel: guix-bioc
Location: guix-bioc/packages/r.scm (guix-bioc packages r)
Home page: https://bioconductor.org/packages/RnBeads.mm10
Licenses: GPL 3
Build system: r
Synopsis: RnBeads.mm10
Description:

Automatically generated RnBeads annotation package for the assembly mm10.

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-rae230bprobe 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/rae230bprobe
Licenses: LGPL 2.0+
Build system: r
Synopsis: Probe sequence data for microarrays of type rae230b
Description:

This package was automatically created by package AnnotationForge version 1.11.21. The probe sequence data was obtained from http://www.affymetrix.com. The file name was RAE230B\_probe\_tab.

r-ri16cod-db 3.4.0
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/ri16cod.db
Licenses: Artistic License 2.0
Build system: r
Synopsis: Codelink Rat Inflammation 16 Bioarray annotation data (chip ri16cod)
Description:

Codelink Rat Inflammation 16 Bioarray annotation data (chip ri16cod) assembled using data from public repositories.

r-ribocrypt 1.16.0
Channel: guix-bioc
Location: guix-bioc/packages/r.scm (guix-bioc packages r)
Home page: https://github.com/m-swirski/RiboCrypt
Licenses: Expat
Build system: r
Synopsis: Interactive visualization in genomics
Description:

R Package for interactive visualization and browsing NGS data. It contains a browser for both transcript and genomic coordinate view. In addition a QC and general metaplots are included, among others differential translation plots and gene expression plots. The package is still under development.

r-redisparam 1.12.1
Dependencies: hiredis@1.1.0
Propagated dependencies: r-withr@3.0.2 r-redux@1.1.5 r-logger@0.4.1 r-biocparallel@1.44.0
Channel: guix-bioc
Location: guix-bioc/packages/r.scm (guix-bioc packages r)
Home page: https://bioconductor.org/packages/RedisParam
Licenses: Artistic License 2.0
Build system: r
Synopsis: Provide a 'redis' back-end for BiocParallel
Description:

This package provides a Redis-based back-end for BiocParallel, enabling an alternative mechanism for distributed computation. The The manager distributes tasks to a worker pool through a central Redis server, rather than directly to workers as with other BiocParallel implementations. This means that the worker pool can change dynamically during job evaluation. All features of BiocParallel are supported, including reproducible random number streams, logging to the manager, and alternative load balancing task distributions.

r-rnaseqcovarimpute 1.8.0
Channel: guix-bioc
Location: guix-bioc/packages/r.scm (guix-bioc packages r)
Home page: https://github.com/brennanhilton/RNAseqCovarImpute
Licenses: GPL 3
Build system: r
Synopsis: Impute Covariate Data in RNA Sequencing Studies
Description:

The RNAseqCovarImpute package makes linear model analysis for RNA sequencing read counts compatible with multiple imputation (MI) of missing covariates. A major problem with implementing MI in RNA sequencing studies is that the outcome data must be included in the imputation prediction models to avoid bias. This is difficult in omics studies with high-dimensional data. The first method we developed in the RNAseqCovarImpute package surmounts the problem of high-dimensional outcome data by binning genes into smaller groups to analyze pseudo-independently. This method implements covariate MI in gene expression studies by 1) randomly binning genes into smaller groups, 2) creating M imputed datasets separately within each bin, where the imputation predictor matrix includes all covariates and the log counts per million (CPM) for the genes within each bin, 3) estimating gene expression changes using `limma::voom` followed by `limma::lmFit` functions, separately on each M imputed dataset within each gene bin, 4) un-binning the gene sets and stacking the M sets of model results before applying the `limma::squeezeVar` function to apply a variance shrinking Bayesian procedure to each M set of model results, 5) pooling the results with Rubins’ rules to produce combined coefficients, standard errors, and P-values, and 6) adjusting P-values for multiplicity to account for false discovery rate (FDR). A faster method uses principal component analysis (PCA) to avoid binning genes while still retaining outcome information in the MI models. Binning genes into smaller groups requires that the MI and limma-voom analysis is run many times (typically hundreds). The more computationally efficient MI PCA method implements covariate MI in gene expression studies by 1) performing PCA on the log CPM values for all genes using the Bioconductor `PCAtools` package, 2) creating M imputed datasets where the imputation predictor matrix includes all covariates and the optimum number of PCs to retain (e.g., based on Horn’s parallel analysis or the number of PCs that account for >80% explained variation), 3) conducting the standard limma-voom pipeline with the `voom` followed by `lmFit` followed by `eBayes` functions on each M imputed dataset, 4) pooling the results with Rubins’ rules to produce combined coefficients, standard errors, and P-values, and 5) adjusting P-values for multiplicity to account for false discovery rate (FDR).

r-rgmqllib 1.30.0
Channel: guix-bioc
Location: guix-bioc/packages/r.scm (guix-bioc packages r)
Home page: http://www.bioinformatics.deib.polimi.it/genomic_computing/GMQL/
Licenses: Artistic License 2.0
Build system: r
Synopsis: RGMQLlib, java libraries to run GMQL scala API
Description:

This package provides a package that contains scala libraries to call GMQL from R used by RGMQL package. It contains a scalable data management engine written in Scala programming language.

r-reder 3.6.2
Propagated dependencies: r-scales@1.4.0 r-igraph@2.2.1
Channel: guix-bioc
Location: guix-bioc/packages/r.scm (guix-bioc packages r)
Home page: https://doi.org/10.1186/gb-2012-13-4-r29
Licenses: GPL 3
Build system: r
Synopsis: Interactive visualization and manipulation of nested networks
Description:

RedeR combines an R package with a stand-alone Java application for interactive visualization and manipulation of nested networks. Graph, node, and edge attributes can be configured using either graphical or command-line methods, following igraph syntax rules.

r-rrvgo 1.22.0
Propagated dependencies: r-wordcloud@2.6 r-umap@0.2.10.0 r-treemap@2.4-4 r-tm@0.7-16 r-shiny@1.11.1 r-pheatmap@1.0.13 r-gosemsim@2.36.0 r-go-db@3.22.0 r-ggrepel@0.9.6 r-ggplot2@4.0.1 r-annotationdbi@1.72.0
Channel: guix-bioc
Location: guix-bioc/packages/r.scm (guix-bioc packages r)
Home page: https://www.bioconductor.org/packages/rrvgo
Licenses: GPL 3
Build system: r
Synopsis: Reduce + Visualize GO
Description:

Reduce and visualize lists of Gene Ontology terms by identifying redudance based on semantic similarity.

r-rmir-hsa 1.0.5
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/RmiR.hsa
Licenses: FSDG-compatible
Build system: r
Synopsis: Various databases of microRNA Targets
Description:

Various databases of microRNA Targets.

r-rificomparative 1.10.0
Channel: guix-bioc
Location: guix-bioc/packages/r.scm (guix-bioc packages r)
Home page: https://bioconductor.org/packages/rifiComparative
Licenses: FSDG-compatible
Build system: r
Synopsis: 'rifiComparative' compares the output of rifi from two different conditions
Description:

rifiComparative is a continuation of rifi package. It compares two conditions output of rifi using half-life and mRNA at time 0 segments. As an input for the segmentation, the difference between half-life of both condtions and log2FC of the mRNA at time 0 are used. The package provides segmentation, statistics, summary table, fragments visualization and some additional useful plots for further anaylsis.

r-rgenometracksdata 0.99.0
Propagated dependencies: r-annotationhub@4.0.0
Channel: guix-bioc
Location: guix-bioc/packages/r.scm (guix-bioc packages r)
Home page: https://bioconductor.org/packages/rGenomeTracksData
Licenses: GPL 3+
Build system: r
Synopsis: Demonstration Data from rGenomeTracks Package
Description:

rGenomeTracksData is a collection of data from pyGenomeTracks project. The purpose of this data is testing and demonstration of rGenomeTracks. This package include 14 sample file from different genomic and epigenomic file format.

r-rjmcmcnucleosomes 1.34.0
Dependencies: gsl@2.8
Propagated dependencies: r-seqinfo@1.0.0 r-s4vectors@0.48.0 r-rcpp@1.1.0 r-iranges@2.44.0 r-genomicranges@1.62.0 r-consensusseeker@1.38.0 r-biocparallel@1.44.0 r-biocgenerics@0.56.0
Channel: guix-bioc
Location: guix-bioc/packages/r.scm (guix-bioc packages r)
Home page: https://github.com/ArnaudDroitLab/RJMCMCNucleosomes
Licenses: Artistic License 2.0
Build system: r
Synopsis: Bayesian hierarchical model for genome-wide nucleosome positioning with high-throughput short-read data (MNase-Seq)
Description:

This package does nucleosome positioning using informative Multinomial-Dirichlet prior in a t-mixture with reversible jump estimation of nucleosome positions for genome-wide profiling.

Total results: 2911