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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:

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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-rfastp 1.20.1
Propagated dependencies: r-rjson@0.2.23 r-rhtslib@3.6.0 r-reshape2@1.4.5 r-rcpp@1.1.0 r-ggplot2@4.0.1
Channel: guix-bioc
Location: guix-bioc/packages/r.scm (guix-bioc packages r)
Home page: https://bioconductor.org/packages/Rfastp
Licenses: FSDG-compatible
Build system: r
Synopsis: An Ultra-Fast and All-in-One Fastq Preprocessor (Quality Control, Adapter, low quality and polyX trimming) and UMI Sequence Parsing)
Description:

Rfastp is an R wrapper of fastp developed in c++. fastp performs quality control for fastq files. including low quality bases trimming, polyX trimming, adapter auto-detection and trimming, paired-end reads merging, UMI sequence/id handling. Rfastp can concatenate multiple files into one file (like shell command cat) and accept multiple files as input.

r-ruvnormalize 1.44.0
Propagated dependencies: r-ruvnormalizedata@1.30.0 r-biobase@2.70.0
Channel: guix-bioc
Location: guix-bioc/packages/r.scm (guix-bioc packages r)
Home page: https://bioconductor.org/packages/RUVnormalize
Licenses: GPL 3
Build system: r
Synopsis: RUV for normalization of expression array data
Description:

RUVnormalize is meant to remove unwanted variation from gene expression data when the factor of interest is not defined, e.g., to clean up a dataset for general use or to do any kind of unsupervised analysis.

r-ruvnormalizedata 1.30.0
Propagated dependencies: r-biobase@2.70.0
Channel: guix-bioc
Location: guix-bioc/packages/r.scm (guix-bioc packages r)
Home page: https://bioconductor.org/packages/RUVnormalizeData
Licenses: GPL 3
Build system: r
Synopsis: Gender data for the RUVnormalize package
Description:

Microarray gene expression data from the study of Vawter et al., 2004.

r-rtrmui 1.48.0
Propagated dependencies: r-shiny@1.11.1 r-rtrm@1.48.0 r-org-mm-eg-db@3.22.0 r-org-hs-eg-db@3.22.0 r-motifdb@1.52.0
Channel: guix-bioc
Location: guix-bioc/packages/r.scm (guix-bioc packages r)
Home page: https://github.com/ddiez/rTRMui
Licenses: GPL 3
Build system: r
Synopsis: shiny user interface for rTRM
Description:

This package provides a web interface to compute transcriptional regulatory modules with rTRM.

r-rqubic 1.56.0
Propagated dependencies: r-biocgenerics@0.56.0 r-biobase@2.70.0 r-biclust@2.0.3.1
Channel: guix-bioc
Location: guix-bioc/packages/r.scm (guix-bioc packages r)
Home page: https://bioconductor.org/packages/rqubic
Licenses: GPL 2
Build system: r
Synopsis: Qualitative biclustering algorithm for expression data analysis in R
Description:

This package implements the QUBIC algorithm introduced by Li et al. for the qualitative biclustering with gene expression data.

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-ragene11sttranscriptcluster-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/ragene11sttranscriptcluster.db
Licenses: Artistic License 2.0
Build system: r
Synopsis: Affymetrix ragene11 annotation data (chip ragene11sttranscriptcluster)
Description:

Affymetrix ragene11 annotation data (chip ragene11sttranscriptcluster) assembled using data from public repositories.

r-roastgsa 1.8.0
Propagated dependencies: r-rcolorbrewer@1.1-3 r-limma@3.66.0 r-gplots@3.2.0 r-ggplot2@4.0.1 r-biobase@2.70.0
Channel: guix-bioc
Location: guix-bioc/packages/r.scm (guix-bioc packages r)
Home page: https://bioconductor.org/packages/roastgsa
Licenses: GPL 3
Build system: r
Synopsis: Rotation based gene set analysis
Description:

This package implements a variety of functions useful for gene set analysis using rotations to approximate the null distribution. It contributes with the implementation of seven test statistic scores that can be used with different goals and interpretations. Several functions are available to complement the statistical results with graphical representations.

r-rnu34cdf 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/rnu34cdf
Licenses: LGPL 2.0+
Build system: r
Synopsis: rnu34cdf
Description:

This package provides a package containing an environment representing the RN_U34.CDF file.

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-rforproteomics 1.48.0
Propagated dependencies: r-r-utils@2.13.0 r-msnbase@2.36.0 r-biocviews@1.78.0 r-biocmanager@1.30.27
Channel: guix-bioc
Location: guix-bioc/packages/r.scm (guix-bioc packages r)
Home page: http://lgatto.github.com/RforProteomics/
Licenses: Artistic License 2.0
Build system: r
Synopsis: Companion package to the 'Using R and Bioconductor for proteomics data analysis' publication
Description:

This package contains code to illustrate the Using R and Bioconductor for proteomics data analysis and Visualisation of proteomics data using R and Bioconductor manuscripts. The vignettes describe the code and data needed to reproduce the examples and figures described in the paper and functionality for proteomics visualisation. It also contain various function to discover R software for mass spectrometry and proteomics.

r-roberts2005annotation-db 3.2.3
Propagated dependencies: r-org-hs-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/Roberts2005Annotation.db
Licenses: Artistic License 2.0
Build system: r
Synopsis: Roberts2005Annotation Annotation Data (Roberts2005Annotation)
Description:

Roberts2005Annotation Annotation Data (Roberts2005Annotation) assembled using data from public repositories.

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-roseq 1.22.0
Propagated dependencies: r-pbmcapply@1.5.1 r-limma@3.66.0 r-edger@4.8.0
Channel: guix-bioc
Location: guix-bioc/packages/r.scm (guix-bioc packages r)
Home page: https://github.com/krishan57gupta/ROSeq
Licenses: GPL 3
Build system: r
Synopsis: Modeling expression ranks for noise-tolerant differential expression analysis of scRNA-Seq data
Description:

ROSeq - A rank based approach to modeling gene expression with filtered and normalized read count matrix. ROSeq takes filtered and normalized read matrix and cell-annotation/condition as input and determines the differentially expressed genes between the contrasting groups of single cells. One of the input parameters is the number of cores to be used.

r-rcollectl 1.10.0
Dependencies: collectl@4.3.1
Propagated dependencies: r-processx@3.8.6 r-lubridate@1.9.4 r-ggplot2@4.0.1
Channel: guix-bioc
Location: guix-bioc/packages/r.scm (guix-bioc packages r)
Home page: https://github.com/vjcitn/Rcollectl
Licenses: Artistic License 2.0
Build system: r
Synopsis: Help use collectl with R in Linux, to measure resource consumption in R processes
Description:

Provide functions to obtain instrumentation data on processes in a unix environment. Parse output of a collectl run. Vizualize aspects of system usage over time, with annotation.

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-recount3 1.20.0
Propagated dependencies: r-summarizedexperiment@1.40.0 r-sessioninfo@1.2.3 r-s4vectors@0.48.0 r-rtracklayer@1.70.0 r-r-utils@2.13.0 r-matrix@1.7-4 r-httr@1.4.7 r-genomicranges@1.62.0 r-data-table@1.17.8 r-biocfilecache@3.0.0
Channel: guix-bioc
Location: guix-bioc/packages/r.scm (guix-bioc packages r)
Home page: https://github.com/LieberInstitute/recount3
Licenses: Artistic License 2.0
Build system: r
Synopsis: Explore and download data from the recount3 project
Description:

The recount3 package enables access to a large amount of uniformly processed RNA-seq data from human and mouse. You can download RangedSummarizedExperiment objects at the gene, exon or exon-exon junctions level with sample metadata and QC statistics. In addition we provide access to sample coverage BigWig files.

r-rrbsdata 1.30.0
Propagated dependencies: r-biseq@1.50.0
Channel: guix-bioc
Location: guix-bioc/packages/r.scm (guix-bioc packages r)
Home page: https://bioconductor.org/packages/RRBSdata
Licenses: LGPL 3
Build system: r
Synopsis: An RRBS data set with 12 samples and 10,000 simulated DMRs
Description:

RRBS data set comprising 12 samples with simulated differentially methylated regions (DMRs).

r-rtopper 1.56.0
Propagated dependencies: r-multtest@2.66.0 r-limma@3.66.0 r-biobase@2.70.0
Channel: guix-bioc
Location: guix-bioc/packages/r.scm (guix-bioc packages r)
Home page: https://bioconductor.org/packages/RTopper
Licenses: FSDG-compatible
Build system: r
Synopsis: This package is designed to perform Gene Set Analysis across multiple genomic platforms
Description:

the RTopper package is designed to perform and integrate gene set enrichment results across multiple genomic platforms.

r-raer 1.8.0
Propagated dependencies: r-summarizedexperiment@1.40.0 r-singlecellexperiment@1.32.0 r-seqinfo@1.0.0 r-s4vectors@0.48.0 r-rtracklayer@1.70.0 r-rsamtools@2.26.0 r-rhtslib@3.6.0 r-matrix@1.7-4 r-iranges@2.44.0 r-genomicranges@1.62.0 r-genomicfeatures@1.62.0 r-genomicalignments@1.46.0 r-genomeinfodb@1.46.0 r-cli@3.6.5 r-bsgenome@1.78.0 r-biostrings@2.78.0 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://rnabioco.github.io/raer
Licenses: Expat
Build system: r
Synopsis: RNA editing tools in R
Description:

Toolkit for identification and statistical testing of RNA editing signals from within R. Provides support for identifying sites from bulk-RNA and single cell RNA-seq datasets, and general methods for extraction of allelic read counts from alignment files. Facilitates annotation and exploratory analysis of editing signals using Bioconductor packages and resources.

r-ragene10stv1probe 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/ragene10stv1probe
Licenses: LGPL 2.0+
Build system: r
Synopsis: Probe sequence data for microarrays of type ragene10stv1
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 RaGene-1\_0-st-v1\_probe\_tab.

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-rcsl 1.18.0
Propagated dependencies: r-umap@0.2.10.0 r-singlecellexperiment@1.32.0 r-rtsne@0.17 r-rcppannoy@0.0.22 r-rcpp@1.1.0 r-pracma@2.4.6 r-nbclust@3.0.1 r-matrixgenerics@1.22.0 r-igraph@2.2.1 r-ggplot2@4.0.1
Channel: guix-bioc
Location: guix-bioc/packages/r.scm (guix-bioc packages r)
Home page: https://github.com/QinglinMei/RCSL
Licenses: Artistic License 2.0
Build system: r
Synopsis: Rank Constrained Similarity Learning for single cell RNA sequencing data
Description:

This package provides a novel clustering algorithm and toolkit RCSL (Rank Constrained Similarity Learning) to accurately identify various cell types using scRNA-seq data from a complex tissue. RCSL considers both lo-cal similarity and global similarity among the cells to discern the subtle differences among cells of the same type as well as larger differences among cells of different types. RCSL uses Spearman’s rank correlations of a cell’s expression vector with those of other cells to measure its global similar-ity, and adaptively learns neighbour representation of a cell as its local similarity. The overall similar-ity of a cell to other cells is a linear combination of its global similarity and local similarity.

r-regsplice 1.36.0
Propagated dependencies: r-summarizedexperiment@1.40.0 r-s4vectors@0.48.0 r-pbapply@1.7-4 r-limma@3.66.0 r-glmnet@4.1-10 r-edger@4.8.0
Channel: guix-bioc
Location: guix-bioc/packages/r.scm (guix-bioc packages r)
Home page: https://github.com/lmweber/regsplice
Licenses: Expat
Build system: r
Synopsis: L1-regularization based methods for detection of differential splicing
Description:

Statistical methods for detection of differential splicing (differential exon usage) in RNA-seq and exon microarray data, using L1-regularization (lasso) to improve power.

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Total results: 68658