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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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r-edaseq 2.44.0
Propagated dependencies: r-annotationdbi@1.72.0 r-aroma-light@3.40.0 r-biobase@2.70.0 r-biocgenerics@0.56.0 r-biocmanager@1.30.27 r-biomart@2.66.0 r-biostrings@2.78.0 r-genomicfeatures@1.62.0 r-genomicranges@1.62.0 r-iranges@2.44.0 r-rsamtools@2.26.0 r-shortread@1.68.0
Channel: guix
Location: gnu/packages/bioconductor.scm (gnu packages bioconductor)
Home page: https://github.com/drisso/EDASeq
Licenses: Artistic License 2.0
Build system: r
Synopsis: Exploratory data analysis and normalization for RNA-Seq
Description:

This package provides support for numerical and graphical summaries of RNA-Seq genomic read data. Provided within-lane normalization procedures to adjust for GC-content effect (or other gene-level effects) on read counts: loess robust local regression, global-scaling, and full-quantile normalization. Between-lane normalization procedures to adjust for distributional differences between lanes (e.g., sequencing depth): global-scaling and full-quantile normalization.

r-variancepartition 1.40.0
Propagated dependencies: r-aod@1.3.3 r-biobase@2.70.0 r-biocparallel@1.44.0 r-corpcor@1.6.10 r-fancova@0.6-1 r-ggplot2@4.0.1 r-gplots@3.2.0 r-gtools@3.9.5 r-iterators@1.0.14 r-limma@3.66.0 r-lme4@1.1-37 r-lmertest@3.1-3 r-mass@7.3-65 r-matrix@1.7-4 r-matrixstats@1.5.0 r-pbkrtest@0.5.5 r-rdpack@2.6.4 r-remacor@0.0.20 r-reshape2@1.4.5 r-rhpcblasctl@0.23-42 r-rlang@1.1.6 r-scales@1.4.0
Channel: guix
Location: gnu/packages/bioconductor.scm (gnu packages bioconductor)
Home page: https://bioconductor.org/packages/variancePartition/
Licenses: GPL 2+
Build system: r
Synopsis: Analyze variation in gene expression experiments
Description:

This is a package providing tools to quantify and interpret multiple sources of biological and technical variation in gene expression experiments. It uses a linear mixed model to quantify variation in gene expression attributable to individual, tissue, time point, or technical variables. The package includes dream differential expression analysis for repeated measures.

r-biocset 1.24.0
Propagated dependencies: r-annotationdbi@1.72.0 r-biocio@1.20.0 r-dplyr@1.1.4 r-keggrest@1.50.0 r-ontologyindex@2.12 r-plyr@1.8.9 r-rlang@1.1.6 r-s4vectors@0.48.0 r-tibble@3.3.0 r-tidyr@1.3.1
Channel: guix
Location: gnu/packages/bioconductor.scm (gnu packages bioconductor)
Home page: https://bioconductor.org/packages/BiocSet
Licenses: Artistic License 2.0
Build system: r
Synopsis: Representing different biological sets
Description:

BiocSet displays different biological sets in a triple tibble format. These three tibbles are element, set, and elementset. The user has the ability to activate one of these three tibbles to perform common functions from the dplyr package. Mapping functionality and accessing web references for elements/sets are also available in BiocSet.

r-baalchip 1.36.0
Propagated dependencies: r-coda@0.19-4.1 r-doby@4.7.0 r-doparallel@1.0.17 r-foreach@1.5.2 r-genomeinfodb@1.46.0 r-genomicalignments@1.46.0 r-genomicranges@1.62.0 r-ggplot2@4.0.1 r-iranges@2.44.0 r-reshape2@1.4.5 r-rsamtools@2.26.0 r-scales@1.4.0
Channel: guix
Location: gnu/packages/bioconductor.scm (gnu packages bioconductor)
Home page: https://bioconductor.org/packages/BaalChIP
Licenses: Artistic License 2.0
Build system: r
Synopsis: Analysis of allele-specific transcription factor binding in cancer genomes
Description:

This package offers functions to process multiple ChIP-seq BAM files and detect allele-specific events. It computes allele counts at individual variants (SNPs/SNVs), implements extensive QC (quality control) steps to remove problematic variants, and utilizes a Bayesian framework to identify statistically significant allele-specific events. BaalChIP is able to account for copy number differences between the two alleles, a known phenotypical feature of cancer samples.

r-motifrg 1.31.0
Propagated dependencies: r-biostrings@2.78.0 r-bsgenome@1.78.0 r-bsgenome-hsapiens-ucsc-hg19@1.4.3 r-iranges@2.44.0 r-seqlogo@1.76.0 r-xvector@0.50.0
Channel: guix
Location: gnu/packages/bioconductor.scm (gnu packages bioconductor)
Home page: https://bioconductor.org/packages/motifRG
Licenses: Artistic License 2.0
Build system: r
Synopsis: Discover motifs in high throughput sequencing data
Description:

This package provides tools for discriminative motif discovery in high throughput genetic sequencing data sets using regression methods.

r-cistopic-next 0.3.0-1.04cecbb
Propagated dependencies: r-aucell@1.32.0 r-data-table@1.17.8 r-dosnow@1.0.20 r-dplyr@1.1.4 r-dt@0.34.0 r-feather@0.3.5 r-fitdistrplus@1.2-4 r-genomicranges@1.62.0 r-ggplot2@4.0.1 r-lda@1.5.2 r-matrix@1.7-4 r-plyr@1.8.9 r-rcistarget@1.29.0 r-rtracklayer@1.70.0 r-s4vectors@0.48.0 r-text2vec@0.6.4
Channel: guix
Location: gnu/packages/bioconductor.scm (gnu packages bioconductor)
Home page: https://github.com/aertslab/cisTopic
Licenses: GPL 3
Build system: r
Synopsis: Modelling of cis-regulatory topics from single cell epigenomics data
Description:

The sparse nature of single cell epigenomics data can be overruled using probabilistic modelling methods such as Latent Dirichlet Allocation (LDA). This package allows the probabilistic modelling of cis-regulatory topics (cisTopics) from single cell epigenomics data, and includes functionalities to identify cell states based on the contribution of cisTopics and explore the nature and regulatory proteins driving them.

r-biocneighbors 2.4.0
Propagated dependencies: r-assorthead@1.4.0 r-rcpp@1.1.0
Channel: guix
Location: gnu/packages/bioconductor.scm (gnu packages bioconductor)
Home page: https://bioconductor.org/packages/BiocNeighbors
Licenses: GPL 3
Build system: r
Synopsis: Nearest Neighbor Detection for Bioconductor packages
Description:

This package implements exact and approximate methods for nearest neighbor detection, in a framework that allows them to be easily switched within Bioconductor packages or workflows. The exact algorithm is implemented using pre-clustering with the k-means algorithm. Functions are also provided to search for all neighbors within a given distance. Parallelization is achieved for all methods using the BiocParallel framework.

r-transcriptr 1.37.0
Propagated dependencies: r-biocgenerics@0.56.0 r-caret@7.0-1 r-chipseq@1.60.0 r-e1071@1.7-16 r-genomeinfodb@1.46.0 r-genomicalignments@1.46.0 r-genomicfeatures@1.62.0 r-genomicranges@1.62.0 r-ggplot2@4.0.1 r-iranges@2.44.0 r-proc@1.19.0.1 r-reshape2@1.4.5 r-rsamtools@2.26.0 r-rtracklayer@1.70.0 r-s4vectors@0.48.0
Channel: guix
Location: gnu/packages/bioconductor.scm (gnu packages bioconductor)
Home page: https://bioconductor.org/packages/transcriptR
Licenses: GPL 3
Build system: r
Synopsis: Primary transcripts detection and quantification
Description:

The differences in the RNA types being sequenced have an impact on the resulting sequencing profiles. mRNA-seq data is enriched with reads derived from exons, while GRO-, nucRNA- and chrRNA-seq demonstrate a substantial broader coverage of both exonic and intronic regions. The presence of intronic reads in GRO-seq type of data makes it possible to use it to computationally identify and quantify all de novo continuous regions of transcription distributed across the genome. This type of data, however, is more challenging to interpret and less common practice compared to mRNA-seq. One of the challenges for primary transcript detection concerns the simultaneous transcription of closely spaced genes, which needs to be properly divided into individually transcribed units. The R package transcriptR combines RNA-seq data with ChIP-seq data of histone modifications that mark active Transcription Start Sites (TSSs), such as, H3K4me3 or H3K9/14Ac to overcome this challenge. The advantage of this approach over the use of, for example, gene annotations is that this approach is data driven and therefore able to deal also with novel and case specific events.

r-affxparser 1.82.0
Channel: guix
Location: gnu/packages/bioconductor.scm (gnu packages bioconductor)
Home page: https://github.com/HenrikBengtsson/affxparser
Licenses: LGPL 2.0+ LGPL 2.1 GPL 2
Build system: r
Synopsis: Affymetrix File Parsing SDK
Description:

This is a package for parsing Affymetrix files (CDF, CEL, CHP, BPMAP, BAR). It provides methods for fast and memory efficient parsing of Affymetrix files using the Affymetrix' Fusion SDK. Both ASCII- and binary-based files are supported. Currently, there are methods for reading chip definition file (CDF) and a cell intensity file (CEL). These files can be read either in full or in part. For example, probe signals from a few probesets can be extracted very quickly from a set of CEL files into a convenient list structure.

r-helloranges 1.36.0
Propagated dependencies: r-biocgenerics@0.56.0 r-biocio@1.20.0 r-biostrings@2.78.0 r-bsgenome@1.78.0 r-docopt@0.7.2 r-genomicalignments@1.46.0 r-genomicfeatures@1.62.0 r-genomicranges@1.62.0 r-iranges@2.44.0 r-rsamtools@2.26.0 r-rtracklayer@1.70.0 r-s4vectors@0.48.0 r-seqinfo@1.0.0 r-summarizedexperiment@1.40.0 r-variantannotation@1.56.0
Channel: guix
Location: gnu/packages/bioconductor.scm (gnu packages bioconductor)
Home page: https://bioconductor.org/packages/HelloRanges
Licenses: GPL 2+
Build system: r
Synopsis: Introduce *Ranges to bedtools users
Description:

This package translates bedtools command-line invocations to R code calling functions from the Bioconductor *Ranges infrastructure. This is intended to educate novice Bioconductor users and to compare the syntax and semantics of the two frameworks.

r-txdb-mmusculus-ucsc-mm9-knowngene 3.2.2
Propagated dependencies: r-annotationdbi@1.72.0 r-genomicfeatures@1.62.0
Channel: guix
Location: gnu/packages/bioconductor.scm (gnu packages bioconductor)
Home page: https://bioconductor.org/packages/TxDb.Mmusculus.UCSC.mm9.knownGene/
Licenses: Artistic License 2.0
Build system: r
Synopsis: Annotation package for mouse genome in TxDb format
Description:

This package provides an annotation database of Mouse genome data. It is derived from the UCSC mm9 genome and based on the "knownGene" track. The database is exposed as a TxDb object.

r-xmapbridge 1.68.0
Channel: guix
Location: gnu/packages/bioconductor.scm (gnu packages bioconductor)
Home page: https://git.bioconductor.org/packages/xmapbridge
Licenses: LGPL 3
Build system: r
Synopsis: Display numeric data in the web based genome browser X:MAP
Description:

The package xmapbridge can plot graphs in the X:Map genome browser. X:Map uses the Google Maps API to provide a scrollable view of the genome. It supports a number of species, and can be accessed at http://xmap.picr.man.ac.uk. This package exports plotting files in a suitable format. Graph plotting in R is done using calls to the functions xmap.plot and xmap.points, which have parameters that aim to be similar to those used by the standard plot methods in R. These result in data being written to a set of files (in a specific directory structure) that contain the data to be displayed, as well as some additional meta-data describing each of the graphs.

r-bsgenome-drerio-ucsc-danrer10 1.4.2
Propagated dependencies: r-bsgenome@1.78.0
Channel: guix
Location: gnu/packages/bioconductor.scm (gnu packages bioconductor)
Home page: https://bioconductor.org/packages/BSgenome.Drerio.UCSC.danRer10
Licenses: Artistic License 2.0
Build system: r
Synopsis: Full genome sequences for Danio rerio (UCSC version danRer10)
Description:

This package provides full genome sequences for Danio rerio (Zebrafish) as provided by UCSC (danRer10, Sep. 2014) and stored in Biostrings objects.

r-bioccheck 1.46.0
Propagated dependencies: r-biocbaseutils@1.12.0 r-biocfilecache@3.0.0 r-biocmanager@1.30.27 r-biocviews@1.78.0 r-callr@3.7.6 r-cli@3.6.5 r-codetools@0.2-20 r-graph@1.88.0 r-httr2@1.2.1 r-knitr@1.50 r-rvest@1.0.5 r-stringdist@0.9.15
Channel: guix
Location: gnu/packages/bioconductor.scm (gnu packages bioconductor)
Home page: https://bioconductor.org/packages/BiocCheck
Licenses: Artistic License 2.0
Build system: r
Synopsis: Executes Bioconductor-specific package checks
Description:

This package contains tools to perform additional quality checks on R packages that are to be submitted to the Bioconductor repository.

r-ace 1.28.0
Propagated dependencies: r-biobase@2.70.0 r-genomicranges@1.62.0 r-ggplot2@4.0.1 r-qdnaseq@1.46.0
Channel: guix
Location: gnu/packages/bioconductor.scm (gnu packages bioconductor)
Home page: https://github.com/tgac-vumc/ACE
Licenses: GPL 2
Build system: r
Synopsis: Absolute copy number estimation from low-coverage whole genome sequencing
Description:

This package uses segmented copy number data to estimate tumor cell percentage and produce copy number plots displaying absolute copy numbers. For this it uses segmented data from the QDNAseq package, which in turn uses a number of dependencies to turn mapped reads into segmented data. ACE will run QDNAseq or use its output rds-file of segmented data. It will subsequently run through all samples in the object(s), for which it will create individual subdirectories. For each sample, it will calculate how well the segments fit (the relative error) to integer copy numbers for each percentage of tumor cells (cells with divergent segments).

r-scannotatr 1.16.0
Propagated dependencies: r-annotationhub@4.0.0 r-ape@5.8-1 r-caret@7.0-1 r-data-tree@1.2.0 r-dplyr@1.1.4 r-e1071@1.7-16 r-ggplot2@4.0.1 r-kernlab@0.9-33 r-proc@1.19.0.1 r-rocr@1.0-11 r-seurat@5.3.1 r-singlecellexperiment@1.32.0 r-summarizedexperiment@1.40.0
Channel: guix
Location: gnu/packages/bioconductor.scm (gnu packages bioconductor)
Home page: https://github.com/grisslab/scAnnotatR
Licenses: Expat
Build system: r
Synopsis: Pretrained models for prediction on single cell RNA-sequencing data
Description:

This package comprises a set of pretrained machine learning models to predict basic immune cell types. This enables to quickly get a first annotation of the cell types present in the dataset without requiring prior knowledge. The package also lets you train using own models to predict new cell types based on specific research needs.

r-oligoclasses 1.72.0
Propagated dependencies: r-affyio@1.80.0 r-biobase@2.70.0 r-biocgenerics@0.56.0 r-biocmanager@1.30.27 r-biostrings@2.78.0 r-dbi@1.2.3 r-ff@4.5.2 r-foreach@1.5.2 r-genomicranges@1.62.0 r-iranges@2.44.0 r-rsqlite@2.4.4 r-s4vectors@0.48.0 r-summarizedexperiment@1.40.0
Channel: guix
Location: gnu/packages/bioconductor.scm (gnu packages bioconductor)
Home page: https://bioconductor.org/packages/oligoClasses/
Licenses: GPL 2+
Build system: r
Synopsis: Classes for high-throughput arrays
Description:

This package contains class definitions, validity checks, and initialization methods for classes used by the oligo and crlmm packages.

r-a4classif 1.58.0
Propagated dependencies: r-a4core@1.58.0 r-a4preproc@1.58.0 r-biobase@2.70.0 r-glmnet@4.1-10 r-pamr@1.57 r-rocr@1.0-11 r-varselrf@0.7-8
Channel: guix
Location: gnu/packages/bioconductor.scm (gnu packages bioconductor)
Home page: https://bioconductor.org/packages/a4Classif/
Licenses: GPL 3
Build system: r
Synopsis: Automated Affymetrix array analysis classification package
Description:

This is the classification package for the automated analysis of Affymetrix arrays.

r-ggcyto 1.38.0
Propagated dependencies: r-data-table@1.17.8 r-flowcore@2.22.0 r-flowworkspace@4.22.0 r-ggplot2@4.0.1 r-gridextra@2.3 r-hexbin@1.28.5 r-ncdfflow@2.56.0 r-plyr@1.8.9 r-rcolorbrewer@1.1-3 r-rlang@1.1.6 r-scales@1.4.0
Channel: guix
Location: gnu/packages/bioconductor.scm (gnu packages bioconductor)
Home page: https://github.com/RGLab/ggcyto/issues
Licenses: Artistic License 2.0
Build system: r
Synopsis: Visualize Cytometry data with ggplot
Description:

With the dedicated fortify method implemented for flowSet, ncdfFlowSet and GatingSet classes, both raw and gated flow cytometry data can be plotted directly with ggplot. The ggcyto wrapper and some custom layers also make it easy to add gates and population statistics to the plot.

r-oscope 1.40.0
Propagated dependencies: r-biocparallel@1.44.0 r-cluster@2.1.8.1 r-ebseq@2.8.0
Channel: guix
Location: gnu/packages/bioconductor.scm (gnu packages bioconductor)
Home page: https://bioconductor.org/packages/Oscope
Licenses: ASL 2.0
Build system: r
Synopsis: Oscillatory genes identifier in unsynchronized single cell RNA-seq
Description:

Oscope is a oscillatory genes identifier in unsynchronized single cell RNA-seq. This statistical pipeline has been developed to identify and recover the base cycle profiles of oscillating genes in an unsynchronized single cell RNA-seq experiment. The Oscope pipeline includes three modules: a sine model module to search for candidate oscillator pairs; a K-medoids clustering module to cluster candidate oscillators into groups; and an extended nearest insertion module to recover the base cycle order for each oscillator group.

r-motifbreakr 2.24.0
Propagated dependencies: r-biocfilecache@3.0.0 r-biocgenerics@0.56.0 r-biocparallel@1.44.0 r-biomart@2.66.0 r-biostrings@2.78.0 r-bsgenome@1.78.0 r-bsicons@0.1.2 r-bslib@0.9.0 r-dt@0.34.0 r-genomeinfodb@1.46.0 r-genomicranges@1.62.0 r-gviz@1.54.0 r-iranges@2.44.0 r-matrixstats@1.5.0 r-motifdb@1.52.0 r-motifstack@1.54.0 r-pwalign@1.6.0 r-rtracklayer@1.70.0 r-s4vectors@0.48.0 r-shiny@1.11.1 r-stringr@1.6.0 r-summarizedexperiment@1.40.0 r-tfmpvalue@0.0.9 r-variantannotation@1.56.0 r-vroom@1.6.6
Channel: guix
Location: gnu/packages/bioconductor.scm (gnu packages bioconductor)
Home page: https://www.bioconductor.org/packages/motifbreakR/
Licenses: GPL 2+
Build system: r
Synopsis: Predicting disruptiveness of single nucleotide polymorphisms
Description:

This package allows biologists to judge in the first place whether the sequence surrounding the polymorphism is a good match, and in the second place how much information is gained or lost in one allele of the polymorphism relative to another. This package gives a choice of algorithms for interrogation of genomes with motifs from public sources:

  1. a weighted-sum probability matrix;

  2. log-probabilities;

  3. weighted by relative entropy.

This package can predict effects for novel or previously described variants in public databases, making it suitable for tasks beyond the scope of its original design. Lastly, it can be used to interrogate any genome curated within Bioconductor.

r-annotate 1.88.0
Propagated dependencies: r-annotationdbi@1.72.0 r-biobase@2.70.0 r-biocgenerics@0.56.0 r-dbi@1.2.3 r-httr@1.4.7 r-xml@3.99-0.20 r-xtable@1.8-4
Channel: guix
Location: gnu/packages/bioconductor.scm (gnu packages bioconductor)
Home page: https://bioconductor.org/packages/annotate
Licenses: Artistic License 2.0
Build system: r
Synopsis: Annotation for microarrays
Description:

This package provides R environments for the annotation of microarrays.

r-dearseq 1.22.0
Propagated dependencies: r-compquadform@1.4.4 r-dplyr@1.1.4 r-ggplot2@4.0.1 r-kernsmooth@2.23-26 r-magrittr@2.0.4 r-matrixstats@1.5.0 r-patchwork@1.3.2 r-pbapply@1.7-4 r-reshape2@1.4.5 r-rlang@1.1.6 r-scattermore@1.2 r-statmod@1.5.1 r-survey@4.4-8 r-tibble@3.3.0 r-viridislite@0.4.2
Channel: guix
Location: gnu/packages/bioconductor.scm (gnu packages bioconductor)
Home page: https://github.com/borishejblum/dearseq
Licenses: GPL 2
Build system: r
Synopsis: DEA for RNA-seq data through a robust variance component test
Description:

This is a package for Differential Expression Analysis of RNA-seq data. It features a variance component score test accounting for data heteroscedasticity through precision weights. Perform both gene-wise and gene set analyses, and can deal with repeated or longitudinal data.

r-erma 1.24.1
Propagated dependencies: r-annotationdbi@1.72.0 r-biobase@2.70.0 r-biocgenerics@0.56.0 r-biocparallel@1.44.0 r-genomeinfodb@1.46.0 r-genomicfiles@1.46.0 r-genomicranges@1.62.0 r-ggplot2@4.0.1 r-homo-sapiens@1.3.1 r-iranges@2.44.0 r-rtracklayer@1.70.0 r-s4vectors@0.48.0 r-shiny@1.11.1 r-summarizedexperiment@1.40.0
Channel: guix
Location: gnu/packages/bioconductor.scm (gnu packages bioconductor)
Home page: https://bioconductor.org/packages/erma
Licenses: Artistic License 2.0
Build system: r
Synopsis: Epigenomic road map adventures
Description:

The epigenomics road map describes locations of epigenetic marks in DNA from a variety of cell types. Of interest are locations of histone modifications, sites of DNA methylation, and regions of accessible chromatin. This package presents a selection of elements of the road map including metadata and outputs of the ChromImpute procedure applied to ENCODE cell lines by Ernst and Kellis.

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