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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-eatonetalchipseq 0.48.0
Propagated dependencies: r-shortread@1.68.0 r-rtracklayer@1.70.0 r-genomicranges@1.62.0
Channel: guix-bioc
Location: guix-bioc/packages/e.scm (guix-bioc packages e)
Home page: https://bioconductor.org/packages/EatonEtAlChIPseq
Licenses: FSDG-compatible
Build system: r
Synopsis: ChIP-seq data of ORC-binding sites in Yeast excerpted from Eaton et al. 2010
Description:

ChIP-seq analysis subset from "Conserved nucleosome positioning defines replication origins" (PMID 20351051).

r-easyreporting 1.22.0
Propagated dependencies: r-shiny@1.11.1 r-rmarkdown@2.30 r-rlang@1.1.6
Channel: guix-bioc
Location: guix-bioc/packages/e.scm (guix-bioc packages e)
Home page: https://bioconductor.org/packages/easyreporting
Licenses: Artistic License 2.0
Build system: r
Synopsis: Helps creating report for improving Reproducible Computational Research
Description:

An S4 class for facilitating the automated creation of rmarkdown files inside other packages/software even without knowing rmarkdown language. Best if implemented in functions as "recursive" style programming.

r-estrogen 1.56.0
Channel: guix-bioc
Location: guix-bioc/packages/e.scm (guix-bioc packages e)
Home page: https://bioconductor.org/packages/estrogen
Licenses: LGPL 2.0+
Build system: r
Synopsis: Microarray dataset that can be used as example for 2x2 factorial designs
Description:

Data from 8 Affymetrix genechips, looking at a 2x2 factorial design (with 2 repeats per level).

r-ecoliprobe 2.18.0
Propagated dependencies: r-annotationdbi@1.72.0
Channel: guix-bioc
Location: guix-bioc/packages/e.scm (guix-bioc packages e)
Home page: https://bioconductor.org/packages/ecoliprobe
Licenses: LGPL 2.0+
Build system: r
Synopsis: Probe sequence data for microarrays of type ecoli
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 E\_coli\_probe\_tab.

r-epimutacionsdata 1.14.0
Channel: guix-bioc
Location: guix-bioc/packages/e.scm (guix-bioc packages e)
Home page: https://github.com/LeireAbarrategui/epimutacionsData
Licenses: Expat
Build system: r
Synopsis: Data for epimutacions package
Description:

This package includes the data necessary to run functions and examples in epimutacions package. Collection of DNA methylation data. The package contains 2 datasets: (1) Control ( GEO: GSE104812), (GEO: GSE97362) case samples; and (2) reference panel (GEO: GSE127824). It also contains candidate regions to be epimutations in 450k methylation arrays.

r-epigrahmm 1.18.0
Propagated dependencies: r-summarizedexperiment@1.40.0 r-seqinfo@1.0.0 r-scales@1.4.0 r-s4vectors@0.48.0 r-rtracklayer@1.70.0 r-rsamtools@2.26.0 r-rhdf5lib@1.32.0 r-rhdf5@2.54.0 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-pheatmap@1.0.13 r-matrix@1.7-4 r-mass@7.3-65 r-magrittr@2.0.4 r-limma@3.66.0 r-iranges@2.44.0 r-greylistchip@1.42.0 r-ggpubr@0.6.2 r-ggplot2@4.0.1 r-genomicranges@1.62.0 r-data-table@1.17.8 r-csaw@1.44.0 r-bamsignals@1.42.0
Channel: guix-bioc
Location: guix-bioc/packages/e.scm (guix-bioc packages e)
Home page: https://bioconductor.org/packages/epigraHMM
Licenses: Expat
Build system: r
Synopsis: Epigenomic R-based analysis with hidden Markov models
Description:

epigraHMM provides a set of tools for the analysis of epigenomic data based on hidden Markov Models. It contains two separate peak callers, one for consensus peaks from biological or technical replicates, and one for differential peaks from multi-replicate multi-condition experiments. In differential peak calling, epigraHMM provides window-specific posterior probabilities associated with every possible combinatorial pattern of read enrichment across conditions.

r-epiregulon-extra 1.6.0
Propagated dependencies: r-summarizedexperiment@1.40.0 r-singlecellexperiment@1.32.0 r-scran@1.38.0 r-scater@1.38.0 r-scales@1.4.0 r-reshape2@1.4.5 r-patchwork@1.3.2 r-matrix@1.7-4 r-igraph@2.2.1 r-ggraph@2.2.2 r-ggplot2@4.0.1 r-complexheatmap@2.26.0 r-clusterprofiler@4.18.2 r-circlize@0.4.16 r-checkmate@2.3.3
Channel: guix-bioc
Location: guix-bioc/packages/e.scm (guix-bioc packages e)
Home page: https://github.com/xiaosaiyao/epiregulon.extra/
Licenses: Expat
Build system: r
Synopsis: Companion package to epiregulon with additional plotting, differential and graph functions
Description:

Gene regulatory networks model the underlying gene regulation hierarchies that drive gene expression and observed phenotypes. Epiregulon infers TF activity in single cells by constructing a gene regulatory network (regulons). This is achieved through integration of scATAC-seq and scRNA-seq data and incorporation of public bulk TF ChIP-seq data. Links between regulatory elements and their target genes are established by computing correlations between chromatin accessibility and gene expressions.

r-emdomics 2.40.0
Propagated dependencies: r-preprocesscore@1.72.0 r-matrixstats@1.5.0 r-ggplot2@4.0.1 r-emdist@0.3-3 r-cdft@1.2 r-biocparallel@1.44.0
Channel: guix-bioc
Location: guix-bioc/packages/e.scm (guix-bioc packages e)
Home page: https://bioconductor.org/packages/EMDomics
Licenses: Expat
Build system: r
Synopsis: Earth Mover's Distance for Differential Analysis of Genomics Data
Description:

The EMDomics algorithm is used to perform a supervised multi-class analysis to measure the magnitude and statistical significance of observed continuous genomics data between groups. Usually the data will be gene expression values from array-based or sequence-based experiments, but data from other types of experiments can also be analyzed (e.g. copy number variation). Traditional methods like Significance Analysis of Microarrays (SAM) and Linear Models for Microarray Data (LIMMA) use significance tests based on summary statistics (mean and standard deviation) of the distributions. This approach lacks power to identify expression differences between groups that show high levels of intra-group heterogeneity. The Earth Mover's Distance (EMD) algorithm instead computes the "work" needed to transform one distribution into another, thus providing a metric of the overall difference in shape between two distributions. Permutation of sample labels is used to generate q-values for the observed EMD scores. This package also incorporates the Komolgorov-Smirnov (K-S) test and the Cramer von Mises test (CVM), which are both common distribution comparison tests.

r-ecolik12-db0 3.22.0
Propagated dependencies: r-annotationdbi@1.72.0
Channel: guix-bioc
Location: guix-bioc/packages/e.scm (guix-bioc packages e)
Home page: https://bioconductor.org/packages/ecoliK12.db0
Licenses: Artistic License 2.0
Build system: r
Synopsis: Base Level Annotation databases for E coli K12 Strain
Description:

Base annotation databases for E coli K12 Strain, intended ONLY to be used by AnnotationDbi to produce regular annotation packages.

r-esatac 1.32.0
Propagated dependencies: r-venndiagram@1.7.3 r-tfbstools@1.48.0 r-shortread@1.68.0 r-seqinfo@1.0.0 r-s4vectors@0.48.0 r-rtracklayer@1.70.0 r-rsamtools@2.26.0 r-rmarkdown@2.30 r-rjava@1.0-11 r-rcpp@1.1.0 r-rbowtie2@2.16.0 r-r-utils@2.13.0 r-pipeframe@1.26.0 r-motifmatchr@1.32.0 r-magrittr@2.0.4 r-knitr@1.50 r-jaspar2018@1.1.1 r-iranges@2.44.0 r-igraph@2.2.1 r-ggplot2@4.0.1 r-genomicranges@1.62.0 r-genomicfeatures@1.62.0 r-genomicalignments@1.46.0 r-digest@0.6.39 r-corrplot@0.95 r-clusterprofiler@4.18.2 r-chipseeker@1.46.1 r-bsgenome@1.78.0 r-biostrings@2.78.0 r-biocmanager@1.30.27 r-biocgenerics@0.56.0 r-annotationdbi@1.72.0
Channel: guix-bioc
Location: guix-bioc/packages/e.scm (guix-bioc packages e)
Home page: https://github.com/wzthu/esATAC
Licenses: GPL 3 FSDG-compatible
Build system: r
Synopsis: An Easy-to-use Systematic pipeline for ATACseq data analysis
Description:

This package provides a framework and complete preset pipeline for quantification and analysis of ATAC-seq Reads. It covers raw sequencing reads preprocessing (FASTQ files), reads alignment (Rbowtie2), aligned reads file operations (SAM, BAM, and BED files), peak calling (F-seq), genome annotations (Motif, GO, SNP analysis) and quality control report. The package is managed by dataflow graph. It is easy for user to pass variables seamlessly between processes and understand the workflow. Users can process FASTQ files through end-to-end preset pipeline which produces a pretty HTML report for quality control and preliminary statistical results, or customize workflow starting from any intermediate stages with esATAC functions easily and flexibly.

r-egsea 1.38.0
Propagated dependencies: r-topgo@2.62.0 r-stringi@1.8.7 r-safe@3.50.0 r-rcolorbrewer@1.1-3 r-plotly@4.11.0 r-pathview@1.50.0 r-padog@1.52.0 r-org-rn-eg-db@3.22.0 r-org-mm-eg-db@3.22.0 r-org-hs-eg-db@3.22.0 r-metap@1.12 r-limma@3.66.0 r-hwriter@1.3.2.1 r-htmlwidgets@1.6.4 r-htmlutils@0.1.9 r-gsva@2.4.1 r-gplots@3.2.0 r-globaltest@5.64.0 r-ggplot2@4.0.1 r-gage@2.60.0 r-egseadata@1.38.0 r-edger@4.8.0 r-dt@0.34.0 r-biobase@2.70.0 r-annotationdbi@1.72.0
Channel: guix-bioc
Location: guix-bioc/packages/e.scm (guix-bioc packages e)
Home page: https://bioconductor.org/packages/EGSEA
Licenses: GPL 3
Build system: r
Synopsis: Ensemble of Gene Set Enrichment Analyses
Description:

This package implements the Ensemble of Gene Set Enrichment Analyses (EGSEA) method for gene set testing. EGSEA algorithm utilizes the analysis results of twelve prominent GSE algorithms in the literature to calculate collective significance scores for each gene set.

r-ensdb-rnorvegicus-v79 2.99.0
Propagated dependencies: r-ensembldb@2.34.0
Channel: guix-bioc
Location: guix-bioc/packages/e.scm (guix-bioc packages e)
Home page: https://bioconductor.org/packages/EnsDb.Rnorvegicus.v79
Licenses: Artistic License 2.0
Build system: r
Synopsis: Ensembl based annotation package
Description:

Exposes an annotation databases generated from Ensembl.

r-etec16s 1.38.0
Propagated dependencies: r-metagenomeseq@1.52.0 r-biobase@2.70.0
Channel: guix-bioc
Location: guix-bioc/packages/e.scm (guix-bioc packages e)
Home page: https://bioconductor.org/packages/etec16s
Licenses: Artistic License 2.0
Build system: r
Synopsis: Individual-specific changes in the human gut microbiota after challenge with enterotoxigenic Escherichia coli and subsequent ciprofloxacin treatment
Description:

16S rRNA gene sequencing data to study changes in the faecal microbiota of 12 volunteers during a human challenge study with ETEC (H10407) and subsequent treatment with ciprofloxacin.

r-epialleler 1.18.0
Propagated dependencies: r-rhtslib@3.6.0 r-rcpp@1.1.0 r-genomicranges@1.62.0 r-data-table@1.17.8 r-biocgenerics@0.56.0 r-bh@1.87.0-1
Channel: guix-bioc
Location: guix-bioc/packages/e.scm (guix-bioc packages e)
Home page: https://github.com/BBCG/epialleleR
Licenses: Artistic License 2.0
Build system: r
Synopsis: Fast, Epiallele-Aware Methylation Caller and Reporter
Description:

Epialleles are specific DNA methylation patterns that are mitotically and/or meiotically inherited. This package calls and reports cytosine methylation as well as frequencies of hypermethylated epialleles at the level of genomic regions or individual cytosines in next-generation sequencing data using binary alignment map (BAM) files as an input. Among other things, this package can also extract and visualise methylation patterns and assess allele specificity of methylation.

r-escher 1.10.0
Propagated dependencies: r-summarizedexperiment@1.40.0 r-spatialexperiment@1.20.0 r-singlecellexperiment@1.32.0 r-rlang@1.1.6 r-ggplot2@4.0.1
Channel: guix-bioc
Location: guix-bioc/packages/e.scm (guix-bioc packages e)
Home page: https://github.com/boyiguo1/escheR
Licenses: Expat
Build system: r
Synopsis: Unified multi-dimensional visualizations with Gestalt principles
Description:

The creation of effective visualizations is a fundamental component of data analysis. In biomedical research, new challenges are emerging to visualize multi-dimensional data in a 2D space, but current data visualization tools have limited capabilities. To address this problem, we leverage Gestalt principles to improve the design and interpretability of multi-dimensional data in 2D data visualizations, layering aesthetics to display multiple variables. The proposed visualization can be applied to spatially-resolved transcriptomics data, but also broadly to data visualized in 2D space, such as embedding visualizations. We provide this open source R package escheR, which is built off of the state-of-the-art ggplot2 visualization framework and can be seamlessly integrated into genomics toolboxes and workflows.

r-edge 2.42.0
Propagated dependencies: r-sva@3.58.0 r-qvalue@2.42.0 r-mass@7.3-65 r-biobase@2.70.0
Channel: guix-bioc
Location: guix-bioc/packages/e.scm (guix-bioc packages e)
Home page: https://github.com/jdstorey/edge
Licenses: Expat
Build system: r
Synopsis: Extraction of Differential Gene Expression
Description:

The edge package implements methods for carrying out differential expression analyses of genome-wide gene expression studies. Significance testing using the optimal discovery procedure and generalized likelihood ratio tests (equivalent to F-tests and t-tests) are implemented for general study designs. Special functions are available to facilitate the analysis of common study designs, including time course experiments. Other packages such as sva and qvalue are integrated in edge to provide a wide range of tools for gene expression analysis.

r-epicv2manifest 0.99.7
Propagated dependencies: r-annotationhub@4.0.0
Channel: guix-bioc
Location: guix-bioc/packages/e.scm (guix-bioc packages e)
Home page: https://bioconductor.org/packages/EPICv2manifest
Licenses: Artistic License 2.0
Build system: r
Synopsis: Illumina Infinium MethylationEPIC v2.0 extended manifest from Peters et al. 2024
Description:

This package provides a data.frame containing an extended probe manifest for the Illumina Infinium Methylation v2.0 Kit. Contains the complete manifest from the Illumina-provided EPIC-8v2-0_EA.csv, plus additional probewise information described in Peters et al. (2024).

r-ebsea 1.38.0
Propagated dependencies: r-empiricalbrownsmethod@1.38.0 r-deseq2@1.50.2
Channel: guix-bioc
Location: guix-bioc/packages/e.scm (guix-bioc packages e)
Home page: https://bioconductor.org/packages/EBSEA
Licenses: GPL 2
Build system: r
Synopsis: Exon Based Strategy for Expression Analysis of genes
Description:

Calculates differential expression of genes based on exon counts of genes obtained from RNA-seq sequencing data.

r-epiregulon 2.0.2
Propagated dependencies: r-summarizedexperiment@1.40.0 r-singlecellexperiment@1.32.0 r-scuttle@1.20.0 r-scrapper@1.4.0 r-scran@1.38.0 r-s4vectors@0.48.0 r-rcpp@1.1.0 r-motifmatchr@1.32.0 r-matrix@1.7-4 r-lifecycle@1.0.4 r-iranges@2.44.0 r-genomicranges@1.62.0 r-genomeinfodb@1.46.0 r-experimenthub@3.0.0 r-entropy@1.3.2 r-checkmate@2.3.3 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-biocparallel@1.44.0 r-annotationhub@4.0.0 r-annotationhub@4.0.0
Channel: guix-bioc
Location: guix-bioc/packages/e.scm (guix-bioc packages e)
Home page: https://github.com/xiaosaiyao/epiregulon/
Licenses: Expat
Build system: r
Synopsis: Gene regulatory network inference from single cell epigenomic data
Description:

Gene regulatory networks model the underlying gene regulation hierarchies that drive gene expression and observed phenotypes. Epiregulon infers TF activity in single cells by constructing a gene regulatory network (regulons). This is achieved through integration of scATAC-seq and scRNA-seq data and incorporation of public bulk TF ChIP-seq data. Links between regulatory elements and their target genes are established by computing correlations between chromatin accessibility and gene expressions.

r-epivizrdata 1.38.0
Propagated dependencies: r-summarizedexperiment@1.40.0 r-seqinfo@1.0.0 r-s4vectors@0.48.0 r-organismdbi@1.52.0 r-iranges@2.44.0 r-genomicranges@1.62.0 r-genomicfeatures@1.62.0 r-epivizrserver@1.38.0 r-ensembldb@2.34.0 r-biobase@2.70.0
Channel: guix-bioc
Location: guix-bioc/packages/e.scm (guix-bioc packages e)
Home page: http://epiviz.github.io
Licenses: Expat
Build system: r
Synopsis: Data Management API for epiviz interactive visualization app
Description:

Serve data from Bioconductor Objects through a WebSocket connection.

r-ewce 1.18.0
Propagated dependencies: r-summarizedexperiment@1.40.0 r-stringr@1.6.0 r-singlecellexperiment@1.32.0 r-rnomni@1.0.1.2 r-reshape2@1.4.5 r-orthogene@1.16.1 r-matrix@1.7-4 r-limma@3.66.0 r-hgnchelper@0.8.15 r-ggplot2@4.0.1 r-ewcedata@1.18.0 r-dplyr@1.1.4 r-delayedarray@0.36.0 r-data-table@1.17.8 r-biocparallel@1.44.0
Channel: guix-bioc
Location: guix-bioc/packages/e.scm (guix-bioc packages e)
Home page: https://github.com/NathanSkene/EWCE
Licenses: GPL 3
Build system: r
Synopsis: Expression Weighted Celltype Enrichment
Description:

Used to determine which cell types are enriched within gene lists. The package provides tools for testing enrichments within simple gene lists (such as human disease associated genes) and those resulting from differential expression studies. The package does not depend upon any particular Single Cell Transcriptome dataset and user defined datasets can be loaded in and used in the analyses.

r-epistasisga 1.12.0
Propagated dependencies: r-survival@3.8-3 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-qgraph@1.9.8 r-matrixstats@1.5.0 r-igraph@2.2.1 r-ggplot2@4.0.1 r-data-table@1.17.8 r-biocparallel@1.44.0 r-bigmemory@4.6.4 r-bh@1.87.0-1 r-batchtools@0.9.18
Channel: guix-bioc
Location: guix-bioc/packages/e.scm (guix-bioc packages e)
Home page: https://github.com/mnodzenski/epistasisGA
Licenses: GPL 3
Build system: r
Synopsis: An R package to identify multi-snp effects in nuclear family studies using the GADGETS method
Description:

This package runs the GADGETS method to identify epistatic effects in nuclear family studies. It also provides functions for permutation-based inference and graphical visualization of the results.

r-eir 1.50.0
Propagated dependencies: r-snowfall@1.84-6.3 r-snow@0.4-4 r-runit@0.4.33.1 r-rcurl@1.98-1.17 r-rcppannoy@0.0.22 r-digest@0.6.39 r-dbi@1.2.3 r-chemminer@3.62.0 r-biocgenerics@0.56.0
Channel: guix-bioc
Location: guix-bioc/packages/e.scm (guix-bioc packages e)
Home page: https://github.com/girke-lab/eiR
Licenses: Artistic License 2.0
Build system: r
Synopsis: Accelerated similarity searching of small molecules
Description:

The eiR package provides utilities for accelerated structure similarity searching of very large small molecule data sets using an embedding and indexing approach.

r-ecoli2probe 2.18.0
Propagated dependencies: r-annotationdbi@1.72.0
Channel: guix-bioc
Location: guix-bioc/packages/e.scm (guix-bioc packages e)
Home page: https://bioconductor.org/packages/ecoli2probe
Licenses: LGPL 2.0+
Build system: r
Synopsis: Probe sequence data for microarrays of type ecoli2
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 E\_coli\_2\_probe\_tab.

Total results: 2909