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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-msbackendmassbank 1.18.2
Propagated dependencies: r-spectra@1.20.0 r-s4vectors@0.48.0 r-protgenerics@1.42.0 r-mscoreutils@1.21.0 r-iranges@2.44.0 r-dbi@1.2.3 r-data-table@1.17.8 r-biocparallel@1.44.0
Channel: guix-bioc
Location: guix-bioc/packages/m.scm (guix-bioc packages m)
Home page: https://github.com/RforMassSpectrometry/MsBackendMassbank
Licenses: Artistic License 2.0
Build system: r
Synopsis: Mass Spectrometry Data Backend for MassBank record Files
Description:

Mass spectrometry (MS) data backend supporting import and export of MS/MS library spectra from MassBank record files. Different backends are available that allow handling of data in plain MassBank text file format or allow also to interact directly with MassBank SQL databases. Objects from this package are supposed to be used with the Spectra Bioconductor package. This package thus adds MassBank support to the Spectra package.

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

r-mirna20cdf 2.18.0
Propagated dependencies: r-annotationdbi@1.72.0
Channel: guix-bioc
Location: guix-bioc/packages/m.scm (guix-bioc packages m)
Home page: https://bioconductor.org/packages/mirna20cdf
Licenses: LGPL 2.0+
Build system: r
Synopsis: mirna20cdf
Description:

This package provides a package containing an environment representing the miRNA-2_0.cdf file.

r-metacyto 1.32.0
Propagated dependencies: r-tidyr@1.3.1 r-metafor@4.8-0 r-ggplot2@4.0.1 r-flowsom@2.18.0 r-flowcore@2.22.0 r-fastcluster@1.3.0 r-cluster@2.1.8.1
Channel: guix-bioc
Location: guix-bioc/packages/m.scm (guix-bioc packages m)
Home page: https://bioconductor.org/packages/MetaCyto
Licenses: GPL 2+
Build system: r
Synopsis: MetaCyto: A package for meta-analysis of cytometry data
Description:

This package provides functions for preprocessing, automated gating and meta-analysis of cytometry data. It also provides functions that facilitate the collection of cytometry data from the ImmPort database.

r-msa2dist 1.14.0
Propagated dependencies: r-tidyr@1.3.1 r-tibble@3.3.0 r-stringr@1.6.0 r-stringi@1.8.7 r-seqinr@4.2-36 r-rlang@1.1.6 r-rcppthread@2.2.0 r-rcpp@1.1.0 r-pwalign@1.6.0 r-iranges@2.44.0 r-genomicranges@1.62.0 r-foreach@1.5.2 r-dplyr@1.1.4 r-doparallel@1.0.17 r-biostrings@2.78.0 r-ape@5.8-1
Channel: guix-bioc
Location: guix-bioc/packages/m.scm (guix-bioc packages m)
Home page: https://gitlab.gwdg.de/mpievolbio-it/MSA2dist
Licenses: FSDG-compatible
Build system: r
Synopsis: MSA2dist calculates pairwise distances between all sequences of a DNAStringSet or a AAStringSet using a custom score matrix and conducts codon based analysis
Description:

MSA2dist calculates pairwise distances between all sequences of a DNAStringSet or a AAStringSet using a custom score matrix and conducts codon based analysis. It uses scoring matrices to be used in these pairwise distance calculations which can be adapted to any scoring for DNA or AA characters. E.g. by using literal distances MSA2dist calculates pairwise IUPAC distances. DNAStringSet alignments can be analysed as codon alignments to look for synonymous and nonsynonymous substitutions (dN/dS) in a parallelised fashion using a variety of substitution models. Non-aligned coding sequences can be directly used to construct pairwise codon alignments (global/local) and calculate dN/dS without any external dependencies.

r-mspuritydata 1.38.0
Channel: guix-bioc
Location: guix-bioc/packages/m.scm (guix-bioc packages m)
Home page: https://bioconductor.org/packages/msPurityData
Licenses: GPL 2+
Build system: r
Synopsis: Fragmentation spectral libraries and data to test the msPurity package
Description:

Fragmentation spectral libraries and data to test the msPurity package.

r-mirbaseconverter 1.34.0
Channel: guix-bioc
Location: guix-bioc/packages/m.scm (guix-bioc packages m)
Home page: https://github.com/taoshengxu/miRBaseConverter
Licenses: GPL 2+
Build system: r
Synopsis: comprehensive and high-efficiency tool for converting and retrieving the information of miRNAs in different miRBase versions
Description:

This package provides a comprehensive tool for converting and retrieving the miRNA Name, Accession, Sequence, Version, History and Family information in different miRBase versions. It can process a huge number of miRNAs in a short time without other depends.

r-moexexonprobesetlocation 1.15.0
Propagated dependencies: r-annotationdbi@1.72.0
Channel: guix-bioc
Location: guix-bioc/packages/m.scm (guix-bioc packages m)
Home page: https://bioconductor.org/packages/MoExExonProbesetLocation
Licenses: LGPL 2.0+
Build system: r
Synopsis: Probe sequence data for microarrays of type MoEx
Description:

This package was automatically created by package AnnotationForge version 1.7.17. The exon-level probeset genome location was retrieved from Netaffx using AffyCompatible.

r-mgu74bcdf 2.18.0
Propagated dependencies: r-annotationdbi@1.72.0
Channel: guix-bioc
Location: guix-bioc/packages/m.scm (guix-bioc packages m)
Home page: https://bioconductor.org/packages/mgu74bcdf
Licenses: LGPL 2.0+
Build system: r
Synopsis: mgu74bcdf
Description:

This package provides a package containing an environment representing the MG_U74B.cdf file.

r-magar 1.18.0
Propagated dependencies: r-upsetr@1.4.0 r-snpstats@1.60.0 r-rnbeads-hg38@1.42.1 r-rnbeads-hg19@1.42.0 r-rnbeads@2.28.0 r-rjson@0.2.23 r-reshape2@1.4.5 r-plyr@1.8.9 r-jsonlite@2.0.0 r-impute@1.84.0 r-igraph@2.2.1 r-hdf5array@1.38.0 r-ff@4.5.2 r-doparallel@1.0.17 r-data-table@1.17.8 r-crlmm@1.68.0 r-bigstatsr@1.6.2 r-argparse@2.3.1
Channel: guix-bioc
Location: guix-bioc/packages/m.scm (guix-bioc packages m)
Home page: https://github.com/MPIIComputationalEpigenetics/MAGAR
Licenses: GPL 3
Build system: r
Synopsis: MAGAR: R-package to compute methylation Quantitative Trait Loci (methQTL) from DNA methylation and genotyping data
Description:

"Methylation-Aware Genotype Association in R" (MAGAR) computes methQTL from DNA methylation and genotyping data from matched samples. MAGAR uses a linear modeling stragety to call CpGs/SNPs that are methQTLs. MAGAR accounts for the local correlation structure of CpGs.

r-mumosa 1.18.0
Propagated dependencies: r-uwot@0.2.4 r-summarizedexperiment@1.40.0 r-singlecellexperiment@1.32.0 r-scuttle@1.20.0 r-scran@1.38.0 r-scaledmatrix@1.18.0 r-s4vectors@0.48.0 r-metapod@1.18.0 r-matrix@1.7-4 r-iranges@2.44.0 r-igraph@2.2.1 r-delayedmatrixstats@1.32.0 r-delayedarray@0.36.0 r-biocsingular@1.26.1 r-biocparallel@1.44.0 r-biocneighbors@2.4.0 r-biocgenerics@0.56.0 r-beachmat@2.26.0 r-batchelor@1.26.0
Channel: guix-bioc
Location: guix-bioc/packages/m.scm (guix-bioc packages m)
Home page: http://bioconductor.org/packages/mumosa
Licenses: GPL 3
Build system: r
Synopsis: Multi-Modal Single-Cell Analysis Methods
Description:

Assorted utilities for multi-modal analyses of single-cell datasets. Includes functions to combine multiple modalities for downstream analysis, perform MNN-based batch correction across multiple modalities, and to compute correlations between assay values for different modalities.

r-mouse430a2cdf 2.18.0
Propagated dependencies: r-annotationdbi@1.72.0
Channel: guix-bioc
Location: guix-bioc/packages/m.scm (guix-bioc packages m)
Home page: https://bioconductor.org/packages/mouse430a2cdf
Licenses: LGPL 2.0+
Build system: r
Synopsis: mouse430a2cdf
Description:

This package provides a package containing an environment representing the Mouse430A_2.cdf file.

r-mouse4302probe 2.18.0
Propagated dependencies: r-annotationdbi@1.72.0
Channel: guix-bioc
Location: guix-bioc/packages/m.scm (guix-bioc packages m)
Home page: https://bioconductor.org/packages/mouse4302probe
Licenses: LGPL 2.0+
Build system: r
Synopsis: Probe sequence data for microarrays of type mouse4302
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 Mouse430\_2\_probe\_tab.

r-mirnatap-db 0.99.10
Propagated dependencies: r-rsqlite@2.4.4 r-mirnatap@1.44.0 r-dbi@1.2.3 r-annotationdbi@1.72.0
Channel: guix-bioc
Location: guix-bioc/packages/m.scm (guix-bioc packages m)
Home page: https://bioconductor.org/packages/miRNAtap.db
Licenses: GPL 2
Build system: r
Synopsis: Data for miRNAtap
Description:

This package holds the database for miRNAtap.

r-metagxpancreas 1.30.0
Propagated dependencies: r-summarizedexperiment@1.40.0 r-s4vectors@0.48.0 r-impute@1.84.0 r-experimenthub@3.0.0 r-annotationhub@4.0.0
Channel: guix-bioc
Location: guix-bioc/packages/m.scm (guix-bioc packages m)
Home page: https://bioconductor.org/packages/MetaGxPancreas
Licenses: Artistic License 2.0
Build system: r
Synopsis: Transcriptomic Pancreatic Cancer Datasets
Description:

This package provides a collection of pancreatic Cancer transcriptomic datasets that are part of the MetaGxData package compendium. This package contains multiple pancreas cancer datasets that have been downloaded from various resources and turned into SummarizedExperiment objects. The details of how the authors normalized the data can be found in the experiment data section of the objects. Additionally, the location the data was obtained from can be found in the url variables of the experiment data portion of each SE.

r-motifpeeker 1.2.0
Propagated dependencies: r-viridis@0.6.5 r-universalmotif@1.28.0 r-tidyr@1.3.1 r-summarizedexperiment@1.40.0 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-purrr@1.2.0 r-plotly@4.11.0 r-memes@1.18.0 r-iranges@2.44.0 r-htmlwidgets@1.6.4 r-htmltools@0.5.8.1 r-heatmaply@1.6.0 r-ggplot2@4.0.1 r-genomicranges@1.62.0 r-genomicalignments@1.46.0 r-dt@0.34.0 r-dplyr@1.1.4 r-bsgenome@1.78.0 r-biostrings@2.78.0 r-biocparallel@1.44.0 r-biocfilecache@3.0.0
Channel: guix-bioc
Location: guix-bioc/packages/m.scm (guix-bioc packages m)
Home page: https://github.com/neurogenomics/MotifPeeker
Licenses: GPL 3+
Build system: r
Synopsis: Benchmarking Epigenomic Profiling Methods Using Motif Enrichment
Description:

MotifPeeker is used to compare and analyse datasets from epigenomic profiling methods with motif enrichment as the key benchmark. The package outputs an HTML report consisting of three sections: (1. General Metrics) Overview of peaks-related general metrics for the datasets (FRiP scores, peak widths and motif-summit distances). (2. Known Motif Enrichment Analysis) Statistics for the frequency of user-provided motifs enriched in the datasets. (3. De-Novo Motif Enrichment Analysis) Statistics for the frequency of de-novo discovered motifs enriched in the datasets and compared with known motifs.

r-mgug4122a-db 3.2.3
Propagated dependencies: r-org-mm-eg-db@3.22.0 r-annotationdbi@1.72.0
Channel: guix-bioc
Location: guix-bioc/packages/m.scm (guix-bioc packages m)
Home page: https://bioconductor.org/packages/mgug4122a.db
Licenses: Artistic License 2.0
Build system: r
Synopsis: Agilent "Mouse Genome, Whole" annotation data (chip mgug4122a)
Description:

Agilent "Mouse Genome, Whole" annotation data (chip mgug4122a) assembled using data from public repositories.

r-microbiomeprofiler 1.16.0
Propagated dependencies: r-yulab-utils@0.2.1 r-shinywidgets@0.9.0 r-shinycustomloader@0.9.0 r-shiny@1.11.1 r-magrittr@2.0.4 r-htmltools@0.5.8.1 r-gson@0.1.0 r-golem@0.5.1 r-ggplot2@4.0.1 r-enrichplot@1.30.3 r-dt@0.34.0 r-config@0.3.2 r-clusterprofiler@4.18.2
Channel: guix-bioc
Location: guix-bioc/packages/m.scm (guix-bioc packages m)
Home page: https://github.com/YuLab-SMU/MicrobiomeProfiler/
Licenses: GPL 2
Build system: r
Synopsis: An R/shiny package for microbiome functional enrichment analysis
Description:

This is an R/shiny package to perform functional enrichment analysis for microbiome data. This package was based on clusterProfiler. Moreover, MicrobiomeProfiler support KEGG enrichment analysis, COG enrichment analysis, Microbe-Disease association enrichment analysis, Metabo-Pathway analysis.

r-methylimp2 1.6.0
Propagated dependencies: r-summarizedexperiment@1.40.0 r-corpcor@1.6.10 r-champdata@2.42.0 r-biocparallel@1.44.0
Channel: guix-bioc
Location: guix-bioc/packages/m.scm (guix-bioc packages m)
Home page: https://github.com/annaplaksienko/methyLImp2
Licenses: GPL 3
Build system: r
Synopsis: Missing value estimation of DNA methylation data
Description:

This package allows to estimate missing values in DNA methylation data. methyLImp method is based on linear regression since methylation levels show a high degree of inter-sample correlation. Implementation is parallelised over chromosomes since probes on different chromosomes are usually independent. Mini-batch approach to reduce the runtime in case of large number of samples is available.

r-multicrispr 1.20.0
Propagated dependencies: r-tidyselect@1.2.1 r-tidyr@1.3.1 r-stringi@1.8.7 r-seqinfo@1.0.0 r-rtracklayer@1.70.0 r-reticulate@1.44.1 r-rbowtie@1.50.0 r-plyranges@1.30.1 r-magrittr@2.0.4 r-karyoploter@1.36.0 r-ggplot2@4.0.1 r-genomicranges@1.62.0 r-genomicfeatures@1.62.0 r-data-table@1.17.8 r-crisprseek@1.50.0 r-bsgenome@1.78.0 r-biostrings@2.78.0 r-biocgenerics@0.56.0
Channel: guix-bioc
Location: guix-bioc/packages/m.scm (guix-bioc packages m)
Home page: https://github.com/bhagwataditya/multicrispr
Licenses: GPL 2
Build system: r
Synopsis: Multi-locus multi-purpose Crispr/Cas design
Description:

This package is for designing Crispr/Cas9 and Prime Editing experiments. It contains functions to (1) define and transform genomic targets, (2) find spacers (4) count offtarget (mis)matches, and (5) compute Doench2016/2014 targeting efficiency. Care has been taken for multicrispr to scale well towards large target sets, enabling the design of large Crispr/Cas9 libraries.

r-metascope 1.10.0
Propagated dependencies: r-tidyr@1.3.1 r-tibble@3.3.0 r-taxonomizr@0.11.1 r-summarizedexperiment@1.40.0 r-stringr@1.6.0 r-s4vectors@0.48.0 r-rsamtools@2.26.0 r-rlang@1.1.6 r-readr@2.1.6 r-rbowtie2@2.16.0 r-multiassayexperiment@1.36.1 r-matrix@1.7-4 r-magrittr@2.0.4 r-ggplot2@4.0.1 r-dplyr@1.1.4 r-data-table@1.17.8 r-biostrings@2.78.0 r-biocfilecache@3.0.0
Channel: guix-bioc
Location: guix-bioc/packages/m.scm (guix-bioc packages m)
Home page: https://bioconductor.org/packages/MetaScope
Licenses: GPL 3+
Build system: r
Synopsis: Tools and functions for preprocessing 16S and metagenomic sequencing microbiome data
Description:

This package contains tools and methods for preprocessing microbiome data. Functionality includes library generation, demultiplexing, alignment, and microbe identification. It is in part an R translation of the PathoScope 2.0 pipeline.

r-mu19ksuba-db 3.13.0
Propagated dependencies: r-org-mm-eg-db@3.22.0 r-annotationdbi@1.72.0
Channel: guix-bioc
Location: guix-bioc/packages/m.scm (guix-bioc packages m)
Home page: https://bioconductor.org/packages/mu19ksuba.db
Licenses: Artistic License 2.0
Build system: r
Synopsis: Affymetrix Affymetrix Mu19KsubA Array annotation data (chip mu19ksuba)
Description:

Affymetrix Affymetrix Mu19KsubA Array annotation data (chip mu19ksuba) assembled using data from public repositories.

r-mbcb 1.64.0
Propagated dependencies: r-tcltk2@1.6.1 r-preprocesscore@1.72.0
Channel: guix-bioc
Location: guix-bioc/packages/m.scm (guix-bioc packages m)
Home page: https://qbrc.swmed.edu/
Licenses: FSDG-compatible
Build system: r
Synopsis: MBCB (Model-based Background Correction for Beadarray)
Description:

This package provides a model-based background correction method, which incorporates the negative control beads to pre-process Illumina BeadArray data.

r-moonlight2r 1.8.1
Propagated dependencies: r-withr@3.0.2 r-tidyr@1.3.1 r-tidyheatmap@1.13.1 r-tibble@3.3.0 r-stringr@1.6.0 r-seqminer@9.7 r-rtracklayer@1.70.0 r-rlang@1.1.6 r-rismed@2.3.0 r-readr@2.1.6 r-rcolorbrewer@1.1-3 r-randomforest@4.7-1.2 r-qpdf@1.4.1 r-purrr@1.2.0 r-parmigene@1.1.1 r-org-hs-eg-db@3.22.0 r-magrittr@2.0.4 r-hiver@0.4.0 r-gplots@3.2.0 r-ggplot2@4.0.1 r-geoquery@2.78.0 r-genomicranges@1.62.0 r-fuzzyjoin@0.1.6.1 r-foreach@1.5.2 r-experimenthub@3.0.0 r-epimix@1.12.0 r-easypubmed@3.1.6 r-dplyr@1.1.4 r-dose@4.4.0 r-doparallel@1.0.17 r-data-table@1.17.8 r-complexheatmap@2.26.0 r-clusterprofiler@4.18.2 r-circlize@0.4.16 r-biocgenerics@0.56.0 r-biobase@2.70.0 r-annotationhub@4.0.0
Channel: guix-bioc
Location: guix-bioc/packages/m.scm (guix-bioc packages m)
Home page: https://github.com/ELELAB/Moonlight2R
Licenses: GPL 3
Build system: r
Synopsis: Identify oncogenes and tumor suppressor genes from omics data
Description:

The understanding of cancer mechanism requires the identification of genes playing a role in the development of the pathology and the characterization of their role (notably oncogenes and tumor suppressors). We present an updated version of the R/bioconductor package called MoonlightR, namely Moonlight2R, which returns a list of candidate driver genes for specific cancer types on the basis of omics data integration. The Moonlight framework contains a primary layer where gene expression data and information about biological processes are integrated to predict genes called oncogenic mediators, divided into putative tumor suppressors and putative oncogenes. This is done through functional enrichment analyses, gene regulatory networks and upstream regulator analyses to score the importance of well-known biological processes with respect to the studied cancer type. By evaluating the effect of the oncogenic mediators on biological processes or through random forests, the primary layer predicts two putative roles for the oncogenic mediators: i) tumor suppressor genes (TSGs) and ii) oncogenes (OCGs). As gene expression data alone is not enough to explain the deregulation of the genes, a second layer of evidence is needed. We have automated the integration of a secondary mutational layer through new functionalities in Moonlight2R. These functionalities analyze mutations in the cancer cohort and classifies these into driver and passenger mutations using the driver mutation prediction tool, CScape-somatic. Those oncogenic mediators with at least one driver mutation are retained as the driver genes. As a consequence, this methodology does not only identify genes playing a dual role (e.g. TSG in one cancer type and OCG in another) but also helps in elucidating the biological processes underlying their specific roles. In particular, Moonlight2R can be used to discover OCGs and TSGs in the same cancer type. This may for instance help in answering the question whether some genes change role between early stages (I, II) and late stages (III, IV). In the future, this analysis could be useful to determine the causes of different resistances to chemotherapeutic treatments. An additional mechanistic layer evaluates if there are mutations affecting the protein stability of the transcription factors (TFs) of the TSGs and OCGs, as that may have an effect on the expression of the genes.

Total results: 2909