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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:

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-multimodalexperiment 1.10.0
Propagated dependencies: r-s4vectors@0.48.0 r-multiassayexperiment@1.36.1 r-iranges@2.44.0 r-biocgenerics@0.56.0
Channel: guix-bioc
Location: guix-bioc/packages/m.scm (guix-bioc packages m)
Home page: https://bioconductor.org/packages/MultimodalExperiment
Licenses: Artistic License 2.0
Build system: r
Synopsis: Integrative Bulk and Single-Cell Experiment Container
Description:

MultimodalExperiment is an S4 class that integrates bulk and single-cell experiment data; it is optimally storage-efficient, and its methods are exceptionally fast. It effortlessly represents multimodal data of any nature and features normalized experiment, subject, sample, and cell annotations, which are related to underlying biological experiments through maps. Its coordination methods are opt-in and employ database-like join operations internally to deliver fast and flexible management of multimodal data.

r-measurementerror-cor 1.82.0
Channel: guix-bioc
Location: guix-bioc/packages/m.scm (guix-bioc packages m)
Home page: https://bioconductor.org/packages/MeasurementError.cor
Licenses: LGPL 2.0+
Build system: r
Synopsis: Measurement Error model estimate for correlation coefficient
Description:

Two-stage measurement error model for correlation estimation with smaller bias than the usual sample correlation.

r-maaslin3 1.2.0
Channel: guix-bioc
Location: guix-bioc/packages/m.scm (guix-bioc packages m)
Home page: http://huttenhower.sph.harvard.edu/maaslin3
Licenses: Expat
Build system: r
Synopsis: "Refining and extending generalized multivariate linear models for meta-omic association discovery"
Description:

MaAsLin 3 refines and extends generalized multivariate linear models for meta-omicron association discovery. It finds abundance and prevalence associations between microbiome meta-omics features and complex metadata in population-scale epidemiological studies. The software includes multiple analysis methods (including support for multiple covariates, repeated measures, and ordered predictors), filtering, normalization, and transform options to customize analysis for your specific study.

r-msbackendmgf 1.18.0
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-biocparallel@1.44.0
Channel: guix-bioc
Location: guix-bioc/packages/m.scm (guix-bioc packages m)
Home page: https://github.com/RforMassSpectrometry/MsBackendMgf
Licenses: Artistic License 2.0
Build system: r
Synopsis: Mass Spectrometry Data Backend for Mascot Generic Format (mgf) Files
Description:

Mass spectrometry (MS) data backend supporting import and export of MS/MS spectra data from Mascot Generic Format (mgf) files. Objects defined in this package are supposed to be used with the Spectra Bioconductor package. This package thus adds mgf file support to the Spectra package.

r-msstatslip 1.16.0
Channel: guix-bioc
Location: guix-bioc/packages/m.scm (guix-bioc packages m)
Home page: https://bioconductor.org/packages/MSstatsLiP
Licenses: Artistic License 2.0
Build system: r
Synopsis: LiP Significance Analysis in shotgun mass spectrometry-based proteomic experiments
Description:

This package provides tools for LiP peptide and protein significance analysis. Provides functions for summarization, estimation of LiP peptide abundance, and detection of changes across conditions. Utilizes functionality across the MSstats family of packages.

r-msstatsconvert 1.20.0
Propagated dependencies: r-stringi@1.8.7 r-rcpp@1.1.0 r-log4r@0.4.4 r-data-table@1.17.8 r-checkmate@2.3.3
Channel: guix-bioc
Location: guix-bioc/packages/m.scm (guix-bioc packages m)
Home page: https://bioconductor.org/packages/MSstatsConvert
Licenses: Artistic License 2.0
Build system: r
Synopsis: Import Data from Various Mass Spectrometry Signal Processing Tools to MSstats Format
Description:

MSstatsConvert provides tools for importing reports of Mass Spectrometry data processing tools into R format suitable for statistical analysis using the MSstats and MSstatsTMT packages.

r-moda 1.36.0
Propagated dependencies: r-wgcna@1.73 r-rcolorbrewer@1.1-3 r-igraph@2.2.1 r-dynamictreecut@1.63-1 r-cluster@2.1.8.1 r-amountain@1.36.0
Channel: guix-bioc
Location: guix-bioc/packages/m.scm (guix-bioc packages m)
Home page: https://bioconductor.org/packages/MODA
Licenses: GPL 2+
Build system: r
Synopsis: MODA: MOdule Differential Analysis for weighted gene co-expression network
Description:

MODA can be used to estimate and construct condition-specific gene co-expression networks, and identify differentially expressed subnetworks as conserved or condition specific modules which are potentially associated with relevant biological processes.

r-metacca 1.38.0
Channel: guix-bioc
Location: guix-bioc/packages/m.scm (guix-bioc packages m)
Home page: https://doi.org/10.1093/bioinformatics/btw052
Licenses: Expat
Build system: r
Synopsis: Summary Statistics-Based Multivariate Meta-Analysis of Genome-Wide Association Studies Using Canonical Correlation Analysis
Description:

metaCCA performs multivariate analysis of a single or multiple GWAS based on univariate regression coefficients. It allows multivariate representation of both phenotype and genotype. metaCCA extends the statistical technique of canonical correlation analysis to the setting where original individual-level records are not available, and employs a covariance shrinkage algorithm to achieve robustness.

r-mistyr 1.18.0
Channel: guix-bioc
Location: guix-bioc/packages/m.scm (guix-bioc packages m)
Home page: https://saezlab.github.io/mistyR/
Licenses: GPL 3
Build system: r
Synopsis: Multiview Intercellular SpaTial modeling framework
Description:

mistyR is an implementation of the Multiview Intercellular SpaTialmodeling framework (MISTy). MISTy is an explainable machine learning framework for knowledge extraction and analysis of single-cell, highly multiplexed, spatially resolved data. MISTy facilitates an in-depth understanding of marker interactions by profiling the intra- and intercellular relationships. MISTy is a flexible framework able to process a custom number of views. Each of these views can describe a different spatial context, i.e., define a relationship among the observed expressions of the markers, such as intracellular regulation or paracrine regulation, but also, the views can also capture cell-type specific relationships, capture relations between functional footprints or focus on relations between different anatomical regions. Each MISTy view is considered as a potential source of variability in the measured marker expressions. Each MISTy view is then analyzed for its contribution to the total expression of each marker and is explained in terms of the interactions with other measurements that led to the observed contribution.

r-mouseagingdata 1.6.0
Propagated dependencies: r-singlecellexperiment@1.32.0 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://github.com/ccb-hms/MouseAgingData
Licenses: Artistic License 2.0
Build system: r
Synopsis: Multi-omics data access for studies investigating the effects of aging
Description:

The MouseAgingData package provides analysis-ready data resources from different studies focused on aging and rejuvenation in mice. The package currently provides two 10x Genomics single-cell RNA-seq datasets. The first study profiled the aging mouse brain measured across 37,089 cells (Ximerakis et al., 2019). The second study investigated parabiosis by profiling a total of 105,329 cells (Ximerakis & Holton et al., 2023). The datasets are provided as SingleCellExperiment objects and provide raw UMI counts and cell metadata.

r-mouse4302cdf 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/mouse4302cdf
Licenses: LGPL 2.0+
Build system: r
Synopsis: mouse4302cdf
Description:

This package provides a package containing an environment representing the Mouse430_2.cdf file.

r-metagene2 1.26.0
Channel: guix-bioc
Location: guix-bioc/packages/m.scm (guix-bioc packages m)
Home page: https://github.com/ArnaudDroitLab/metagene2
Licenses: Artistic License 2.0
Build system: r
Synopsis: package to produce metagene plots
Description:

This package produces metagene plots to compare coverages of sequencing experiments at selected groups of genomic regions. It can be used for such analyses as assessing the binding of DNA-interacting proteins at promoter regions or surveying antisense transcription over the length of a gene. The metagene2 package can manage all aspects of the analysis, from normalization of coverages to plot facetting according to experimental metadata. Bootstraping analysis is used to provide confidence intervals of per-sample mean coverages.

r-msimpute 1.20.0
Dependencies: python@3.11.14
Channel: guix-bioc
Location: guix-bioc/packages/m.scm (guix-bioc packages m)
Home page: https://bioconductor.org/packages/msImpute
Licenses: FSDG-compatible
Build system: r
Synopsis: Imputation of label-free mass spectrometry peptides
Description:

MsImpute is a package for imputation of peptide intensity in proteomics experiments. It additionally contains tools for MAR/MNAR diagnosis and assessment of distortions to the probability distribution of the data post imputation. The missing values are imputed by low-rank approximation of the underlying data matrix if they are MAR (method = "v2"), by Barycenter approach if missingness is MNAR ("v2-mnar"), or by Peptide Identity Propagation (PIP).

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-meshr 2.16.0
Channel: guix-bioc
Location: guix-bioc/packages/m.scm (guix-bioc packages m)
Home page: https://bioconductor.org/packages/meshr
Licenses: Artistic License 2.0
Build system: r
Synopsis: Tools for conducting enrichment analysis of MeSH
Description:

This package provides a set of annotation maps describing the entire MeSH assembled using data from MeSH.

r-mitch 1.22.1
Channel: guix-bioc
Location: guix-bioc/packages/m.scm (guix-bioc packages m)
Home page: https://github.com/markziemann/mitch
Licenses: FSDG-compatible
Build system: r
Synopsis: Multi-Contrast Gene Set Enrichment Analysis
Description:

mitch is an R package for multi-contrast enrichment analysis. At it’s heart, it uses a rank-MANOVA based statistical approach to detect sets of genes that exhibit enrichment in the multidimensional space as compared to the background. The rank-MANOVA concept dates to work by Cox and Mann (https://doi.org/10.1186/1471-2105-13-S16-S12). mitch is useful for pathway analysis of profiling studies with one, two or more contrasts, or in studies with multiple omics profiling, for example proteomic, transcriptomic, epigenomic analysis of the same samples. mitch is perfectly suited for pathway level differential analysis of scRNA-seq data. We have an established routine for pathway enrichment of Infinium Methylation Array data (see vignette). The main strengths of mitch are that it can import datasets easily from many upstream tools and has advanced plotting features to visualise these enrichments.

r-monalisa 1.16.0
Channel: guix-bioc
Location: guix-bioc/packages/m.scm (guix-bioc packages m)
Home page: https://github.com/fmicompbio/monaLisa
Licenses: GPL 3+
Build system: r
Synopsis: Binned Motif Enrichment Analysis and Visualization
Description:

Useful functions to work with sequence motifs in the analysis of genomics data. These include methods to annotate genomic regions or sequences with predicted motif hits and to identify motifs that drive observed changes in accessibility or expression. Functions to produce informative visualizations of the obtained results are also provided.

r-mircompdata 1.40.0
Channel: guix-bioc
Location: guix-bioc/packages/m.scm (guix-bioc packages m)
Home page: https://bioconductor.org/packages/miRcompData
Licenses: GPL 3 FSDG-compatible
Build system: r
Synopsis: Data used in the miRcomp package
Description:

Raw amplification data from a large microRNA mixture / dilution study. These data are used by the miRcomp package to assess the performance of methods that estimate expression from the amplification curves.

r-meshdbi 1.46.0
Channel: guix-bioc
Location: guix-bioc/packages/m.scm (guix-bioc packages m)
Home page: https://bioconductor.org/packages/MeSHDbi
Licenses: Artistic License 2.0
Build system: r
Synopsis: DBI to construct MeSH-related package from sqlite file
Description:

The package is unified implementation of MeSH.db, MeSH.AOR.db, and MeSH.PCR.db and also is interface to construct Gene-MeSH package (MeSH.XXX.eg.db). loadMeSHDbiPkg import sqlite file and generate MeSH.XXX.eg.db.

r-magrene 1.12.0
Propagated dependencies: r-biocparallel@1.44.0
Channel: guix-bioc
Location: guix-bioc/packages/m.scm (guix-bioc packages m)
Home page: https://github.com/almeidasilvaf/magrene
Licenses: GPL 3
Build system: r
Synopsis: Motif Analysis In Gene Regulatory Networks
Description:

magrene allows the identification and analysis of graph motifs in (duplicated) gene regulatory networks (GRNs), including lambda, V, PPI V, delta, and bifan motifs. GRNs can be tested for motif enrichment by comparing motif frequencies to a null distribution generated from degree-preserving simulated GRNs. Motif frequencies can be analyzed in the context of gene duplications to explore the impact of small-scale and whole-genome duplications on gene regulatory networks. Finally, users can calculate interaction similarity for gene pairs based on the Sorensen-Dice similarity index.

r-missrows 1.30.0
Propagated dependencies: r-s4vectors@0.48.0 r-plyr@1.8.9 r-multiassayexperiment@1.36.1 r-gtools@3.9.5 r-ggplot2@4.0.1
Channel: guix-bioc
Location: guix-bioc/packages/m.scm (guix-bioc packages m)
Home page: https://bioconductor.org/packages/missRows
Licenses: Artistic License 2.0
Build system: r
Synopsis: Handling Missing Individuals in Multi-Omics Data Integration
Description:

The missRows package implements the MI-MFA method to deal with missing individuals ('biological units') in multi-omics data integration. The MI-MFA method generates multiple imputed datasets from a Multiple Factor Analysis model, then the yield results are combined in a single consensus solution. The package provides functions for estimating coordinates of individuals and variables, imputing missing individuals, and various diagnostic plots to inspect the pattern of missingness and visualize the uncertainty due to missing values.

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-mgu74bv2-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/mgu74bv2.db
Licenses: Artistic License 2.0
Build system: r
Synopsis: Affymetrix Affymetrix MG_U74Bv2 Array annotation data (chip mgu74bv2)
Description:

Affymetrix Affymetrix MG_U74Bv2 Array annotation data (chip mgu74bv2) assembled using data from public repositories.

r-mcseadata 1.30.0
Propagated dependencies: r-genomicranges@1.62.0
Channel: guix-bioc
Location: guix-bioc/packages/m.scm (guix-bioc packages m)
Home page: https://bioconductor.org/packages/mCSEAdata
Licenses: GPL 2
Build system: r
Synopsis: Data package for mCSEA package
Description:

Data objects necessary to some mCSEA package functions. There are also example data objects to illustrate mCSEA package functionality.

Total results: 2911