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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-curatedpcadata 1.6.0
Propagated dependencies: r-s4vectors@0.48.0 r-rlang@1.1.6 r-reshape2@1.4.5 r-raggedexperiment@1.34.0 r-multiassayexperiment@1.36.1 r-experimenthub@3.0.0 r-annotationhub@4.0.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://github.com/Syksy/curatedPCaData
Licenses: FSDG-compatible
Build system: r
Synopsis: Curated Prostate Cancer Data
Description:

The package curatedPCaData offers a selection of annotated prostate cancer datasets featuring multiple omics, manually curated metadata, and derived downstream variables. The studies are offered as MultiAssayExperiment (MAE) objects via ExperimentHub, and comprise of clinical characteristics tied to gene expression, copy number alteration and somatic mutation data. Further, downstream features computed from these multi-omics data are offered. Multiple vignettes help grasp characteristics of the various studies and provide example exploratory and meta-analysis of leveraging the multiple studies provided here-in.

r-centreannotation 0.99.1
Propagated dependencies: r-rsqlite@2.4.4 r-dbi@1.2.3 r-biocgenerics@0.56.0 r-annotationhub@4.0.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://github.com/slrvv/CENTREannotation
Licenses: Artistic License 2.0
Build system: r
Synopsis: Hub package for the annotation data of CENTRE (GENCODE v40 and SCREEN v3)
Description:

This is an AnnotationHub package for the CENTRE Bioconductor software package. It contains the GENCODE version 40 annotation and ENCODE Registry of candidate cis-regulatory elements (cCREs) version 3. All for Human hg38 genome.

r-caen 1.18.0
Propagated dependencies: r-summarizedexperiment@1.40.0 r-poiclaclu@1.0.2.1
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://bioconductor.org/packages/CAEN
Licenses: GPL 2
Build system: r
Synopsis: Category encoding method for selecting feature genes for the classification of single-cell RNA-seq
Description:

With the development of high-throughput techniques, more and more gene expression analysis tend to replace hybridization-based microarrays with the revolutionary technology.The novel method encodes the category again by employing the rank of samples for each gene in each class. We then consider the correlation coefficient of gene and class with rank of sample and new rank of category. The highest correlation coefficient genes are considered as the feature genes which are most effective to classify the samples.

r-cohcapanno 1.46.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://bioconductor.org/packages/COHCAPanno
Licenses: GPL 3
Build system: r
Synopsis: Annotations for City of Hope CpG Island Analysis Pipeline
Description:

This package provides genomic location, nearby CpG island and nearby gene information for common Illumina methylation array platforms.

r-cytokernel 1.16.0
Propagated dependencies: r-summarizedexperiment@1.40.0 r-s4vectors@0.48.0 r-rlang@1.1.6 r-rcpp@1.1.0 r-magrittr@2.0.4 r-dplyr@1.1.4 r-data-table@1.17.8 r-complexheatmap@2.26.0 r-circlize@0.4.16 r-biocparallel@1.44.0 r-ashr@2.2-63
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://bioconductor.org/packages/cytoKernel
Licenses: GPL 3
Build system: r
Synopsis: Differential expression using kernel-based score test
Description:

cytoKernel implements a kernel-based score test to identify differentially expressed features in high-dimensional biological experiments. This approach can be applied across many different high-dimensional biological data including gene expression data and dimensionally reduced cytometry-based marker expression data. In this R package, we implement functions that compute the feature-wise p values and their corresponding adjusted p values. Additionally, it also computes the feature-wise shrunk effect sizes and their corresponding shrunken effect size. Further, it calculates the percent of differentially expressed features and plots user-friendly heatmap of the top differentially expressed features on the rows and samples on the columns.

r-cardinalworkflows 1.42.0
Propagated dependencies: r-cardinal@3.12.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://bioconductor.org/packages/CardinalWorkflows
Licenses: Artistic License 2.0
Build system: r
Synopsis: Datasets and workflows for the Cardinal MSI
Description:

Datasets and workflows for Cardinal: DESI and MALDI examples including pig fetus, cardinal painting, and human RCC.

r-cnorode 1.52.0
Propagated dependencies: r-genalg@0.2.1 r-cellnoptr@1.56.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://bioconductor.org/packages/CNORode
Licenses: GPL 2
Build system: r
Synopsis: ODE add-on to CellNOptR
Description:

Logic based ordinary differential equation (ODE) add-on to CellNOptR.

r-chevreulshiny 1.2.0
Propagated dependencies: r-wiggleplotr@1.34.0 r-waiter@0.2.5-1.927501b r-tidyselect@1.2.1 r-tidyr@1.3.1 r-tibble@3.3.0 r-stringr@1.6.0 r-singlecellexperiment@1.32.0 r-shinywidgets@0.9.0 r-shinyjs@2.1.0 r-shinyhelper@0.3.2 r-shinyfiles@0.9.3 r-shinydashboard@0.7.3 r-shiny@1.11.1 r-scales@1.4.0 r-s4vectors@0.48.0 r-rsqlite@2.4.4 r-readr@2.1.6 r-rappdirs@0.3.3 r-purrr@1.2.0 r-plotly@4.11.0 r-patchwork@1.3.2 r-ggplotify@0.1.3 r-ggplot2@4.0.1 r-future@1.68.0 r-fs@1.6.6 r-enhancedvolcano@1.26.0 r-dt@0.34.0 r-dplyr@1.1.4 r-dbi@1.2.3 r-dataeditr@0.1.5 r-complexheatmap@2.26.0 r-clustree@0.5.1 r-chevreulprocess@1.2.0 r-chevreulplot@1.2.0 r-alabaster-base@1.10.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://github.com/whtns/chevreulShiny
Licenses: Expat
Build system: r
Synopsis: Tools for managing SingleCellExperiment objects as projects
Description:

This package provides tools for managing SingleCellExperiment objects as projects. Includes functions for analysis and visualization of single-cell data. Also included is a shiny app for visualization of pre-processed scRNA data. Supported by NIH grants R01CA137124 and R01EY026661 to David Cobrinik.

r-cocitestats 1.82.0
Propagated dependencies: r-org-hs-eg-db@3.22.0 r-annotationdbi@1.72.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://bioconductor.org/packages/CoCiteStats
Licenses: FSDG-compatible
Build system: r
Synopsis: Different test statistics based on co-citation
Description:

This package provides a collection of software tools for dealing with co-citation data.

r-cma 1.68.0
Propagated dependencies: r-biobase@2.70.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://bioconductor.org/packages/CMA
Licenses: GPL 2+
Build system: r
Synopsis: Synthesis of microarray-based classification
Description:

This package provides a comprehensive collection of various microarray-based classification algorithms both from Machine Learning and Statistics. Variable Selection, Hyperparameter tuning, Evaluation and Comparison can be performed combined or stepwise in a user-friendly environment.

r-cleanupdtseq 1.48.0
Propagated dependencies: r-stringr@1.6.0 r-seqinr@4.2-36 r-seqinfo@1.0.0 r-s4vectors@0.48.0 r-iranges@2.44.0 r-genomicranges@1.62.0 r-e1071@1.7-16 r-bsgenome-drerio-ucsc-danrer7@1.4.0 r-bsgenome@1.78.0 r-biostrings@2.78.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://bioconductor.org/packages/cleanUpdTSeq
Licenses: GPL 2
Build system: r
Synopsis: cleanUpdTSeq cleans up artifacts from polyadenylation sites from oligo(dT)-mediated 3' end RNA sequending data
Description:

This package implements a Naive Bayes classifier for accurately differentiating true polyadenylation sites (pA sites) from oligo(dT)-mediated 3 end sequencing such as PAS-Seq, PolyA-Seq and RNA-Seq by filtering out false polyadenylation sites, mainly due to oligo(dT)-mediated internal priming during reverse transcription. The classifer is highly accurate and outperforms other heuristic methods.

r-cyp450cdf 2.18.0
Propagated dependencies: r-annotationdbi@1.72.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://bioconductor.org/packages/cyp450cdf
Licenses: LGPL 2.0+
Build system: r
Synopsis: cyp450cdf
Description:

This package provides a package containing an environment representing the CYP450.CDF file.

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

r-chromscape 1.20.0
Propagated dependencies: r-viridis@0.6.5 r-umap@0.2.10.0 r-tidyr@1.3.1 r-tibble@3.3.0 r-summarizedexperiment@1.40.0 r-stringr@1.6.0 r-stringdist@0.9.15 r-singlecellexperiment@1.32.0 r-shinywidgets@0.9.0 r-shinyjs@2.1.0 r-shinyhelper@0.3.2 r-shinyfiles@0.9.3 r-shinydashboardplus@2.0.6 r-shinydashboard@0.7.3 r-shinycssloaders@1.1.0 r-shiny@1.11.1 r-scran@1.38.0 r-scater@1.38.0 r-s4vectors@0.48.0 r-rtsne@0.17 r-rtracklayer@1.70.0 r-rsamtools@2.26.0 r-rlist@0.4.6.2 r-rcpp@1.1.0 r-qualv@0.3-5 r-qs@0.27.3 r-plotly@4.11.0 r-msigdbr@25.1.1 r-matrixtests@0.2.3.1 r-matrix@1.7-4 r-kableextra@1.4.0 r-jsonlite@2.0.0 r-irlba@2.3.5.1 r-iranges@2.44.0 r-gridextra@2.3 r-ggrepel@0.9.6 r-ggplot2@4.0.1 r-gggenes@0.5.1 r-genomicranges@1.62.0 r-fs@1.6.6 r-forcats@1.0.1 r-edger@4.8.0 r-dt@0.34.0 r-dplyr@1.1.4 r-delayedarray@0.36.0 r-coop@0.6-3 r-consensusclusterplus@1.74.0 r-colourpicker@1.3.0 r-colorramps@2.3.4 r-biocparallel@1.44.0 r-batchelor@1.26.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://github.com/vallotlab/ChromSCape
Licenses: GPL 3
Build system: r
Synopsis: Analysis of single-cell epigenomics datasets with a Shiny App
Description:

ChromSCape - Chromatin landscape profiling for Single Cells - is a ready-to-launch user-friendly Shiny Application for the analysis of single-cell epigenomics datasets (scChIP-seq, scATAC-seq, scCUT&Tag, ...) from aligned data to differential analysis & gene set enrichment analysis. It is highly interactive, enables users to save their analysis and covers a wide range of analytical steps: QC, preprocessing, filtering, batch correction, dimensionality reduction, vizualisation, clustering, differential analysis and gene set analysis.

r-cardspa 1.2.0
Propagated dependencies: r-wrmisc@1.15.4 r-summarizedexperiment@1.40.0 r-spatstat-random@3.4-3 r-spatialexperiment@1.20.0 r-sp@2.2-0 r-singlecellexperiment@1.32.0 r-sf@1.0-23 r-scatterpie@0.2.6 r-s4vectors@0.48.0 r-reshape2@1.4.5 r-rcppml@0.3.7 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-rcolorbrewer@1.1-3 r-rann@2.6.2 r-nnls@1.6 r-nmf@0.28 r-mcmcpack@1.7-1 r-matrix@1.7-4 r-gtools@3.9.5 r-ggplot2@4.0.1 r-ggcorrplot@0.1.4.1 r-fields@17.1 r-dplyr@1.1.4 r-concaveman@1.2.0 r-biocparallel@1.44.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://github.com/YMa-lab/CARDspa
Licenses: FSDG-compatible
Build system: r
Synopsis: Spatially Informed Cell Type Deconvolution for Spatial Transcriptomics
Description:

CARD is a reference-based deconvolution method that estimates cell type composition in spatial transcriptomics based on cell type specific expression information obtained from a reference scRNA-seq data. A key feature of CARD is its ability to accommodate spatial correlation in the cell type composition across tissue locations, enabling accurate and spatially informed cell type deconvolution as well as refined spatial map construction. CARD relies on an efficient optimization algorithm for constrained maximum likelihood estimation and is scalable to spatial transcriptomics with tens of thousands of spatial locations and tens of thousands of genes.

r-copyneutralima 1.28.0
Propagated dependencies: r-rdpack@2.6.4 r-experimenthub@3.0.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://bioconductor.org/packages/CopyNeutralIMA
Licenses: Artistic License 2.0
Build system: r
Synopsis: Copy Neutral Illumina Methylation Arrays
Description:

This package provides a set of genomic copy neutral samples hybridized using Illumina Methylation arrays (450k and EPIC).

r-calibracurve 1.0.0
Propagated dependencies: r-tidyr@1.3.1 r-summarizedexperiment@1.40.0 r-scales@1.4.0 r-openxlsx@4.2.8.1 r-magrittr@2.0.4 r-ggplot2@4.0.1 r-dplyr@1.1.4 r-checkmate@2.3.3
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://github.com/mpc-bioinformatics/CalibraCurve
Licenses: FSDG-compatible
Build system: r
Synopsis: Calibration curves for targeted proteomics, lipidomics and metabolomics data
Description:

CalibraCurve is a computational tool designed to generate calibration curves for targeted mass spectrometry-based quantitative data. It is applicable to various omics disciplines, including proteomics, lipidomics, and metabolomics. The package also offers functionalities for data and calibration curve visualization and concentration prediction from new datasets based on the established curves.

r-cfdnapro 1.16.0
Propagated dependencies: r-tibble@3.3.0 r-stringr@1.6.0 r-rsamtools@2.26.0 r-rlang@1.1.6 r-quantmod@0.4.28 r-plyranges@1.30.1 r-magrittr@2.0.4 r-iranges@2.44.0 r-ggplot2@4.0.1 r-genomicranges@1.62.0 r-genomicalignments@1.46.0 r-genomeinfodb@1.46.0 r-dplyr@1.1.4 r-bsgenome-hsapiens-ucsc-hg38@1.4.5 r-bsgenome-hsapiens-ucsc-hg19@1.4.3 r-bsgenome-hsapiens-ncbi-grch38@1.3.1000 r-biocgenerics@0.56.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://github.com/hw538/cfDNAPro
Licenses: GPL 3
Build system: r
Synopsis: cfDNAPro extracts and Visualises biological features from whole genome sequencing data of cell-free DNA
Description:

cfDNA fragments carry important features for building cancer sample classification ML models, such as fragment size, and fragment end motif etc. Analyzing and visualizing fragment size metrics, as well as other biological features in a curated, standardized, scalable, well-documented, and reproducible way might be time intensive. This package intends to resolve these problems and simplify the process. It offers two sets of functions for cfDNA feature characterization and visualization.

r-cocoa 2.24.0
Propagated dependencies: r-tidyr@1.3.1 r-simplecache@0.4.2 r-s4vectors@0.48.0 r-mira@1.32.0 r-iranges@2.44.0 r-ggplot2@4.0.1 r-genomicranges@1.62.0 r-fitdistrplus@1.2-4 r-data-table@1.17.8 r-complexheatmap@2.26.0 r-biocgenerics@0.56.0 r-biobase@2.70.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: http://code.databio.org/COCOA/
Licenses: GPL 3
Build system: r
Synopsis: Coordinate Covariation Analysis
Description:

COCOA is a method for understanding epigenetic variation among samples. COCOA can be used with epigenetic data that includes genomic coordinates and an epigenetic signal, such as DNA methylation and chromatin accessibility data. To describe the method on a high level, COCOA quantifies inter-sample variation with either a supervised or unsupervised technique then uses a database of "region sets" to annotate the variation among samples. A region set is a set of genomic regions that share a biological annotation, for instance transcription factor (TF) binding regions, histone modification regions, or open chromatin regions. COCOA can identify region sets that are associated with epigenetic variation between samples and increase understanding of variation in your data.

r-chipenrich 2.34.0
Propagated dependencies: r-stringr@1.6.0 r-seqinfo@1.0.0 r-s4vectors@0.48.0 r-rtracklayer@1.70.0 r-rms@8.1-0 r-plyr@1.8.9 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-org-dr-eg-db@3.22.0 r-org-dm-eg-db@3.22.0 r-mgcv@1.9-4 r-mass@7.3-65 r-latticeextra@0.6-31 r-lattice@0.22-7 r-iranges@2.44.0 r-genomicranges@1.62.0 r-chipenrich-data@2.34.0 r-biocgenerics@0.56.0 r-annotationdbi@1.72.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://bioconductor.org/packages/chipenrich
Licenses: GPL 3
Build system: r
Synopsis: Gene Set Enrichment For ChIP-seq Peak Data
Description:

ChIP-Enrich and Poly-Enrich perform gene set enrichment testing using peaks called from a ChIP-seq experiment. The method empirically corrects for confounding factors such as the length of genes, and the mappability of the sequence surrounding genes.

r-copa 1.78.0
Propagated dependencies: r-biobase@2.70.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://bioconductor.org/packages/copa
Licenses: Artistic License 2.0
Build system: r
Synopsis: Functions to perform cancer outlier profile analysis
Description:

COPA is a method to find genes that undergo recurrent fusion in a given cancer type by finding pairs of genes that have mutually exclusive outlier profiles.

r-cbn2path 1.0.0
Dependencies: gsl@2.8
Propagated dependencies: r-tidygraph@1.3.1 r-tcgabiolinks@2.38.0 r-rlang@1.1.6 r-r6@2.6.1 r-patchwork@1.3.2 r-magrittr@2.0.4 r-igraph@2.2.1 r-ggraph@2.2.2 r-ggplot2@4.0.1 r-cowplot@1.2.0 r-coda@0.19-4.1 r-biocparallel@1.44.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://github.com/rockwillck/CBN2Path
Licenses: Expat
Build system: r
Synopsis: "CBN2Path: an R/Bioconductor package for the analysis of cancer progression pathways using Conjunctive Bayesian Networks
Description:

CBN2Path package provides a unifying interface to facilitate CBN-based quantification, analysis and visualization of cancer progression pathways.

r-cytomem 1.14.0
Propagated dependencies: r-matrixstats@1.5.0 r-gplots@3.2.0 r-flowcore@2.22.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://github.com/cytolab/cytoMEM
Licenses: GPL 3
Build system: r
Synopsis: Marker Enrichment Modeling (MEM)
Description:

MEM, Marker Enrichment Modeling, automatically generates and displays quantitative labels for cell populations that have been identified from single-cell data. The input for MEM is a dataset that has pre-clustered or pre-gated populations with cells in rows and features in columns. Labels convey a list of measured features and the features levels of relative enrichment on each population. MEM can be applied to a wide variety of data types and can compare between MEM labels from flow cytometry, mass cytometry, single cell RNA-seq, and spectral flow cytometry using RMSD.

r-comethdmr 1.14.0
Propagated dependencies: r-lmertest@3.1-3 r-iranges@2.44.0 r-genomicranges@1.62.0 r-experimenthub@3.0.0 r-bumphunter@1.52.0 r-biocparallel@1.44.0 r-annotationhub@4.0.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://github.com/TransBioInfoLab/coMethDMR
Licenses: GPL 3
Build system: r
Synopsis: Accurate identification of co-methylated and differentially methylated regions in epigenome-wide association studies
Description:

coMethDMR identifies genomic regions associated with continuous phenotypes by optimally leverages covariations among CpGs within predefined genomic regions. Instead of testing all CpGs within a genomic region, coMethDMR carries out an additional step that selects co-methylated sub-regions first without using any outcome information. Next, coMethDMR tests association between methylation within the sub-region and continuous phenotype using a random coefficient mixed effects model, which models both variations between CpG sites within the region and differential methylation simultaneously.

Total results: 2909