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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-cytomapper 1.22.0
Propagated dependencies: r-viridis@0.6.5 r-svgpanzoom@0.3.4 r-svglite@2.2.2 r-summarizedexperiment@1.40.0 r-spatialexperiment@1.20.0 r-singlecellexperiment@1.32.0 r-shinydashboard@0.7.3 r-shiny@1.11.1 r-s4vectors@0.48.0 r-rhdf5@2.54.0 r-rcolorbrewer@1.1-3 r-raster@3.6-32 r-nnls@1.6 r-matrixstats@1.5.0 r-hdf5array@1.38.0 r-ggplot2@4.0.1 r-ggbeeswarm@0.7.2 r-ebimage@4.52.0 r-delayedarray@0.36.0 r-biocparallel@1.44.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://github.com/BodenmillerGroup/cytomapper
Licenses: GPL 2+
Build system: r
Synopsis: Visualization of highly multiplexed imaging data in R
Description:

Highly multiplexed imaging acquires the single-cell expression of selected proteins in a spatially-resolved fashion. These measurements can be visualised across multiple length-scales. First, pixel-level intensities represent the spatial distributions of feature expression with highest resolution. Second, after segmentation, expression values or cell-level metadata (e.g. cell-type information) can be visualised on segmented cell areas. This package contains functions for the visualisation of multiplexed read-outs and cell-level information obtained by multiplexed imaging technologies. The main functions of this package allow 1. the visualisation of pixel-level information across multiple channels, 2. the display of cell-level information (expression and/or metadata) on segmentation masks and 3. gating and visualisation of single cells.

r-chevreulplot 1.2.0
Propagated dependencies: r-wiggleplotr@1.34.0 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-scuttle@1.20.0 r-scran@1.38.0 r-scater@1.38.0 r-scales@1.4.0 r-s4vectors@0.48.0 r-purrr@1.2.0 r-plotly@4.11.0 r-patchwork@1.3.2 r-ggplot2@4.0.1 r-fs@1.6.6 r-forcats@1.0.1 r-ensdb-hsapiens-v86@2.99.0 r-dplyr@1.1.4 r-complexheatmap@2.26.0 r-clustree@0.5.1 r-cluster@2.1.8.1 r-circlize@0.4.16 r-chevreulprocess@1.2.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://github.com/whtns/chevreulPlot
Licenses: Expat
Build system: r
Synopsis: Plots used in the chevreulPlot package
Description:

This package provides tools for plotting SingleCellExperiment objects in the chevreulPlot package. Includes functions for analysis and visualization of single-cell data. Supported by NIH grants R01CA137124 and R01EY026661 to David Cobrinik.

r-compass 1.48.0
Propagated dependencies: r-tidyr@1.3.1 r-scales@1.4.0 r-rmarkdown@2.30 r-rlang@1.1.6 r-reshape2@1.4.5 r-rcpp@1.1.0 r-rcolorbrewer@1.1-3 r-plyr@1.8.9 r-pdist@1.2.1 r-magrittr@2.0.4 r-knitr@1.50 r-foreach@1.5.2 r-dplyr@1.1.4 r-data-table@1.17.8 r-coda@0.19-4.1 r-clue@0.3-66 r-biocstyle@2.38.0 r-abind@1.4-8
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://bioconductor.org/packages/COMPASS
Licenses: Artistic License 2.0
Build system: r
Synopsis: Combinatorial Polyfunctionality Analysis of Single Cells
Description:

COMPASS is a statistical framework that enables unbiased analysis of antigen-specific T-cell subsets. COMPASS uses a Bayesian hierarchical framework to model all observed cell-subsets and select the most likely to be antigen-specific while regularizing the small cell counts that often arise in multi-parameter space. The model provides a posterior probability of specificity for each cell subset and each sample, which can be used to profile a subject's immune response to external stimuli such as infection or vaccination.

r-clusterseq 1.34.0
Propagated dependencies: r-biocparallel@1.44.0 r-biocgenerics@0.56.0 r-bayseq@2.44.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://github.com/samgg/clusterSeq
Licenses: GPL 3
Build system: r
Synopsis: Clustering of high-throughput sequencing data by identifying co-expression patterns
Description:

Identification of clusters of co-expressed genes based on their expression across multiple (replicated) biological samples.

r-chimp-db0 3.22.0
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/chimp.db0
Licenses: Artistic License 2.0
Build system: r
Synopsis: Base Level Annotation databases for chimp
Description:

Base annotation databases for chimp, intended ONLY to be used by AnnotationDbi to produce regular annotation packages.

r-cpsm 1.2.0
Propagated dependencies: r-survminer@0.5.1 r-survmetrics@0.5.1 r-survival@3.8-3 r-summarizedexperiment@1.40.0 r-rms@8.1-0 r-reshape2@1.4.5 r-randomforestsrc@2.9.3 r-preprocesscore@1.72.0 r-mtlr@0.2.1 r-matrix@1.7-4 r-mass@7.3-65 r-hmisc@5.2-4 r-glmnet@4.1-10 r-ggplot2@4.0.1 r-ggfortify@0.4.19 r-caret@7.0-1
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://github.com/hks5august/CPSM/
Licenses: GPL 3 FSDG-compatible
Build system: r
Synopsis: CPSM: Cancer patient survival model
Description:

CPSM provides a comprehensive computational pipeline for predicting survival probability and risk groups in cancer patients. The package includes steps for data preprocessing, training/test split, and normalization. It enables feature selection using univariate survival analysis and computes a LASSO-based prognostic index (PI) score. CPSM supports the development of predictive models using various feature sets and offers a suite of visualization tools, including survival curves based on predicted probabilities, barplots for predicted mean and median survival times, KM plots overlaid with individual survival predictions, and nomograms for estimating 1-, 3-, 5-, and 10-year survival probabilities. This makes CPSM a versatile tool for survival analysis in cancer research.

r-celarefdata 1.28.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://bioconductor.org/packages/celarefData
Licenses: GPL 3
Build system: r
Synopsis: Processed scRNA data for celaref Vignette - cell labelling by reference
Description:

This experiment data contains some processed data used in the celaref package vignette. These are publically available datasets, that have been processed by celaref package, and can be manipulated further with it.

r-cadra 1.8.0
Propagated dependencies: r-summarizedexperiment@1.40.0 r-reshape2@1.4.5 r-r-cache@0.17.0 r-ppcor@1.1 r-plyr@1.8.9 r-misc3d@0.9-1 r-mass@7.3-65 r-knnmi@1.0 r-gtable@0.3.6 r-gplots@3.2.0 r-ggplot2@4.0.1 r-doparallel@1.0.17
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://github.com/montilab/CaDrA/
Licenses: FSDG-compatible
Build system: r
Synopsis: Candidate Driver Analysis
Description:

This package performs both stepwise and backward heuristic search for candidate (epi)genetic drivers based on a binary multi-omics dataset. CaDrA's main objective is to identify features which, together, are significantly skewed or enriched pertaining to a given vector of continuous scores (e.g. sample-specific scores representing a phenotypic readout of interest, such as protein expression, pathway activity, etc.), based on the union occurence (i.e. logical OR) of the events.

r-curatedatlasqueryr 1.8.0
Propagated dependencies: r-tibble@3.3.0 r-summarizedexperiment@1.40.0 r-stringr@1.6.0 r-singlecellexperiment@1.32.0 r-seuratobject@5.2.0 r-seurat@5.3.1 r-s4vectors@0.48.0 r-rlang@1.1.6 r-purrr@1.2.0 r-httr@1.4.7 r-hdf5array@1.38.0 r-glue@1.8.0 r-duckdb@1.4.2 r-dplyr@1.1.4 r-dbplyr@2.5.1 r-dbi@1.2.3 r-cli@3.6.5 r-biocgenerics@0.56.0 r-assertthat@0.2.1
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://github.com/stemangiola/CuratedAtlasQueryR
Licenses: GPL 3
Build system: r
Synopsis: Queries the Human Cell Atlas
Description:

This package provides access to a copy of the Human Cell Atlas, but with harmonised metadata. This allows for uniform querying across numerous datasets within the Atlas using common fields such as cell type, tissue type, and patient ethnicity. Usage involves first querying the metadata table for cells of interest, and then downloading the corresponding cells into a SingleCellExperiment object.

r-ctsv 1.12.0
Propagated dependencies: r-summarizedexperiment@1.40.0 r-spatialexperiment@1.20.0 r-qvalue@2.42.0 r-pscl@1.5.9 r-knitr@1.50 r-biocparallel@1.44.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://github.com/jingeyu/CTSV
Licenses: GPL 3
Build system: r
Synopsis: Identification of cell-type-specific spatially variable genes accounting for excess zeros
Description:

The R package CTSV implements the CTSV approach developed by Jinge Yu and Xiangyu Luo that detects cell-type-specific spatially variable genes accounting for excess zeros. CTSV directly models sparse raw count data through a zero-inflated negative binomial regression model, incorporates cell-type proportions, and performs hypothesis testing based on R package pscl. The package outputs p-values and q-values for genes in each cell type, and CTSV is scalable to datasets with tens of thousands of genes measured on hundreds of spots. CTSV can be installed in Windows, Linux, and Mac OS.

r-cmapr 1.22.0
Propagated dependencies: r-summarizedexperiment@1.40.0 r-rhdf5@2.54.0 r-matrixstats@1.5.0 r-flowcore@2.22.0 r-data-table@1.17.8
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://github.com/cmap/cmapR
Licenses: FSDG-compatible
Build system: r
Synopsis: CMap Tools in R
Description:

The Connectivity Map (CMap) is a massive resource of perturbational gene expression profiles built by researchers at the Broad Institute and funded by the NIH Library of Integrated Network-Based Cellular Signatures (LINCS) program. Please visit https://clue.io for more information. The cmapR package implements methods to parse, manipulate, and write common CMap data objects, such as annotated matrices and collections of gene sets.

r-cnvgsa 1.54.0
Propagated dependencies: r-splitstackshape@1.4.8 r-genomicranges@1.62.0 r-foreach@1.5.2 r-doparallel@1.0.17 r-brglm@0.7.3
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://bioconductor.org/packages/cnvGSA
Licenses: LGPL 2.0+
Build system: r
Synopsis: Gene Set Analysis of (Rare) Copy Number Variants
Description:

This package is intended to facilitate gene-set association with rare CNVs in case-control studies.

r-cghmcr 1.68.0
Propagated dependencies: r-limma@3.66.0 r-dnacopy@1.84.0 r-cntools@1.66.0 r-biocgenerics@0.56.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://bioconductor.org/packages/cghMCR
Licenses: LGPL 2.0+
Build system: r
Synopsis: Find chromosome regions showing common gains/losses
Description:

This package provides functions to identify genomic regions of interests based on segmented copy number data from multiple samples.

r-clustirr 1.8.0
Propagated dependencies: r-visnetwork@2.1.4 r-tidyr@1.3.1 r-stringdist@0.9.15 r-stanheaders@2.32.10 r-scales@1.4.0 r-rstantools@2.5.0 r-rstan@2.32.7 r-reshape2@1.4.5 r-rcppparallel@5.1.11-1 r-rcppeigen@0.3.4.0.2 r-rcpp@1.1.0 r-posterior@1.6.1 r-igraph@2.2.1 r-ggplot2@4.0.1 r-ggforce@0.5.0 r-future-apply@1.20.0 r-future@1.68.0 r-dplyr@1.1.4 r-bh@1.87.0-1
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://github.com/snaketron/ClustIRR
Licenses: FSDG-compatible
Build system: r
Synopsis: Clustering of immune receptor repertoires
Description:

ClustIRR analyzes repertoires of B- and T-cell receptors. It starts by identifying communities of immune receptors with similar specificities, based on the sequences of their complementarity-determining regions (CDRs). Next, it employs a Bayesian probabilistic models to quantify differential community occupancy (DCO) between repertoires, allowing the identification of expanding or contracting communities in response to e.g. infection or cancer treatment.

r-crimage 1.58.0
Propagated dependencies: r-sgeostat@1.0-27 r-mass@7.3-65 r-foreach@1.5.2 r-ebimage@4.52.0 r-e1071@1.7-16 r-dnacopy@1.84.0 r-acgh@1.88.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://bioconductor.org/packages/CRImage
Licenses: Artistic License 2.0
Build system: r
Synopsis: CRImage a package to classify cells and calculate tumour cellularity
Description:

CRImage provides functionality to process and analyze images, in particular to classify cells in biological images. Furthermore, in the context of tumor images, it provides functionality to calculate tumour cellularity.

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-cmap 1.15.1
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://bioconductor.org/packages/cMAP
Licenses: LGPL 2.0+
Build system: r
Synopsis: data package containing annotation data for cMAP
Description:

Annotation data file for cMAP assembled using data from public data repositories.

r-cnorfuzzy 1.52.0
Propagated dependencies: r-nloptr@2.2.1 r-cellnoptr@1.56.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://bioconductor.org/packages/CNORfuzzy
Licenses: GPL 2
Build system: r
Synopsis: Addon to CellNOptR: Fuzzy Logic
Description:

This package is an extension to CellNOptR. It contains additional functionality needed to simulate and train a prior knowledge network to experimental data using constrained fuzzy logic (cFL, rather than Boolean logic as is the case in CellNOptR). Additionally, this package will contain functions to use for the compilation of multiple optimization results (either Boolean or cFL).

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

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

r-cpvsnp 1.42.0
Propagated dependencies: r-plyr@1.8.9 r-gseabase@1.72.0 r-ggplot2@4.0.1 r-genomicfeatures@1.62.0 r-corpcor@1.6.10 r-biocparallel@1.44.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://bioconductor.org/packages/cpvSNP
Licenses: Artistic License 2.0
Build system: r
Synopsis: Gene set analysis methods for SNP association p-values that lie in genes in given gene sets
Description:

Gene set analysis methods exist to combine SNP-level association p-values into gene sets, calculating a single association p-value for each gene set. This package implements two such methods that require only the calculated SNP p-values, the gene set(s) of interest, and a correlation matrix (if desired). One method (GLOSSI) requires independent SNPs and the other (VEGAS) can take into account correlation (LD) among the SNPs. Built-in plotting functions are available to help users visualize results.

r-ctdata 1.10.0
Propagated dependencies: r-experimenthub@3.0.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://bioconductor.org/packages/CTdata
Licenses: Artistic License 2.0
Build system: r
Synopsis: Data companion to CTexploreR
Description:

Data from publicly available databases (GTEx, CCLE, TCGA and ENCODE) that go with CTexploreR in order to re-define a comprehensive and thoroughly curated list of CT genes and their main characteristics.

r-crisprseek 1.50.0
Propagated dependencies: r-xvector@0.50.0 r-stringr@1.6.0 r-seqinr@4.2-36 r-seqinfo@1.0.0 r-s4vectors@0.48.0 r-rlang@1.1.6 r-rio@1.2.4 r-rhdf5@2.54.0 r-reticulate@1.44.1 r-openxlsx@4.2.8.1 r-mltools@0.3.5 r-keras@2.16.0 r-iranges@2.44.0 r-hash@2.2.6.3 r-gtools@3.9.5 r-genomicranges@1.62.0 r-genomicfeatures@1.62.0 r-dplyr@1.1.4 r-delayedarray@0.36.0 r-data-table@1.17.8 r-bsgenome@1.78.0 r-biostrings@2.78.0 r-biocgenerics@0.56.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://bioconductor.org/packages/CRISPRseek
Licenses: FSDG-compatible
Build system: r
Synopsis: Design of guide RNAs in CRISPR genome-editing systems
Description:

The package encompasses functions to find potential guide RNAs for the CRISPR-based genome-editing systems including the Base Editors and the Prime Editors when supplied with target sequences as input. Users have the flexibility to filter resulting guide RNAs based on parameters such as the absence of restriction enzyme cut sites or the lack of paired guide RNAs. The package also facilitates genome-wide exploration for off-targets, offering features to score and rank off-targets, retrieve flanking sequences, and indicate whether the hits are located within exon regions. All detected guide RNAs are annotated with the cumulative scores of the top5 and topN off-targets together with the detailed information such as mismatch sites and restrictuion enzyme cut sites. The package also outputs INDELs and their frequencies for Cas9 targeted sites.

r-clariomsrattranscriptcluster-db 8.8.0
Propagated dependencies: r-org-rn-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/clariomsrattranscriptcluster.db
Licenses: Artistic License 2.0
Build system: r
Synopsis: Affymetrix clariomsrat annotation data (chip clariomsrattranscriptcluster)
Description:

Affymetrix clariomsrat annotation data (chip clariomsrattranscriptcluster) assembled using data from public repositories.

r-crisprvariants 1.38.0
Propagated dependencies: r-s4vectors@0.48.0 r-rsamtools@2.26.0 r-reshape2@1.4.5 r-iranges@2.44.0 r-gridextra@2.3 r-ggplot2@4.0.1 r-genomicranges@1.62.0 r-genomicalignments@1.46.0 r-genomeinfodb@1.46.0 r-biostrings@2.78.0 r-biocparallel@1.44.0 r-annotationdbi@1.72.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://bioconductor.org/packages/CrispRVariants
Licenses: GPL 2
Build system: r
Synopsis: Tools for counting and visualising mutations in a target location
Description:

CrispRVariants provides tools for analysing the results of a CRISPR-Cas9 mutagenesis sequencing experiment, or other sequencing experiments where variants within a given region are of interest. These tools allow users to localize variant allele combinations with respect to any genomic location (e.g. the Cas9 cut site), plot allele combinations and calculate mutation rates with flexible filtering of unrelated variants.

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