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    / / /\ \ \ / / /  \ \_\\ \ \_/      \ \ \ \/___/
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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-spasim 1.12.0
Propagated dependencies: r-summarizedexperiment@1.40.0 r-spatstat-random@3.4-3 r-spatstat-geom@3.6-1 r-spatialexperiment@1.20.0 r-rann@2.6.2 r-ggplot2@4.0.1 r-dplyr@1.1.4
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://trigosteam.github.io/spaSim/
Licenses: Artistic License 2.0
Build system: r
Synopsis: Spatial point data simulator for tissue images
Description:

This package provides a suite of functions for simulating spatial patterns of cells in tissue images. Output images are multitype point data in SingleCellExperiment format. Each point represents a cell, with its 2D locations and cell type. Potential cell patterns include background cells, tumour/immune cell clusters, immune rings, and blood/lymphatic vessels.

r-spatialomicsoverlay 1.10.0
Propagated dependencies: r-xml@3.99-0.20 r-stringr@1.6.0 r-scattermore@1.2 r-s4vectors@0.48.0 r-readxl@1.4.5 r-rbioformats@1.10.0 r-plotrix@3.8-13 r-pbapply@1.7-4 r-magick@2.9.0 r-ggtext@0.1.2 r-ggplot2@4.0.1 r-geomxtools@3.14.0 r-ebimage@4.52.0 r-dplyr@1.1.4 r-data-table@1.17.8 r-biocfilecache@3.0.0 r-biobase@2.70.0 r-base64enc@0.1-3
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://bioconductor.org/packages/SpatialOmicsOverlay
Licenses: Expat
Build system: r
Synopsis: Spatial Overlay for Omic Data from Nanostring GeoMx Data
Description:

This package provides tools for NanoString Technologies GeoMx Technology. Package to easily graph on top of an OME-TIFF image. Plotting annotations can range from tissue segment to gene expression.

r-spsimseq 1.20.0
Propagated dependencies: r-wgcna@1.73 r-singlecellexperiment@1.32.0 r-phyloseq@1.54.0 r-mvtnorm@1.3-3 r-limma@3.66.0 r-hmisc@5.2-4 r-fitdistrplus@1.2-4 r-edger@4.8.0
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://github.com/CenterForStatistics-UGent/SPsimSeq
Licenses: GPL 2
Build system: r
Synopsis: Semi-parametric simulation tool for bulk and single-cell RNA sequencing data
Description:

SPsimSeq uses a specially designed exponential family for density estimation to constructs the distribution of gene expression levels from a given real RNA sequencing data (single-cell or bulk), and subsequently simulates a new dataset from the estimated marginal distributions using Gaussian-copulas to retain the dependence between genes. It allows simulation of multiple groups and batches with any required sample size and library size.

r-sccomp 2.2.0
Propagated dependencies: 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-scales@1.4.0 r-rlang@1.1.6 r-readr@2.1.6 r-purrr@1.2.0 r-patchwork@1.3.2 r-magrittr@2.0.4 r-lifecycle@1.0.4 r-instantiate@0.2.3 r-glue@1.8.0 r-ggrepel@0.9.6 r-ggplot2@4.0.1 r-forcats@1.0.1 r-fansi@1.0.7 r-dplyr@1.1.4 r-crayon@1.5.3 r-cli@3.6.5 r-boot@1.3-32
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://github.com/MangiolaLaboratory/sccomp
Licenses: GPL 3
Build system: r
Synopsis: Differential Composition and Variability Analysis for Single-Cell Data
Description:

Comprehensive R package for differential composition and variability analysis in single-cell RNA sequencing, CyTOF, and microbiome data. Provides robust Bayesian modeling with outlier detection, random effects, and advanced statistical methods for cell type proportion analysis. Features include probabilistic outlier identification, mixed-effect modeling, differential variability testing, and comprehensive visualization tools. Perfect for cancer research, immunology, developmental biology, and single-cell genomics applications.

r-spacetrooper 1.0.1
Propagated dependencies: r-summarizedexperiment@1.40.0 r-spatialexperimentio@1.2.0 r-spatialexperiment@1.20.0 r-sfheaders@0.4.5 r-sf@1.0-23 r-scuttle@1.20.0 r-scater@1.38.0 r-s4vectors@0.48.0 r-robustbase@0.99-6 r-rlang@1.1.6 r-rhdf5@2.54.0 r-glmnet@4.1-10 r-ggpubr@0.6.2 r-ggplot2@4.0.1 r-e1071@1.7-16 r-dropletutils@1.30.0 r-dplyr@1.1.4 r-data-table@1.17.8 r-cowplot@1.2.0 r-arrow@22.0.0
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://github.com/drighelli/SpaceTrooper
Licenses: Expat
Build system: r
Synopsis: SpaceTrooper performs Quality Control analysis of Image-Based spatial
Description:

SpaceTrooper performs Quality Control analysis using data driven GLM models of Image-Based spatial data, providing exploration plots, QC metrics computation, outlier detection. It implements a GLM strategy for the detection of low quality cells in imaging-based spatial data (Transcriptomics and Proteomics). It additionally implements several plots for the visualization of imaging based polygons through the ggplot2 package.

r-survclust 1.4.0
Propagated dependencies: r-survival@3.8-3 r-rcpp@1.1.0 r-pdist@1.2.1 r-multiassayexperiment@1.36.1
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://github.com/arorarshi/survClust
Licenses: Expat
Build system: r
Synopsis: Identification Of Clinically Relevant Genomic Subtypes Using Outcome Weighted Learning
Description:

survClust is an outcome weighted integrative clustering algorithm used to classify multi-omic samples on their available time to event information. The resulting clusters are cross-validated to avoid over overfitting and output classification of samples that are molecularly distinct and clinically meaningful. It takes in binary (mutation) as well as continuous data (other omic types).

r-spatialheatmap 2.16.3
Propagated dependencies: r-xml2@1.5.0 r-tibble@3.3.0 r-summarizedexperiment@1.40.0 r-spscomps@0.3.4.0 r-singlecellexperiment@1.32.0 r-shinydashboard@0.7.3 r-shiny@1.11.1 r-s4vectors@0.48.0 r-rsvg@2.7.0 r-reshape2@1.4.5 r-matrix@1.7-4 r-igraph@2.2.1 r-grimport@0.9-7 r-gridextra@2.3 r-ggplotify@0.1.3 r-ggplot2@4.0.1 r-genefilter@1.92.0 r-edger@4.8.0 r-dplyr@1.1.4 r-data-table@1.17.8
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://spatialheatmap.org
Licenses: Artistic License 2.0
Build system: r
Synopsis: spatialHeatmap: Visualizing Spatial Assays in Anatomical Images and Large-Scale Data Extensions
Description:

The spatialHeatmap package offers the primary functionality for visualizing cell-, tissue- and organ-specific assay data in spatial anatomical images. Additionally, it provides extended functionalities for large-scale data mining routines and co-visualizing bulk and single-cell data. A description of the project is available here: https://spatialheatmap.org.

r-sosta 1.2.0
Propagated dependencies: r-terra@1.8-86 r-summarizedexperiment@1.40.0 r-spatstat-random@3.4-3 r-spatstat-geom@3.6-1 r-spatstat-explore@3.6-0 r-spatialexperiment@1.20.0 r-smoothr@1.2.1 r-singlecellexperiment@1.32.0 r-sf@1.0-23 r-s4vectors@0.48.0 r-rlang@1.1.6 r-patchwork@1.3.2 r-ggplot2@4.0.1 r-ebimage@4.52.0 r-dplyr@1.1.4
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://github.com/sgunz/sosta
Licenses: FSDG-compatible
Build system: r
Synopsis: package for the analysis of anatomical tissue structures in spatial omics data
Description:

sosta (Spatial Omics STructure Analysis) is a package for analyzing spatial omics data to explore tissue organization at the anatomical structure level. It reconstructs anatomically relevant structures based on molecular features or cell types. It further calculates a range of metrics at the structure level to quantitatively describe tissue architecture. The package is designed to integrate with other packages for the analysis of spatial omics data.

r-spatialexperimentio 1.2.0
Propagated dependencies: r-spatialexperiment@1.20.0 r-singlecellexperiment@1.32.0 r-s4vectors@0.48.0 r-purrr@1.2.0 r-dropletutils@1.30.0 r-data-table@1.17.8 r-arrow@22.0.0
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://github.com/estellad/SpatialExperimentIO
Licenses: Artistic License 2.0
Build system: r
Synopsis: Read in Xenium, CosMx, MERSCOPE or STARmapPLUS data as SpatialExperiment object
Description:

Read in imaging-based spatial transcriptomics technology data. Current available modules are for Xenium by 10X Genomics, CosMx by Nanostring, MERSCOPE by Vizgen, or STARmapPLUS from Broad Institute. You can choose to read the data in as a SpatialExperiment or a SingleCellExperiment object.

r-synlet 2.10.0
Propagated dependencies: r-rcolorbrewer@1.1-3 r-rankprod@3.36.0 r-patchwork@1.3.2 r-magrittr@2.0.4 r-ggplot2@4.0.1 r-data-table@1.17.8
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://bioconductor.org/packages/synlet
Licenses: GPL 3
Build system: r
Synopsis: Hits Selection for Synthetic Lethal RNAi Screen Data
Description:

Select hits from synthetic lethal RNAi screen data. For example, there are two identical celllines except one gene is knocked-down in one cellline. The interest is to find genes that lead to stronger lethal effect when they are knocked-down further by siRNA. Quality control and various visualisation tools are implemented. Four different algorithms could be used to pick up the interesting hits. This package is designed based on 384 wells plates, but may apply to other platforms with proper configuration.

r-simpintlists 1.46.0
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://bioconductor.org/packages/simpIntLists
Licenses: GPL 2+
Build system: r
Synopsis: The package contains BioGRID interactions for various organisms in a simple format
Description:

The package contains BioGRID interactions for arabidopsis(thale cress), c.elegans, fruit fly, human, mouse, yeast( budding yeast ) and S.pombe (fission yeast) . Entrez ids, official names and unique ids can be used to find proteins. The format of interactions are lists. For each gene/protein, there is an entry in the list with "name" containing name of the gene/protein and "interactors" containing the list of genes/proteins interacting with it.

r-simat 1.42.0
Propagated dependencies: r-reshape2@1.4.5 r-rcpp@1.1.0 r-mzr@2.44.0 r-ggplot2@4.0.1
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: http://omics.georgetown.edu/SIMAT.html
Licenses: GPL 2
Build system: r
Synopsis: GC-SIM-MS data processing and alaysis tool
Description:

This package provides a pipeline for analysis of GC-MS data acquired in selected ion monitoring (SIM) mode. The tool also provides a guidance in choosing appropriate fragments for the targets of interest by using an optimization algorithm. This is done by considering overlapping peaks from a provided library by the user.

r-scoreinvhap 1.32.0
Propagated dependencies: r-variantannotation@1.56.0 r-summarizedexperiment@1.40.0 r-snpstats@1.60.0 r-genomicranges@1.62.0 r-biostrings@2.78.0 r-biocparallel@1.44.0
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://bioconductor.org/packages/scoreInvHap
Licenses: FSDG-compatible
Build system: r
Synopsis: Get inversion status in predefined regions
Description:

scoreInvHap can get the samples inversion status of known inversions. scoreInvHap uses SNP data as input and requires the following information about the inversion: genotype frequencies in the different haplotypes, R2 between the region SNPs and inversion status and heterozygote genotypes in the reference. The package include this data for 21 inversions.

r-slalom 1.32.0
Propagated dependencies: r-summarizedexperiment@1.40.0 r-singlecellexperiment@1.32.0 r-rsvd@1.0.5 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-gseabase@1.72.0 r-ggplot2@4.0.1 r-bh@1.87.0-1
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://bioconductor.org/packages/slalom
Licenses: GPL 2
Build system: r
Synopsis: Factorial Latent Variable Modeling of Single-Cell RNA-Seq Data
Description:

slalom is a scalable modelling framework for single-cell RNA-seq data that uses gene set annotations to dissect single-cell transcriptome heterogeneity, thereby allowing to identify biological drivers of cell-to-cell variability and model confounding factors. The method uses Bayesian factor analysis with a latent variable model to identify active pathways (selected by the user, e.g. KEGG pathways) that explain variation in a single-cell RNA-seq dataset. This an R/C++ implementation of the f-scLVM Python package. See the publication describing the method at https://doi.org/10.1186/s13059-017-1334-8.

r-snagee 1.50.0
Propagated dependencies: r-snageedata@1.46.0
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: http://bioconductor.org/
Licenses: Artistic License 2.0
Build system: r
Synopsis: Signal-to-Noise applied to Gene Expression Experiments
Description:

Signal-to-Noise applied to Gene Expression Experiments. Signal-to-noise ratios can be used as a proxy for quality of gene expression studies and samples. The SNRs can be calculated on any gene expression data set as long as gene IDs are available, no access to the raw data files is necessary. This allows to flag problematic studies and samples in any public data set.

r-scdotplot 1.4.0
Propagated dependencies: r-tidyr@1.3.1 r-tibble@3.3.0 r-stringr@1.6.0 r-singlecellexperiment@1.32.0 r-seurat@5.3.1 r-scater@1.38.0 r-scales@1.4.0 r-rlang@1.1.6 r-purrr@1.2.0 r-magrittr@2.0.4 r-ggtree@4.0.1 r-ggsci@4.1.0 r-ggplot2@4.0.1 r-dplyr@1.1.4 r-cli@3.6.5 r-biocgenerics@0.56.0 r-aplot@0.2.9
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://github.com/ben-laufer/scDotPlot
Licenses: Artistic License 2.0
Build system: r
Synopsis: Cluster a Single-cell RNA-seq Dot Plot
Description:

Dot plots of single-cell RNA-seq data allow for an examination of the relationships between cell groupings (e.g. clusters) and marker gene expression. The scDotPlot package offers a unified approach to perform a hierarchical clustering analysis and add annotations to the columns and/or rows of a scRNA-seq dot plot. It works with SingleCellExperiment and Seurat objects as well as data frames.

r-svmdo 1.10.0
Propagated dependencies: r-survival@3.8-3 r-summarizedexperiment@1.40.0 r-sjmisc@2.8.11 r-shinytitle@0.1.0 r-shinyfiles@0.9.3 r-shiny@1.11.1 r-org-hs-eg-db@3.22.0 r-nortest@1.0-4 r-klar@1.7-3 r-golem@0.5.1 r-e1071@1.7-16 r-dt@0.34.0 r-dplyr@1.1.4 r-dose@4.4.0 r-data-table@1.17.8 r-catools@1.18.3 r-caret@7.0-1 r-bsda@1.2.2 r-annotationdbi@1.72.0
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://bioconductor.org/packages/SVMDO
Licenses: GPL 3
Build system: r
Synopsis: Identification of Tumor-Discriminating mRNA Signatures via Support Vector Machines Supported by Disease Ontology
Description:

It is an easy-to-use GUI using disease information for detecting tumor/normal sample discriminating gene sets from differentially expressed genes. Our approach is based on an iterative algorithm filtering genes with disease ontology enrichment analysis and wilk and wilks lambda criterion connected to SVM classification model construction. Along with gene set extraction, SVMDO also provides individual prognostic marker detection. The algorithm is designed for FPKM and RPKM normalized RNA-Seq transcriptome datasets.

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

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

r-simpic 1.6.0
Propagated dependencies: r-withr@3.0.2 r-summarizedexperiment@1.40.0 r-singlecellexperiment@1.32.0 r-scuttle@1.20.0 r-scales@1.4.0 r-s4vectors@0.48.0 r-rlang@1.1.6 r-matrixstats@1.5.0 r-matrix@1.7-4 r-fitdistrplus@1.2-4 r-edger@4.8.0 r-checkmate@2.3.3 r-biocgenerics@0.56.0 r-actuar@3.3-6
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://github.com/sagrikachugh/simPIC
Licenses: GPL 3
Build system: r
Synopsis: Flexible simulation of paired-insertion counts for single-cell ATAC-sequencing data
Description:

simPIC is a package for simulating single-cell ATAC-seq count data. It provides a user-friendly, well documented interface for data simulation. Functions are provided for parameter estimation, realistic scATAC-seq data simulation, and comparing real and simulated datasets.

r-scrnaseqapp 1.10.0
Propagated dependencies: r-xml2@1.5.0 r-xfun@0.54 r-sortable@0.6.0 r-slingshot@2.18.0 r-singlecellexperiment@1.32.0 r-shinymanager@1.0.410 r-shinyhelper@0.3.2 r-shiny@1.11.1 r-seuratobject@5.2.0 r-seurat@5.3.1 r-scrypt@0.1.6 r-scales@1.4.0 r-s4vectors@0.48.0 r-rtracklayer@1.70.0 r-rsqlite@2.4.4 r-rsamtools@2.26.0 r-rhdf5@2.54.0 r-reshape2@1.4.5 r-refmanager@1.4.0 r-rcolorbrewer@1.1-3 r-plotly@4.11.0 r-patchwork@1.3.2 r-matrix@1.7-4 r-magrittr@2.0.4 r-jsonlite@2.0.0 r-iranges@2.44.0 r-htmltools@0.5.8.1 r-gridextra@2.3 r-ggridges@0.5.7 r-ggrepel@0.9.6 r-ggplot2@4.0.1 r-ggforce@0.5.0 r-ggdendro@0.2.0 r-genomicranges@1.62.0 r-genomeinfodb@1.46.0 r-fs@1.6.6 r-dt@0.34.0 r-dbi@1.2.3 r-data-table@1.17.8 r-complexheatmap@2.26.0 r-colourpicker@1.3.0 r-circlize@0.4.16 r-bslib@0.9.0 r-bibtex@0.5.1
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://github.com/jianhong/scRNAseqApp
Licenses: GPL 3
Build system: r
Synopsis: single-cell RNAseq Shiny app-package
Description:

The scRNAseqApp is a Shiny app package designed for interactive visualization of single-cell data. It is an enhanced version derived from the ShinyCell, repackaged to accommodate multiple datasets. The app enables users to visualize data containing various types of information simultaneously, facilitating comprehensive analysis. Additionally, it includes a user management system to regulate database accessibility for different users.

r-serumstimulation 1.46.0
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://bioconductor.org/packages/serumStimulation
Licenses: GPL 2+
Build system: r
Synopsis: serumStimulation is a data package which is used by examples in package pcaGoPromoter
Description:

This package contains 13 micro array data results from a serum stimulation experiment.

r-smokingmouse 1.8.0
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://github.com/LieberInstitute/smokingMouse
Licenses: Artistic License 2.0
Build system: r
Synopsis: Provides access to smokingMouse project data
Description:

This is an ExperimentHub package that provides access to the data generated and analyzed in the [smoking-nicotine-mouse](https://github.com/LieberInstitute/smoking-nicotine-mouse/) LIBD project. The datasets contain the expression data of mouse genes, transcripts, exons, and exon-exon junctions across 208 samples from pup and adult mouse brain, and adult blood, that were exposed to nicotine, cigarette smoke, or controls. They also contain relevant metadata of these samples and gene expression features, such QC metrics, if they were used after filtering steps and also if the features were differently expressed in the different experiments.

r-schiccompare 1.2.0
Propagated dependencies: r-tidyr@1.3.1 r-rstatix@0.7.3 r-rlang@1.1.6 r-ranger@0.17.0 r-miceadds@3.18-36 r-mice@3.18.0 r-mclust@6.1.2 r-lattice@0.22-7 r-hiccompare@1.32.0 r-gtools@3.9.5 r-ggplot2@4.0.1 r-dplyr@1.1.4 r-data-table@1.17.8 r-biocparallel@1.44.0
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://github.com/dozmorovlab/ScHiCcompare
Licenses: Expat
Build system: r
Synopsis: Differential Analysis of Single-cell Hi-C Data
Description:

This package provides functions for differential chromatin interaction analysis between two single-cell Hi-C data groups. It includes tools for imputation, normalization, and differential analysis of chromatin interactions. The package implements pooling techniques for imputation and offers methods to normalize and test for differential interactions across single-cell Hi-C datasets.

r-sdams 1.30.0
Propagated dependencies: r-trust@0.1-8 r-summarizedexperiment@1.40.0 r-qvalue@2.42.0
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://bioconductor.org/packages/SDAMS
Licenses: GPL 2+ GPL 3+
Build system: r
Synopsis: Differential Abundant/Expression Analysis for Metabolomics, Proteomics and single-cell RNA sequencing Data
Description:

This Package utilizes a Semi-parametric Differential Abundance/expression analysis (SDA) method for metabolomics and proteomics data from mass spectrometry as well as single-cell RNA sequencing data. SDA is able to robustly handle non-normally distributed data and provides a clear quantification of the effect size.

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Total results: 68658