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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-spacemarkers 2.0.0
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://github.com/DeshpandeLab/SpaceMarkers
Licenses: Expat
Build system: r
Synopsis: Spatial Interaction Markers
Description:

Spatial transcriptomic technologies have helped to resolve the connection between gene expression and the 2D orientation of tissues relative to each other. However, the limited single-cell resolution makes it difficult to highlight the most important molecular interactions in these tissues. SpaceMarkers, R/Bioconductor software, can help to find molecular interactions, by identifying genes associated with latent space interactions in spatial transcriptomics.

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-speckle 1.10.0
Propagated dependencies: r-singlecellexperiment@1.32.0 r-seurat@5.3.1 r-limma@3.66.0 r-ggplot2@4.0.1 r-edger@4.8.0
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://bioconductor.org/packages/speckle
Licenses: GPL 3
Build system: r
Synopsis: Statistical methods for analysing single cell RNA-seq data
Description:

The speckle package contains functions for the analysis of single cell RNA-seq data. The speckle package currently contains functions to analyse differences in cell type proportions. There are also functions to estimate the parameters of the Beta distribution based on a given counts matrix, and a function to normalise a counts matrix to the median library size. There are plotting functions to visualise cell type proportions and the mean-variance relationship in cell type proportions and counts. As our research into specialised analyses of single cell data continues we anticipate that the package will be updated with new functions.

r-somaticcanceralterations 1.46.0
Propagated dependencies: r-s4vectors@0.48.0 r-iranges@2.44.0 r-genomicranges@1.62.0
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://bioconductor.org/packages/SomaticCancerAlterations
Licenses: GPL 3
Build system: r
Synopsis: Somatic Cancer Alterations
Description:

Collection of somatic cancer alteration datasets.

r-splatter 1.34.0
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://bioconductor.org/packages/splatter/
Licenses: FSDG-compatible
Build system: r
Synopsis: Simple Simulation of Single-cell RNA Sequencing Data
Description:

Splatter is a package for the simulation of single-cell RNA sequencing count data. It provides a simple interface for creating complex simulations that are reproducible and well-documented. Parameters can be estimated from real data and functions are provided for comparing real and simulated datasets.

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@1.7-4 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-simbu 1.12.0
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://github.com/omnideconv/SimBu
Licenses: FSDG-compatible
Build system: r
Synopsis: Simulate Bulk RNA-seq Datasets from Single-Cell Datasets
Description:

SimBu can be used to simulate bulk RNA-seq datasets with known cell type fractions. You can either use your own single-cell study for the simulation or the sfaira database. Different pre-defined simulation scenarios exist, as are options to run custom simulations. Additionally, expression values can be adapted by adding an mRNA bias, which produces more biologically relevant simulations.

r-seqcombo 1.32.0
Propagated dependencies: r-yulab-utils@0.2.1 r-igraph@2.2.1 r-ggplot2@4.0.1
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://bioconductor.org/packages/seqcombo
Licenses: Artistic License 2.0
Build system: r
Synopsis: Visualization Tool for Genetic Reassortment
Description:

This package provides useful functions for visualizing virus reassortment events.

r-swath2stats 1.40.1
Propagated dependencies: r-reshape2@1.4.5 r-ggplot2@4.0.1 r-data-table@1.17.8 r-biomart@2.66.0
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://peterblattmann.github.io/SWATH2stats/
Licenses: GPL 3
Build system: r
Synopsis: Transform and Filter SWATH Data for Statistical Packages
Description:

This package is intended to transform SWATH data from the OpenSWATH software into a format readable by other statistics packages while performing filtering, annotation and FDR estimation.

r-simbenchdata 1.18.0
Propagated dependencies: r-s4vectors@0.48.0 r-experimenthub@3.0.0
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://bioconductor.org/packages/SimBenchData
Licenses: GPL 3
Build system: r
Synopsis: SimBenchData: a collection of 35 single-cell RNA-seq data covering a wide range of data characteristics
Description:

The SimBenchData package contains a total of 35 single-cell RNA-seq datasets covering a wide range of data characteristics, including major sequencing protocols, multiple tissue types, and both human and mouse sources.

r-shdz-db 3.2.3
Propagated dependencies: r-org-hs-eg-db@3.22.0 r-annotationdbi@1.72.0
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://bioconductor.org/packages/SHDZ.db
Licenses: Artistic License 2.0
Build system: r
Synopsis: SHDZ http://genome-www5.stanford.edu/ Annotation Data (SHDZ)
Description:

SHDZ http://genome-www5.stanford.edu/ Annotation Data (SHDZ) assembled using data from public repositories.

r-scarray 1.18.0
Propagated dependencies: r-summarizedexperiment@1.40.0 r-sparsearray@1.10.2 r-singlecellexperiment@1.32.0 r-s4vectors@0.48.0 r-matrix@1.7-4 r-gdsfmt@1.46.0 r-delayedmatrixstats@1.32.0 r-delayedarray@0.36.0 r-biocsingular@1.26.1 r-biocparallel@1.44.0
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://github.com/AbbVie-ComputationalGenomics/SCArray
Licenses: GPL 3
Build system: r
Synopsis: Large-scale single-cell omics data manipulation with GDS files
Description:

This package provides large-scale single-cell omics data manipulation using Genomic Data Structure (GDS) files. It combines dense and sparse matrices stored in GDS files and the Bioconductor infrastructure framework (SingleCellExperiment and DelayedArray) to provide out-of-memory data storage and large-scale manipulation using the R programming language.

r-spikein 1.52.0
Propagated dependencies: r-affy@1.88.0
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://bioconductor.org/packages/SpikeIn
Licenses: Artistic License 2.0
Build system: r
Synopsis: Affymetrix Spike-In Experiment Data
Description:

This package contains the HGU133 and HGU95 spikein experiment data.

r-sitadela 1.18.0
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://github.com/pmoulos/sitadela
Licenses: Artistic License 2.0
Build system: r
Synopsis: An R package for the easy provision of simple but complete tab-delimited genomic annotation from a variety of sources and organisms
Description:

This package provides an interface to build a unified database of genomic annotations and their coordinates (gene, transcript and exon levels). It is aimed to be used when simple tab-delimited annotations (or simple GRanges objects) are required instead of the more complex annotation Bioconductor packages. Also useful when combinatorial annotation elements are reuired, such as RefSeq coordinates with Ensembl biotypes. Finally, it can download, construct and handle annotations with versioned genes and transcripts (where available, e.g. RefSeq and latest Ensembl). This is particularly useful in precision medicine applications where the latter must be reported.

r-sradb 1.72.0
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://bioconductor.org/packages/SRAdb
Licenses: Artistic License 2.0
Build system: r
Synopsis: compilation of metadata from NCBI SRA and tools
Description:

The Sequence Read Archive (SRA) is the largest public repository of sequencing data from the next generation of sequencing platforms including Roche 454 GS System, Illumina Genome Analyzer, Applied Biosystems SOLiD System, Helicos Heliscope, and others. However, finding data of interest can be challenging using current tools. SRAdb is an attempt to make access to the metadata associated with submission, study, sample, experiment and run much more feasible. This is accomplished by parsing all the NCBI SRA metadata into a SQLite database that can be stored and queried locally. Fulltext search in the package make querying metadata very flexible and powerful. fastq and sra files can be downloaded for doing alignment locally. Beside ftp protocol, the SRAdb has funcitons supporting fastp protocol (ascp from Aspera Connect) for faster downloading large data files over long distance. The SQLite database is updated regularly as new data is added to SRA and can be downloaded at will for the most up-to-date metadata.

r-svaretro 1.16.6
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://bioconductor.org/packages/svaRetro
Licenses: FSDG-compatible
Build system: r
Synopsis: Retrotransposed transcript detection from structural variants
Description:

svaRetro contains functions for detecting retrotransposed transcripts (RTs) from structural variant calls. It takes structural variant calls in GRanges of breakend notation and identifies RTs by exon-exon junctions and insertion sites. The candidate RTs are reported by events and annotated with information of the inserted transcripts.

r-simlr 1.36.0
Propagated dependencies: r-rspectra@0.16-2 r-rcppannoy@0.0.22 r-rcpp@1.1.0 r-pracma@2.4.6 r-matrix@1.7-4
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://github.com/BatzoglouLabSU/SIMLR
Licenses: FSDG-compatible
Build system: r
Synopsis: Single-cell Interpretation via Multi-kernel LeaRning (SIMLR)
Description:

Single-cell RNA-seq technologies enable high throughput gene expression measurement of individual cells, and allow the discovery of heterogeneity within cell populations. Measurement of cell-to-cell gene expression similarity is critical for the identification, visualization and analysis of cell populations. However, single-cell data introduce challenges to conventional measures of gene expression similarity because of the high level of noise, outliers and dropouts. We develop a novel similarity-learning framework, SIMLR (Single-cell Interpretation via Multi-kernel LeaRning), which learns an appropriate distance metric from the data for dimension reduction, clustering and visualization.

r-spqndata 1.22.0
Propagated dependencies: r-summarizedexperiment@1.40.0
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://bioconductor.org/packages/spqnData
Licenses: Artistic License 2.0
Build system: r
Synopsis: Data for the spqn package
Description:

Bulk RNA-seq from GTEx on 4,000 randomly selected, expressed genes. Data has been processed for co-expression analysis.

r-sccb2 1.20.0
Propagated dependencies: r-summarizedexperiment@1.40.0 r-singlecellexperiment@1.32.0 r-seurat@5.3.1 r-rhdf5@2.54.0 r-matrix@1.7-4 r-iterators@1.0.14 r-foreach@1.5.2 r-edger@4.8.0 r-dropletutils@1.30.0 r-doparallel@1.0.17
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://github.com/zijianni/scCB2
Licenses: GPL 3
Build system: r
Synopsis: CB2 improves power of cell detection in droplet-based single-cell RNA sequencing data
Description:

scCB2 is an R package implementing CB2 for distinguishing real cells from empty droplets in droplet-based single cell RNA-seq experiments (especially for 10x Chromium). It is based on clustering similar barcodes and calculating Monte-Carlo p-value for each cluster to test against background distribution. This cluster-level test outperforms single-barcode-level tests in dealing with low count barcodes and homogeneous sequencing library, while keeping FDR well controlled.

r-ssnappy 1.14.0
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://wenjun-liu.github.io/sSNAPPY/
Licenses: GPL 3
Build system: r
Synopsis: Single Sample directioNAl Pathway Perturbation analYsis
Description:

This package provides a single sample pathway perturbation testing method for RNA-seq data. The method propagates changes in gene expression down gene-set topologies to compute single-sample directional pathway perturbation scores that reflect potential direction of change. Perturbation scores can be used to test significance of pathway perturbation at both individual-sample and treatment levels.

r-spatialdecon 1.20.1
Propagated dependencies: r-seuratobject@5.2.0 r-repmis@0.5.1 r-matrix@1.7-4 r-lognormreg@0.5-0 r-geomxtools@3.14.0 r-biobase@2.70.0
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://bioconductor.org/packages/SpatialDecon
Licenses: Expat
Build system: r
Synopsis: Deconvolution of mixed cells from spatial and/or bulk gene expression data
Description:

Using spatial or bulk gene expression data, estimates abundance of mixed cell types within each observation. Based on "Advances in mixed cell deconvolution enable quantification of cell types in spatial transcriptomic data", Danaher (2022). Designed for use with the NanoString GeoMx platform, but applicable to any gene expression data.

r-scmet 1.12.0
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://bioconductor.org/packages/scMET
Licenses: GPL 3
Build system: r
Synopsis: Bayesian modelling of cell-to-cell DNA methylation heterogeneity
Description:

High-throughput single-cell measurements of DNA methylomes can quantify methylation heterogeneity and uncover its role in gene regulation. However, technical limitations and sparse coverage can preclude this task. scMET is a hierarchical Bayesian model which overcomes sparsity, sharing information across cells and genomic features to robustly quantify genuine biological heterogeneity. scMET can identify highly variable features that drive epigenetic heterogeneity, and perform differential methylation and variability analyses. We illustrate how scMET facilitates the characterization of epigenetically distinct cell populations and how it enables the formulation of novel hypotheses on the epigenetic regulation of gene expression.

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-sampleclassifierdata 1.34.0
Propagated dependencies: r-summarizedexperiment@1.40.0
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://bioconductor.org/packages/sampleClassifierData
Licenses: Artistic License 2.0
Build system: r
Synopsis: Pre-processed data for use with the sampleClassifier package
Description:

This package contains two microarray and two RNA-seq datasets that have been preprocessed for use with the sampleClassifier package. The RNA-seq data are derived from Fagerberg et al. (2014) and the Illumina Body Map 2.0 data. The microarray data are derived from Roth et al. (2006) and Ge et al. (2005).

Total results: 2911