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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-scafari 1.0.0
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://github.com/sophiewind/scafari
Licenses: LGPL 3
Build system: r
Synopsis: Analysis of scDNA-seq data
Description:

Scafari is a Shiny application designed for the analysis of single-cell DNA sequencing (scDNA-seq) data provided in .h5 file format. The analysis process is structured into the four key steps "Sequencing", "Panel", "Variants", and "Explore Variants". It supports various analyses and visualizations.

r-sights 1.36.0
Propagated dependencies: r-reshape2@1.4.5 r-qvalue@2.42.0 r-mass@7.3-65 r-lattice@0.22-7 r-ggplot2@4.0.1
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://eg-r.github.io/sights/
Licenses: GPL 3 FSDG-compatible
Build system: r
Synopsis: Statistics and dIagnostic Graphs for HTS
Description:

SIGHTS is a suite of normalization methods, statistical tests, and diagnostic graphical tools for high throughput screening (HTS) assays. HTS assays use microtitre plates to screen large libraries of compounds for their biological, chemical, or biochemical activity.

r-scatterhatch 1.16.0
Propagated dependencies: r-spatstat-geom@3.6-1 r-plyr@1.8.9 r-ggplot2@4.0.1
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://github.com/FertigLab/scatterHatch
Licenses: Expat
Build system: r
Synopsis: Creates hatched patterns for scatterplots
Description:

The objective of this package is to efficiently create scatterplots where groups can be distinguished by color and texture. Visualizations in computational biology tend to have many groups making it difficult to distinguish between groups solely on color. Thus, this package is useful for increasing the accessibility of scatterplot visualizations to those with visual impairments such as color blindness.

r-svm2crmdata 1.42.0
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://bioconductor.org/packages/SVM2CRMdata
Licenses: LGPL 2.0+
Build system: r
Synopsis: An example dataset for use with the SVM2CRM package
Description:

An example dataset for use with the SVM2CRM package.

r-sevenc 1.30.0
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://github.com/ibn-salem/sevenC
Licenses: GPL 3
Build system: r
Synopsis: Computational Chromosome Conformation Capture by Correlation of ChIP-seq at CTCF motifs
Description:

Chromatin looping is an essential feature of eukaryotic genomes and can bring regulatory sequences, such as enhancers or transcription factor binding sites, in the close physical proximity of regulated target genes. Here, we provide sevenC, an R package that uses protein binding signals from ChIP-seq and sequence motif information to predict chromatin looping events. Cross-linking of proteins that bind close to loop anchors result in ChIP-seq signals at both anchor loci. These signals are used at CTCF motif pairs together with their distance and orientation to each other to predict whether they interact or not. The resulting chromatin loops might be used to associate enhancers or transcription factor binding sites (e.g., ChIP-seq peaks) to regulated target genes.

r-seqsqc 1.32.0
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://github.com/Liubuntu/SeqSQC
Licenses: GPL 3
Build system: r
Synopsis: bioconductor package for sample quality check with next generation sequencing data
Description:

The SeqSQC is designed to identify problematic samples in NGS data, including samples with gender mismatch, contamination, cryptic relatedness, and population outlier.

r-scthi 1.22.0
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://bioconductor.org/packages/scTHI
Licenses: GPL 2
Build system: r
Synopsis: Indentification of significantly activated ligand-receptor interactions across clusters of cells from single-cell RNA sequencing data
Description:

scTHI is an R package to identify active pairs of ligand-receptors from single cells in order to study,among others, tumor-host interactions. scTHI contains a set of signatures to classify cells from the tumor microenvironment.

r-spktools 1.66.0
Propagated dependencies: r-rcolorbrewer@1.1-3 r-gtools@3.9.5 r-biobase@2.70.0
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: http://bioconductor.org
Licenses: GPL 2+
Build system: r
Synopsis: Methods for Spike-in Arrays
Description:

The package contains functions that can be used to compare expression measures on different array platforms.

r-spaniel 1.24.0
Propagated dependencies: r-summarizedexperiment@1.40.0 r-singlecellexperiment@1.32.0 r-shiny@1.11.1 r-seurat@5.3.1 r-scran@1.38.0 r-scater@1.38.0 r-s4vectors@0.48.0 r-png@0.1-8 r-magrittr@2.0.4 r-jsonlite@2.0.0 r-jpeg@0.1-11 r-igraph@2.2.1 r-ggplot2@4.0.1 r-dropletutils@1.30.0 r-dplyr@1.1.4
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://bioconductor.org/packages/Spaniel
Licenses: Expat
Build system: r
Synopsis: Spatial Transcriptomics Analysis
Description:

Spaniel includes a series of tools to aid the quality control and analysis of Spatial Transcriptomics data. Spaniel can import data from either the original Spatial Transcriptomics system or 10X Visium technology. The package contains functions to create a SingleCellExperiment Seurat object and provides a method of loading a histologial image into R. The spanielPlot function allows visualisation of metrics contained within the S4 object overlaid onto the image of the tissue.

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-sigspack 1.24.0
Propagated dependencies: r-variantannotation@1.56.0 r-summarizedexperiment@1.40.0 r-rtracklayer@1.70.0 r-quadprog@1.5-8 r-genomicranges@1.62.0 r-genomeinfodb@1.46.0 r-bsgenome@1.78.0 r-biostrings@2.78.0 r-biobase@2.70.0
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://github.com/bihealth/SigsPack
Licenses: GPL 3
Build system: r
Synopsis: Mutational Signature Estimation for Single Samples
Description:

Single sample estimation of exposure to mutational signatures. Exposures to known mutational signatures are estimated for single samples, based on quadratic programming algorithms. Bootstrapping the input mutational catalogues provides estimations on the stability of these exposures. The effect of the sequence composition of mutational context can be taken into account by normalising the catalogues.

r-spatialsimgp 1.4.0
Propagated dependencies: r-summarizedexperiment@1.40.0 r-spatialexperiment@1.20.0 r-mass@7.3-65
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://github.com/kinnaryshah/spatialSimGP
Licenses: Expat
Build system: r
Synopsis: Simulate Spatial Transcriptomics Data with the Mean-variance Relationship
Description:

This packages simulates spatial transcriptomics data with the mean- variance relationship using a Gaussian Process model per gene.

r-summix 2.16.0
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://bioconductor.org/packages/Summix
Licenses: Expat
Build system: r
Synopsis: Summix2: A suite of methods to estimate, adjust, and leverage substructure in genetic summary data
Description:

This package contains the Summix2 method for estimating and adjusting for substructure in genetic summary allele frequency data. The function summix() estimates reference group proportions using a mixture model. The adjAF() function produces adjusted allele frequencies for an observed group with reference group proportions matching a target individual or sample. The summix_local() function estimates local ancestry mixture proportions and performs selection scans in genetic summary data.

r-selex 1.42.0
Dependencies: openjdk@25
Propagated dependencies: r-rjava@1.0-11 r-biostrings@2.78.0
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://bussemakerlab.org/site/software/
Licenses: FSDG-compatible
Build system: r
Synopsis: Functions for analyzing SELEX-seq data
Description:

This package provides tools for quantifying DNA binding specificities based on SELEX-seq data.

r-semdist 1.44.0
Propagated dependencies: r-go-db@3.22.0 r-annotationdbi@1.72.0 r-annotate@1.88.0
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: http://github.com/iangonzalez/SemDist
Licenses: GPL 2+
Build system: r
Synopsis: Information Accretion-based Function Predictor Evaluation
Description:

This package implements methods to calculate information accretion for a given version of the gene ontology and uses this data to calculate remaining uncertainty, misinformation, and semantic similarity for given sets of predicted annotations and true annotations from a protein function predictor.

r-sclane 1.0.4
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://github.com/jr-leary7/scLANE
Licenses: Expat
Build system: r
Synopsis: Model Gene Expression Dynamics with Spline-Based NB GLMs, GEEs, & GLMMs
Description:

Our scLANE model uses truncated power basis spline models to build flexible, interpretable models of single cell gene expression over pseudotime or latent time. The modeling architectures currently supported are Negative-binomial GLMs, GEEs, & GLMMs. Downstream analysis functionalities include model comparison, dynamic gene clustering, smoothed counts generation, gene set enrichment testing, & visualization.

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-scdiagnostics 1.4.0
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://github.com/ccb-hms/scDiagnostics
Licenses: Artistic License 2.0
Build system: r
Synopsis: Cell type annotation diagnostics
Description:

The scDiagnostics package provides diagnostic plots to assess the quality of cell type assignments from single cell gene expression profiles. The implemented functionality allows to assess the reliability of cell type annotations, investigate gene expression patterns, and explore relationships between different cell types in query and reference datasets allowing users to detect potential misalignments between reference and query datasets. The package also provides visualization capabilities for diagnostics purposes.

r-synapsis 1.16.0
Propagated dependencies: r-ebimage@4.52.0
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://bioconductor.org/packages/synapsis
Licenses: Expat
Build system: r
Synopsis: An R package to automate the analysis of double-strand break repair during meiosis
Description:

Synapsis is a Bioconductor software package for automated (unbiased and reproducible) analysis of meiotic immunofluorescence datasets. The primary functions of the software can i) identify cells in meiotic prophase that are labelled by a synaptonemal complex axis or central element protein, ii) isolate individual synaptonemal complexes and measure their physical length, iii) quantify foci and co-localise them with synaptonemal complexes, iv) measure interference between synaptonemal complex-associated foci. The software has applications that extend to multiple species and to the analysis of other proteins that label meiotic prophase chromosomes. The software converts meiotic immunofluorescence images into R data frames that are compatible with machine learning methods. Given a set of microscopy images of meiotic spread slides, synapsis crops images around individual single cells, counts colocalising foci on strands on a per cell basis, and measures the distance between foci on any given strand.

r-synergyfinder 3.18.0
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: http://www.synergyfinder.org
Licenses: FSDG-compatible
Build system: r
Synopsis: Calculate and Visualize Synergy Scores for Drug Combinations
Description:

Efficient implementations for analyzing pre-clinical multiple drug combination datasets. It provides efficient implementations for 1.the popular synergy scoring models, including HSA, Loewe, Bliss, and ZIP to quantify the degree of drug combination synergy; 2. higher order drug combination data analysis and synergy landscape visualization for unlimited number of drugs in a combination; 3. statistical analysis of drug combination synergy and sensitivity with confidence intervals and p-values; 4. synergy barometer for harmonizing multiple synergy scoring methods to provide a consensus metric of synergy; 5. evaluation of synergy and sensitivity simultaneously to provide an unbiased interpretation of the clinical potential of the drug combinations. Based on this package, we also provide a web application (http://www.synergyfinder.org) for users who prefer graphical user interface.

r-stjoincount 1.12.0
Propagated dependencies: r-summarizedexperiment@1.40.0 r-spdep@1.4-1 r-spatialexperiment@1.20.0 r-sp@2.2-0 r-seurat@5.3.1 r-raster@3.6-32 r-pheatmap@1.0.13 r-magrittr@2.0.4 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://github.com/Nina-Song/stJoincount
Licenses: Expat
Build system: r
Synopsis: stJoincount - Join count statistic for quantifying spatial correlation between clusters
Description:

stJoincount facilitates the application of join count analysis to spatial transcriptomic data generated from the 10x Genomics Visium platform. This tool first converts a labeled spatial tissue map into a raster object, in which each spatial feature is represented by a pixel coded by label assignment. This process includes automatic calculation of optimal raster resolution and extent for the sample. A neighbors list is then created from the rasterized sample, in which adjacent and diagonal neighbors for each pixel are identified. After adding binary spatial weights to the neighbors list, a multi-categorical join count analysis is performed to tabulate "joins" between all possible combinations of label pairs. The function returns the observed join counts, the expected count under conditions of spatial randomness, and the variance calculated under non-free sampling. The z-score is then calculated as the difference between observed and expected counts, divided by the square root of the variance.

r-spotclean 1.12.1
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://github.com/zijianni/SpotClean
Licenses: GPL 3
Build system: r
Synopsis: SpotClean adjusts for spot swapping in spatial transcriptomics data
Description:

SpotClean is a computational method to adjust for spot swapping in spatial transcriptomics data. Recent spatial transcriptomics experiments utilize slides containing thousands of spots with spot-specific barcodes that bind mRNA. Ideally, unique molecular identifiers at a spot measure spot-specific expression, but this is often not the case due to bleed from nearby spots, an artifact we refer to as spot swapping. SpotClean is able to estimate the contamination rate in observed data and decontaminate the spot swapping effect, thus increase the sensitivity and precision of downstream analyses.

r-slalom 1.32.0
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-srnadiff 1.30.0
Propagated dependencies: r-summarizedexperiment@1.40.0 r-seqinfo@1.0.0 r-s4vectors@0.48.0 r-rtracklayer@1.70.0 r-rsamtools@2.26.0 r-rcpp@1.1.0 r-iranges@2.44.0 r-gviz@1.54.0 r-genomicranges@1.62.0 r-genomicfeatures@1.62.0 r-genomicalignments@1.46.0 r-edger@4.8.0 r-deseq2@1.50.2 r-biocstyle@2.38.0 r-biocparallel@1.44.0 r-biocmanager@1.30.27
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://bioconductor.org/packages/srnadiff
Licenses: GPL 3
Build system: r
Synopsis: Finding differentially expressed unannotated genomic regions from RNA-seq data
Description:

srnadiff is a package that finds differently expressed regions from RNA-seq data at base-resolution level without relying on existing annotation. To do so, the package implements the identify-then-annotate methodology that builds on the idea of combining two pipelines approachs differential expressed regions detection and differential expression quantification. It reads BAM files as input, and outputs a list differentially regions, together with the adjusted p-values.

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Total results: 69112