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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.

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r-sspaths 1.24.0
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://bioconductor.org/packages/ssPATHS
Licenses: Expat
Build system: r
Synopsis: ssPATHS: Single Sample PATHway Score
Description:

This package generates pathway scores from expression data for single samples after training on a reference cohort. The score is generated by taking the expression of a gene set (pathway) from a reference cohort and performing linear discriminant analysis to distinguish samples in the cohort that have the pathway augmented and not. The separating hyperplane is then used to score new samples.

r-spatialde 1.16.0
Propagated dependencies: r-summarizedexperiment@1.40.0 r-spatialexperiment@1.20.0 r-scales@1.4.0 r-reticulate@1.44.1 r-matrix@1.7-4 r-gridextra@2.3 r-ggrepel@0.9.6 r-ggplot2@4.0.1 r-checkmate@2.3.3 r-basilisk@1.22.0
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://github.com/sales-lab/spatialDE
Licenses: Expat
Build system: r
Synopsis: R wrapper for SpatialDE
Description:

SpatialDE is a method to find spatially variable genes (SVG) from spatial transcriptomics data. This package provides wrappers to use the Python SpatialDE library in R, using reticulate and basilisk.

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-splots 1.76.0
Propagated dependencies: r-rcolorbrewer@1.1-3
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://bioconductor.org/packages/splots
Licenses: LGPL 2.0+
Build system: r
Synopsis: Visualization of high-throughput assays in microtitre plate or slide format
Description:

This package is here to support legacy usages of it, but it should not be used for new code development. It provides a single function, plotScreen, for visualising data in microtitre plate or slide format. As a better alternative for such functionality, please consider the platetools package on CRAN (https://cran.r-project.org/package=platetools and https://github.com/Swarchal/platetools), or ggplot2 (geom_raster, facet_wrap) as exemplified in the vignette of this package.

r-seventygenedata 1.46.0
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://bioconductor.org/packages/release/data/experiment/html/seventyGeneData.html
Licenses: Artistic License 2.0
Build system: r
Synopsis: ExpressionSets from the van't Veer and Van de Vijver breast cancer studies
Description:

Gene expression data for the two breast cancer cohorts published by van't Veer and Van de Vijver in 2002.

r-spotlight 1.14.0
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://github.com/MarcElosua/SPOTlight
Licenses: GPL 3
Build system: r
Synopsis: `SPOTlight`: Spatial Transcriptomics Deconvolution
Description:

`SPOTlight` provides a method to deconvolute spatial transcriptomics spots using a seeded NMF approach along with visualization tools to assess the results. Spatially resolved gene expression profiles are key to understand tissue organization and function. However, novel spatial transcriptomics (ST) profiling techniques lack single-cell resolution and require a combination with single-cell RNA sequencing (scRNA-seq) information to deconvolute the spatially indexed datasets. Leveraging the strengths of both data types, we developed SPOTlight, a computational tool that enables the integration of ST with scRNA-seq data to infer the location of cell types and states within a complex tissue. SPOTlight is centered around a seeded non-negative matrix factorization (NMF) regression, initialized using cell-type marker genes and non-negative least squares (NNLS) to subsequently deconvolute ST capture locations (spots).

r-spatialfeatureexperiment 1.12.1
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://github.com/pachterlab/SpatialFeatureExperiment
Licenses: Artistic License 2.0
Build system: r
Synopsis: Integrating SpatialExperiment with Simple Features in sf
Description:

This package provides a new S4 class integrating Simple Features with the R package sf to bring geospatial data analysis methods based on vector data to spatial transcriptomics. Also implements management of spatial neighborhood graphs and geometric operations. This pakage builds upon SpatialExperiment and SingleCellExperiment, hence methods for these parent classes can still be used.

r-segmenter 1.16.0
Propagated dependencies: r-summarizedexperiment@1.40.0 r-s4vectors@0.48.0 r-iranges@2.44.0 r-genomicranges@1.62.0 r-complexheatmap@2.26.0 r-chromhmmdata@0.99.2 r-chipseeker@1.46.1 r-bamsignals@1.42.0
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://bioconductor.org/packages/segmenter
Licenses: GPL 3
Build system: r
Synopsis: Perform Chromatin Segmentation Analysis in R by Calling ChromHMM
Description:

Chromatin segmentation analysis transforms ChIP-seq data into signals over the genome. The latter represents the observed states in a multivariate Markov model to predict the chromatin's underlying states. ChromHMM, written in Java, integrates histone modification datasets to learn the chromatin states de-novo. The goal of this package is to call chromHMM from within R, capture the output files in an S4 object and interface to other relevant Bioconductor analysis tools. In addition, segmenter provides functions to test, select and visualize the output of the segmentation.

r-scshapes 1.16.0
Propagated dependencies: r-vgam@1.1-13 r-pscl@1.5.9 r-matrix@1.7-4 r-mass@7.3-65 r-magrittr@2.0.4 r-emdbook@1.3.14 r-dgof@1.5.1 r-biocparallel@1.44.0
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://github.com/Malindrie/scShapes
Licenses: GPL 3
Build system: r
Synopsis: Statistical Framework for Modeling and Identifying Differential Distributions in Single-cell RNA-sequencing Data
Description:

We present a novel statistical framework for identifying differential distributions in single-cell RNA-sequencing (scRNA-seq) data between treatment conditions by modeling gene expression read counts using generalized linear models (GLMs). We model each gene independently under each treatment condition using error distributions Poisson (P), Negative Binomial (NB), Zero-inflated Poisson (ZIP) and Zero-inflated Negative Binomial (ZINB) with log link function and model based normalization for differences in sequencing depth. Since all four distributions considered in our framework belong to the same family of distributions, we first perform a Kolmogorov-Smirnov (KS) test to select genes belonging to the family of ZINB distributions. Genes passing the KS test will be then modeled using GLMs. Model selection is done by calculating the Bayesian Information Criterion (BIC) and likelihood ratio test (LRT) statistic.

r-switchbox 1.46.0
Propagated dependencies: r-proc@1.19.0.1 r-gplots@3.2.0
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://bioconductor.org/packages/switchBox
Licenses: GPL 2
Build system: r
Synopsis: Utilities to train and validate classifiers based on pair switching using the K-Top-Scoring-Pair (KTSP) algorithm
Description:

The package offer different classifiers based on comparisons of pair of features (TSP), using various decision rules (e.g., majority wins principle).

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-scvir 1.10.0
Propagated dependencies: r-summarizedexperiment@1.40.0 r-singlecellexperiment@1.32.0 r-shiny@1.11.1 r-scater@1.38.0 r-s4vectors@0.48.0 r-reticulate@1.44.1 r-pheatmap@1.0.13 r-matrixgenerics@1.22.0 r-limma@3.66.0 r-biocfilecache@3.0.0 r-basilisk@1.22.0
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://github.com/vjcitn/scviR
Licenses: Artistic License 2.0
Build system: r
Synopsis: experimental inferface from R to scvi-tools
Description:

This package defines interfaces from R to scvi-tools. A vignette works through the totalVI tutorial for analyzing CITE-seq data. Another vignette compares outputs of Chapter 12 of the OSCA book with analogous outputs based on totalVI quantifications. Future work will address other components of scvi-tools, with a focus on building understanding of probabilistic methods based on variational autoencoders.

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-signer 2.12.0
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://github.com/TojalLab/signeR
Licenses: GPL 3
Build system: r
Synopsis: Empirical Bayesian approach to mutational signature discovery
Description:

The signeR package provides an empirical Bayesian approach to mutational signature discovery. It is designed to analyze single nucleotide variation (SNV) counts in cancer genomes, but can also be applied to other features as well. Functionalities to characterize signatures or genome samples according to exposure patterns are also provided.

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-shinyepico 1.18.0
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://github.com/omorante/shiny_epico
Licenses: FSDG-compatible
Build system: r
Synopsis: ShinyÉPICo
Description:

ShinyÉPICo is a graphical pipeline to analyze Illumina DNA methylation arrays (450k or EPIC). It allows to calculate differentially methylated positions and differentially methylated regions in a user-friendly interface. Moreover, it includes several options to export the results and obtain files to perform downstream analysis.

r-single-mtec-transcriptomes 1.38.0
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://bioconductor.org/packages/Single.mTEC.Transcriptomes
Licenses: LGPL 2.0+
Build system: r
Synopsis: Single Cell Transcriptome Data and Analysis of Mouse mTEC cells
Description:

This data package contains the code used to analyse the single-cell RNA-seq and the bulk ATAC-seq data from the manuscript titled: Single-cell transcriptome analysis reveals coordinated ectopic-gene expression patterns in medullary thymic epithelial cells. This paper was published in Nature Immunology 16,933-941(2015). The data objects provided in this package has been pre-processed: the raw data files can be downloaded from ArrayExpress under the accession identifiers E-MTAB-3346 and E-MTAB-3624. The vignette of this data package provides a documented and reproducible workflow that includes the code that was used to generate each statistic and figure from the manuscript.

r-soybeanprobe 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/soybeanprobe
Licenses: LGPL 2.0+
Build system: r
Synopsis: Probe sequence data for microarrays of type soybean
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 Soybean\_probe\_tab.

r-scider 1.8.0
Propagated dependencies: r-uwot@0.2.4 r-summarizedexperiment@1.40.0 r-spatstat-geom@3.6-1 r-spatstat-explore@3.6-0 r-spatialpack@0.4-1 r-spatialexperiment@1.20.0 r-singlecellexperiment@1.32.0 r-shiny@1.11.1 r-sf@1.0-23 r-s4vectors@0.48.0 r-plotly@4.11.0 r-pheatmap@1.0.13 r-lwgeom@0.2-14 r-knitr@1.50 r-janitor@2.2.1 r-isoband@0.2.7 r-irlba@2.3.5.1 r-igraph@2.2.1 r-hexdensity@1.4.10 r-hexbin@1.28.5 r-ggplot2@4.0.1 r-dbscan@1.2.3 r-biocneighbors@2.4.0
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://github.com/ChenLaboratory/scider
Licenses: FSDG-compatible
Build system: r
Synopsis: Spatial cell-type inter-correlation by density in R
Description:

scider is an user-friendly R package providing functions to model the global density of cells in a slide of spatial transcriptomics data. All functions in the package are built based on the SpatialExperiment object, allowing integration into various spatial transcriptomics-related packages from Bioconductor. After modelling density, the package allows for serveral downstream analysis, including colocalization analysis, boundary detection analysis and differential density analysis.

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-splinetimer 1.38.0
Propagated dependencies: r-longitudinal@1.1.13 r-limma@3.66.0 r-igraph@2.2.1 r-gtools@3.9.5 r-gseabase@1.72.0 r-genenet@1.2.17 r-fis@1.38.0 r-biobase@2.70.0
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://bioconductor.org/packages/splineTimeR
Licenses: GPL 3
Build system: r
Synopsis: Time-course differential gene expression data analysis using spline regression models followed by gene association network reconstruction
Description:

This package provides functions for differential gene expression analysis of gene expression time-course data. Natural cubic spline regression models are used. Identified genes may further be used for pathway enrichment analysis and/or the reconstruction of time dependent gene regulatory association networks.

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-simffpe 1.22.0
Propagated dependencies: r-truncnorm@1.0-9 r-rsamtools@2.26.0 r-iranges@2.44.0 r-genomicranges@1.62.0 r-foreach@1.5.2 r-dplyr@1.1.4 r-doparallel@1.0.17 r-biostrings@2.78.0
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://bioconductor.org/packages/SimFFPE
Licenses: LGPL 3
Build system: r
Synopsis: NGS Read Simulator for FFPE Tissue
Description:

The NGS (Next-Generation Sequencing) reads from FFPE (Formalin-Fixed Paraffin-Embedded) samples contain numerous artifact chimeric reads (ACRS), which can lead to false positive structural variant calls. These ACRs are derived from the combination of two single-stranded DNA (ss-DNA) fragments with short reverse complementary regions (SRCRs). This package simulates these artifact chimeric reads as well as normal reads for FFPE samples on the whole genome / several chromosomes / large regions.

r-stpipe 1.0.1
Dependencies: zlib@1.3.1
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://github.com/mritchielab/stPipe
Licenses: GPL 3
Build system: r
Synopsis: Upstream pre-processing for Sequencing-Based Spatial Transcriptomics
Description:

This package serves as an upstream pipeline for pre-processing sequencing-based spatial transcriptomics data. Functions includes FASTQ trimming, BAM file reformatting, index building, spatial barcode detection, demultiplexing, gene count matrix generation with UMI deduplication, QC, and revelant visualization. Config is an essential input for most of the functions which aims to improve reproducibility.

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Total results: 69112