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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-chromhmmdata 0.99.2
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://bioconductor.org/packages/chromhmmData
Licenses: GPL 3
Build system: r
Synopsis: Chromosome Size, Coordinates and Anchor Files
Description:

Annotation files of the formatted genomic annotation for ChromHMM. Three types of text files are included the chromosome sizes, region coordinates and anchors specifying the transcription start and end sites. The package includes data for two versions of the genome of humans and mice.

r-cellmigration 1.18.0
Propagated dependencies: r-vioplot@0.5.1 r-tiff@0.1-12 r-spatialtools@1.0.5 r-sp@2.2-0 r-reshape2@1.4.5 r-matrixstats@1.5.0 r-hmisc@5.2-4 r-foreach@1.5.2 r-fme@1.3.6.4 r-factominer@2.12 r-doparallel@1.0.17
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://github.com/ocbe-uio/cellmigRation/
Licenses: GPL 2
Build system: r
Synopsis: Track Cells, Analyze Cell Trajectories and Compute Migration Statistics
Description:

Import TIFF images of fluorescently labeled cells, and track cell movements over time. Parallelization is supported for image processing and for fast computation of cell trajectories. In-depth analysis of cell trajectories is enabled by 15 trajectory analysis functions.

r-canine2-db 3.13.0
Propagated dependencies: r-org-cf-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/canine2.db
Licenses: Artistic License 2.0
Build system: r
Synopsis: Affymetrix Affymetrix Canine_2 Array annotation data (chip canine2)
Description:

Affymetrix Affymetrix Canine_2 Array annotation data (chip canine2) assembled using data from public repositories.

r-cellmapperdata 1.36.0
Propagated dependencies: r-experimenthub@3.0.0 r-cellmapper@1.36.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://bioconductor.org/packages/CellMapperData
Licenses: Artistic License 2.0
Build system: r
Synopsis: Pre-processed data for use with the CellMapper package
Description:

Experiment data package. Contains microarray data from several large expression compendia that have been pre-processed for use with the CellMapper package. This pre-processed data is recommended for routine searches using the CellMapper package.

r-categorycompare 1.54.0
Propagated dependencies: r-rcy3@2.30.0 r-hwriter@1.3.2.1 r-gseabase@1.72.0 r-graph@1.88.0 r-gostats@2.76.0 r-colorspace@2.1-2 r-category@2.76.0 r-biocgenerics@0.56.0 r-biobase@2.70.0 r-annotationdbi@1.72.0 r-annotate@1.88.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://github.com/rmflight/categoryCompare
Licenses: GPL 2
Build system: r
Synopsis: Meta-analysis of high-throughput experiments using feature annotations
Description:

Calculates significant annotations (categories) in each of two (or more) feature (i.e. gene) lists, determines the overlap between the annotations, and returns graphical and tabular data about the significant annotations and which combinations of feature lists the annotations were found to be significant. Interactive exploration is facilitated through the use of RCytoscape (heavily suggested).

r-clustall 1.6.0
Propagated dependencies: r-rcolorbrewer@1.1-3 r-pbapply@1.7-4 r-networkd3@0.4.1 r-modeest@2.4.0 r-mice@3.18.0 r-ggplot2@4.0.1 r-fpc@2.2-13 r-foreach@1.5.2 r-flock@0.7 r-factominer@2.12 r-dplyr@1.1.4 r-dosnow@1.0.20 r-complexheatmap@2.26.0 r-clvalid@0.7 r-cluster@2.1.8.1 r-circlize@0.4.16 r-bigstatsr@1.6.2
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://bioconductor.org/packages/ClustAll
Licenses: GPL 2
Build system: r
Synopsis: ClustAll: Data driven strategy to robustly identify stratification of patients within complex diseases
Description:

Data driven strategy to find hidden groups of patients with complex diseases using clinical data. ClustAll facilitates the unsupervised identification of multiple robust stratifications. ClustAll, is able to overcome the most common limitations found when dealing with clinical data (missing values, correlated data, mixed data types).

r-centreprecomputed 1.0.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://github.com/slrvv/CENTREprecomputed
Licenses: Artistic License 2.0
Build system: r
Synopsis: Hub package for the precomputed data of CENTRE and example data
Description:

Interface and documentation for the Experiment Hub records needed by the CENTRE Bioconductor software package. The Experiment Hub records contains the precomputed fisher combined p-values, CRUP correlations. Additionally, the records hold ChIP-seq and RNA-seq data used for the example of the software package.

r-cnvmetrics 1.14.2
Propagated dependencies: r-s4vectors@0.48.0 r-rbeta2009@1.0.1 r-pheatmap@1.0.13 r-magrittr@2.0.4 r-iranges@2.44.0 r-gridextra@2.3 r-genomicranges@1.62.0 r-biocparallel@1.44.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://github.com/krasnitzlab/CNVMetrics
Licenses: Artistic License 2.0
Build system: r
Synopsis: Copy Number Variant Metrics
Description:

The CNVMetrics package calculates similarity metrics to facilitate copy number variant comparison among samples and/or methods. Similarity metrics can be employed to compare CNV profiles of genetically unrelated samples as well as those with a common genetic background. Some metrics are based on the shared amplified/deleted regions while other metrics rely on the level of amplification/deletion. The data type used as input is a plain text file containing the genomic position of the copy number variations, as well as the status and/or the log2 ratio values. Finally, a visualization tool is provided to explore resulting metrics.

r-clst 1.58.0
Propagated dependencies: r-roc@1.86.0 r-lattice@0.22-7
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://bioconductor.org/packages/clst
Licenses: GPL 3
Build system: r
Synopsis: Classification by local similarity threshold
Description:

Package for modified nearest-neighbor classification based on calculation of a similarity threshold distinguishing within-group from between-group comparisons.

r-celltrails 1.28.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://bioconductor.org/packages/CellTrails
Licenses: Artistic License 2.0
Build system: r
Synopsis: Reconstruction, visualization and analysis of branching trajectories
Description:

CellTrails is an unsupervised algorithm for the de novo chronological ordering, visualization and analysis of single-cell expression data. CellTrails makes use of a geometrically motivated concept of lower-dimensional manifold learning, which exhibits a multitude of virtues that counteract intrinsic noise of single cell data caused by drop-outs, technical variance, and redundancy of predictive variables. CellTrails enables the reconstruction of branching trajectories and provides an intuitive graphical representation of expression patterns along all branches simultaneously. It allows the user to define and infer the expression dynamics of individual and multiple pathways towards distinct phenotypes.

r-citefuse 1.22.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://bioconductor.org/packages/CiteFuse
Licenses: GPL 3
Build system: r
Synopsis: CiteFuse: multi-modal analysis of CITE-seq data
Description:

CiteFuse pacakage implements a suite of methods and tools for CITE-seq data from pre-processing to integrative analytics, including doublet detection, network-based modality integration, cell type clustering, differential RNA and protein expression analysis, ADT evaluation, ligand-receptor interaction analysis, and interactive web-based visualisation of the analyses.

r-cytokernel 1.16.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://bioconductor.org/packages/cytoKernel
Licenses: GPL 3
Build system: r
Synopsis: Differential expression using kernel-based score test
Description:

cytoKernel implements a kernel-based score test to identify differentially expressed features in high-dimensional biological experiments. This approach can be applied across many different high-dimensional biological data including gene expression data and dimensionally reduced cytometry-based marker expression data. In this R package, we implement functions that compute the feature-wise p values and their corresponding adjusted p values. Additionally, it also computes the feature-wise shrunk effect sizes and their corresponding shrunken effect size. Further, it calculates the percent of differentially expressed features and plots user-friendly heatmap of the top differentially expressed features on the rows and samples on the columns.

r-customcmpdb 1.20.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://github.com/yduan004/customCMPdb/
Licenses: Artistic License 2.0
Build system: r
Synopsis: Customize and Query Compound Annotation Database
Description:

This package serves as a query interface for important community collections of small molecules, while also allowing users to include custom compound collections.

r-cogena 1.44.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://github.com/zhilongjia/cogena
Licenses: LGPL 3
Build system: r
Synopsis: co-expressed gene-set enrichment analysis
Description:

cogena is a workflow for co-expressed gene-set enrichment analysis. It aims to discovery smaller scale, but highly correlated cellular events that may be of great biological relevance. A novel pipeline for drug discovery and drug repositioning based on the cogena workflow is proposed. Particularly, candidate drugs can be predicted based on the gene expression of disease-related data, or other similar drugs can be identified based on the gene expression of drug-related data. Moreover, the drug mode of action can be disclosed by the associated pathway analysis. In summary, cogena is a flexible workflow for various gene set enrichment analysis for co-expressed genes, with a focus on pathway/GO analysis and drug repositioning.

r-chevreulshiny 1.2.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://github.com/whtns/chevreulShiny
Licenses: Expat
Build system: r
Synopsis: Tools for managing SingleCellExperiment objects as projects
Description:

This package provides tools for managing SingleCellExperiment objects as projects. Includes functions for analysis and visualization of single-cell data. Also included is a shiny app for visualization of pre-processed scRNA data. Supported by NIH grants R01CA137124 and R01EY026661 to David Cobrinik.

r-comethdmr 1.14.0
Propagated dependencies: r-lmertest@3.1-3 r-iranges@2.44.0 r-genomicranges@1.62.0 r-experimenthub@3.0.0 r-bumphunter@1.52.0 r-biocparallel@1.44.0 r-annotationhub@4.0.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://github.com/TransBioInfoLab/coMethDMR
Licenses: GPL 3
Build system: r
Synopsis: Accurate identification of co-methylated and differentially methylated regions in epigenome-wide association studies
Description:

coMethDMR identifies genomic regions associated with continuous phenotypes by optimally leverages covariations among CpGs within predefined genomic regions. Instead of testing all CpGs within a genomic region, coMethDMR carries out an additional step that selects co-methylated sub-regions first without using any outcome information. Next, coMethDMR tests association between methylation within the sub-region and continuous phenotype using a random coefficient mixed effects model, which models both variations between CpG sites within the region and differential methylation simultaneously.

r-curatedadipochip 1.26.0
Propagated dependencies: r-summarizedexperiment@1.40.0 r-experimenthub@3.0.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://github.com/MahShaaban/curatedAdipoChIP
Licenses: GPL 3
Build system: r
Synopsis: Curated ChIP-Seq Dataset of MDI-induced Differentiated Adipocytes (3T3-L1)
Description:

This package provides a curated dataset of publicly available ChIP-sequencing of transcription factors, chromatin remodelers and histone modifications in the 3T3-L1 pre-adipocyte cell line. The package document the data collection, pre-processing and processing of the data. In addition to the documentation, the package contains the scripts that was used to generated the data.

r-cnvfilter 1.24.0
Propagated dependencies: r-variantannotation@1.56.0 r-summarizedexperiment@1.40.0 r-rsamtools@2.26.0 r-regioner@1.42.0 r-pracma@2.4.6 r-karyoploter@1.36.0 r-iranges@2.44.0 r-genomicranges@1.62.0 r-genomeinfodb@1.46.0 r-copynumberplots@1.26.0 r-biostrings@2.78.0 r-assertthat@0.2.1
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://github.com/jpuntomarcos/CNVfilteR
Licenses: Artistic License 2.0
Build system: r
Synopsis: Identifies false positives of CNV calling tools by using SNV calls
Description:

CNVfilteR identifies those CNVs that can be discarded by using the single nucleotide variant (SNV) calls that are usually obtained in common NGS pipelines.

r-consensusde 1.28.0
Propagated dependencies: r-txdb-dmelanogaster-ucsc-dm3-ensgene@3.2.2 r-summarizedexperiment@1.40.0 r-s4vectors@0.48.0 r-ruvseq@1.44.0 r-rsamtools@2.26.0 r-rcolorbrewer@1.1-3 r-pcamethods@2.2.0 r-org-hs-eg-db@3.22.0 r-limma@3.66.0 r-genomicfeatures@1.62.0 r-genomicalignments@1.46.0 r-ensembldb@2.34.0 r-ensdb-hsapiens-v86@2.99.0 r-edger@4.8.0 r-edaseq@2.44.0 r-deseq2@1.50.2 r-dendextend@1.19.1 r-data-table@1.17.8 r-biostrings@2.78.0 r-biocparallel@1.44.0 r-biocgenerics@0.56.0 r-biobase@2.70.0 r-annotationdbi@1.72.0 r-airway@1.30.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://bioconductor.org/packages/consensusDE
Licenses: GPL 3
Build system: r
Synopsis: RNA-seq analysis using multiple algorithms
Description:

This package allows users to perform DE analysis using multiple algorithms. It seeks consensus from multiple methods. Currently it supports "Voom", "EdgeR" and "DESeq". It uses RUV-seq (optional) to remove unwanted sources of variation.

r-cellnoptr 1.56.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://bioconductor.org/packages/CellNOptR
Licenses: GPL 3
Build system: r
Synopsis: Training of boolean logic models of signalling networks using prior knowledge networks and perturbation data
Description:

This package does optimisation of boolean logic networks of signalling pathways based on a previous knowledge network and a set of data upon perturbation of the nodes in the network.

r-crisprbwa 1.14.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://github.com/crisprVerse/crisprBwa
Licenses: Expat
Build system: r
Synopsis: BWA-based alignment of CRISPR gRNA spacer sequences
Description:

This package provides a user-friendly interface to map on-targets and off-targets of CRISPR gRNA spacer sequences using bwa. The alignment is fast, and can be performed using either commonly-used or custom CRISPR nucleases. The alignment can work with any reference or custom genomes. Currently not supported on Windows machines.

r-cocoa 2.24.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: http://code.databio.org/COCOA/
Licenses: GPL 3
Build system: r
Synopsis: Coordinate Covariation Analysis
Description:

COCOA is a method for understanding epigenetic variation among samples. COCOA can be used with epigenetic data that includes genomic coordinates and an epigenetic signal, such as DNA methylation and chromatin accessibility data. To describe the method on a high level, COCOA quantifies inter-sample variation with either a supervised or unsupervised technique then uses a database of "region sets" to annotate the variation among samples. A region set is a set of genomic regions that share a biological annotation, for instance transcription factor (TF) binding regions, histone modification regions, or open chromatin regions. COCOA can identify region sets that are associated with epigenetic variation between samples and increase understanding of variation in your data.

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-cosmiq 1.44.0
Propagated dependencies: r-xcms@4.8.0 r-rcpp@1.1.0 r-pracma@2.4.6 r-massspecwavelet@1.76.0 r-faahko@1.50.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: http://www.bioconductor.org/packages/devel/bioc/html/cosmiq.html
Licenses: GPL 3
Build system: r
Synopsis: cosmiq - COmbining Single Masses Into Quantities
Description:

cosmiq is a tool for the preprocessing of liquid- or gas - chromatography mass spectrometry (LCMS/GCMS) data with a focus on metabolomics or lipidomics applications. To improve the detection of low abundant signals, cosmiq generates master maps of the mZ/RT space from all acquired runs before a peak detection algorithm is applied. The result is a more robust identification and quantification of low-intensity MS signals compared to conventional approaches where peak picking is performed in each LCMS/GCMS file separately. The cosmiq package builds on the xcmsSet object structure and can be therefore integrated well with the package xcms as an alternative preprocessing step.

Total results: 2911