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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-compspot 1.8.0
Propagated dependencies: r-plotly@4.11.0 r-magrittr@2.0.4 r-gridextra@2.3 r-ggpubr@0.6.2 r-ggplot2@4.0.1 r-data-table@1.17.8
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://github.com/sydney-grant/compSPOT
Licenses: Artistic License 2.0
Build system: r
Synopsis: compSPOT: Tool for identifying and comparing significantly mutated genomic hotspots
Description:

Clonal cell groups share common mutations within cancer, precancer, and even clinically normal appearing tissues. The frequency and location of these mutations may predict prognosis and cancer risk. It has also been well established that certain genomic regions have increased sensitivity to acquiring mutations. Mutation-sensitive genomic regions may therefore serve as markers for predicting cancer risk. This package contains multiple functions to establish significantly mutated hotspots, compare hotspot mutation burden between samples, and perform exploratory data analysis of the correlation between hotspot mutation burden and personal risk factors for cancer, such as age, gender, and history of carcinogen exposure. This package allows users to identify robust genomic markers to help establish cancer risk.

r-crisprscoredata 1.14.0
Propagated dependencies: r-experimenthub@3.0.0 r-annotationhub@4.0.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://github.com/crisprVerse/crisprScoreData/issues
Licenses: Expat
Build system: r
Synopsis: Pre-trained models for the crisprScore package
Description:

This package provides an interface to access pre-trained models for on-target and off-target gRNA activity prediction algorithms implemented in the crisprScore package. Pre-trained model data are stored in the ExperimentHub database. Users should consider using the crisprScore package directly to use and load the pre-trained models.

r-chickenprobe 2.18.0
Propagated dependencies: r-annotationdbi@1.72.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://bioconductor.org/packages/chickenprobe
Licenses: LGPL 2.0+
Build system: r
Synopsis: Probe sequence data for microarrays of type chicken
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 Chicken\_probe\_tab.

r-ctdquerier 2.18.0
Propagated dependencies: r-stringr@1.6.0 r-stringdist@0.9.15 r-s4vectors@0.48.0 r-rcurl@1.98-1.17 r-igraph@2.2.1 r-gridextra@2.3 r-ggplot2@4.0.1 r-biocfilecache@3.0.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://bioconductor.org/packages/CTDquerier
Licenses: Expat
Build system: r
Synopsis: Package for CTDbase data query, visualization and downstream analysis
Description:

Package to retrieve and visualize data from the Comparative Toxicogenomics Database (http://ctdbase.org/). The downloaded data is formated as DataFrames for further downstream analyses.

r-crupr 1.2.0
Propagated dependencies: r-txdb-mmusculus-ucsc-mm9-knowngene@3.2.2 r-txdb-mmusculus-ucsc-mm10-knowngene@3.10.0 r-txdb-hsapiens-ucsc-hg38-knowngene@3.22.0 r-txdb-hsapiens-ucsc-hg19-knowngene@3.22.1 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-reshape2@1.4.5 r-randomforest@4.7-1.2 r-preprocesscore@1.72.0 r-matrixstats@1.5.0 r-magrittr@2.0.4 r-iranges@2.44.0 r-ggplot2@4.0.1 r-genomicranges@1.62.0 r-genomicfeatures@1.62.0 r-genomicalignments@1.46.0 r-fs@1.6.6 r-dplyr@1.1.4 r-biocparallel@1.44.0 r-bamsignals@1.42.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://github.com/akbariomgba/crupR
Licenses: GPL 3
Build system: r
Synopsis: An R package to predict condition-specific enhancers from ChIP-seq data
Description:

An R package that offers a workflow to predict condition-specific enhancers from ChIP-seq data. The prediction of regulatory units is done in four main steps: Step 1 - the normalization of the ChIP-seq counts. Step 2 - the prediction of active enhancers binwise on the whole genome. Step 3 - the condition-specific clustering of the putative active enhancers. Step 4 - the detection of possible target genes of the condition-specific clusters using RNA-seq counts.

r-codelink 1.78.0
Propagated dependencies: r-limma@3.66.0 r-biocgenerics@0.56.0 r-biobase@2.70.0 r-annotate@1.88.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://github.com/ddiez/codelink
Licenses: GPL 2
Build system: r
Synopsis: Manipulation of Codelink microarray data
Description:

This package facilitates reading, preprocessing and manipulating Codelink microarray data. The raw data must be exported as text file using the Codelink software.

r-clustcomp 1.38.0
Propagated dependencies: r-sm@2.2-6.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://bioconductor.org/packages/clustComp
Licenses: GPL 2+
Build system: r
Synopsis: Clustering Comparison Package
Description:

clustComp is a package that implements several techniques for the comparison and visualisation of relationships between different clustering results, either flat versus flat or hierarchical versus flat. These relationships among clusters are displayed using a weighted bi-graph, in which the nodes represent the clusters and the edges connect pairs of nodes with non-empty intersection; the weight of each edge is the number of elements in that intersection and is displayed through the edge thickness. The best layout of the bi-graph is provided by the barycentre algorithm, which minimises the weighted number of crossings. In the case of comparing a hierarchical and a non-hierarchical clustering, the dendrogram is pruned at different heights, selected by exploring the tree by depth-first search, starting at the root. Branches are decided to be split according to the value of a scoring function, that can be based either on the aesthetics of the bi-graph or on the mutual information between the hierarchical and the flat clusterings. A mapping between groups of clusters from each side is constructed with a greedy algorithm, and can be additionally visualised.

r-canine-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/canine.db
Licenses: Artistic License 2.0
Build system: r
Synopsis: Affymetrix Affymetrix Canine Array annotation data (chip canine)
Description:

Affymetrix Affymetrix Canine Array annotation data (chip canine) assembled using data from public repositories.

r-cyanofilter 1.18.0
Propagated dependencies: r-mrfdepth@1.0.17 r-ggplot2@4.0.1 r-ggally@2.4.0 r-flowdensity@1.44.0 r-flowcore@2.22.0 r-flowclust@3.48.0 r-cytometree@2.0.6 r-biobase@2.70.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://github.com/fomotis/cyanoFilter
Licenses: Expat
Build system: r
Synopsis: Phytoplankton Population Identification using Cell Pigmentation and/or Complexity
Description:

An approach to filter out and/or identify phytoplankton cells from all particles measured via flow cytometry pigment and cell complexity information. It does this using a sequence of one-dimensional gates on pre-defined channels measuring certain pigmentation and complexity. The package is especially tuned for cyanobacteria, but will work fine for phytoplankton communities where there is at least one cell characteristic that differentiates every phytoplankton in the community.

r-cogito 1.16.0
Propagated dependencies: r-txdb-mmusculus-ucsc-mm9-knowngene@3.2.2 r-seqinfo@1.0.0 r-s4vectors@0.48.0 r-rmarkdown@2.30 r-magrittr@2.0.4 r-jsonlite@2.0.0 r-ggplot2@4.0.1 r-genomicranges@1.62.0 r-genomicfeatures@1.62.0 r-entropy@1.3.2 r-biocmanager@1.30.27 r-annotationdbi@1.72.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://bioconductor.org/packages/Cogito
Licenses: LGPL 3
Build system: r
Synopsis: Compare genomic intervals tool - Automated, complete, reproducible and clear report about genomic and epigenomic data sets
Description:

Biological studies often consist of multiple conditions which are examined with different laboratory set ups like RNA-sequencing or ChIP-sequencing. To get an overview about the whole resulting data set, Cogito provides an automated, complete, reproducible and clear report about all samples and basic comparisons between all different samples. This report can be used as documentation about the data set or as starting point for further custom analysis.

r-chromheatmap 1.64.0
Propagated dependencies: r-rtracklayer@1.70.0 r-iranges@2.44.0 r-genomicranges@1.62.0 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://bioconductor.org/packages/ChromHeatMap
Licenses: Artistic License 2.0
Build system: r
Synopsis: Heat map plotting by genome coordinate
Description:

The ChromHeatMap package can be used to plot genome-wide data (e.g. expression, CGH, SNP) along each strand of a given chromosome as a heat map. The generated heat map can be used to interactively identify probes and genes of interest.

r-clariomshumantranscriptcluster-db 8.8.0
Propagated dependencies: r-org-hs-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/clariomshumantranscriptcluster.db
Licenses: Artistic License 2.0
Build system: r
Synopsis: Affymetrix clariomshuman annotation data (chip clariomshumantranscriptcluster)
Description:

Affymetrix clariomshuman annotation data (chip clariomshumantranscriptcluster) assembled using data from public repositories.

r-curatedbladderdata 1.46.0
Propagated dependencies: r-affy@1.88.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://github.com/lima1/curatedBladderData
Licenses: Artistic License 2.0
Build system: r
Synopsis: Bladder Cancer Gene Expression Analysis
Description:

The curatedBladderData package provides relevant functions and data for gene expression analysis in patients with bladder cancer.

r-canine2probe 2.18.0
Propagated dependencies: r-annotationdbi@1.72.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://bioconductor.org/packages/canine2probe
Licenses: LGPL 2.0+
Build system: r
Synopsis: Probe sequence data for microarrays of type canine2
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 Canine\_2\_probe\_tab.

r-clippda 1.60.0
Propagated dependencies: r-statmod@1.5.1 r-scatterplot3d@0.3-44 r-rgl@1.3.31 r-limma@3.66.0 r-lattice@0.22-7 r-biobase@2.70.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: http://www.cancerstudies.bham.ac.uk/crctu/CLIPPDA.shtml
Licenses: FSDG-compatible
Build system: r
Synopsis: package for the clinical proteomic profiling data analysis
Description:

This package provides methods for the nalysis of data from clinical proteomic profiling studies. The focus is on the studies of human subjects, which are often observational case-control by design and have technical replicates. A method for sample size determination for planning these studies is proposed. It incorporates routines for adjusting for the expected heterogeneities and imbalances in the data and the within-sample replicate correlations.

r-curatedadipoarray 1.22.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://github.com/MahShaaban/curatedAdipoArray
Licenses: FSDG-compatible
Build system: r
Synopsis: Curated Microarrays Dataset of MDI-induced Differentiated Adipocytes (3T3-L1) Under Genetic and Pharmacological Perturbations
Description:

This package provides a curated dataset of Microarrays samples. The samples are MDI- induced pre-adipocytes (3T3-L1) at different time points/stage of differentiation under different types of genetic (knockdown/overexpression) and pharmacological (drug treatment) perturbations. The package documents the data collection and processing. In addition to the documentation, the package contains the scripts that was used to generated the data.

r-cellbarcode 1.16.0
Dependencies: zlib@1.3.1
Propagated dependencies: r-stringr@1.6.0 r-shortread@1.68.0 r-seqinr@4.2-36 r-s4vectors@0.48.0 r-rsamtools@2.26.0 r-rcpp@1.1.0 r-plyr@1.8.9 r-magrittr@2.0.4 r-ggplot2@4.0.1 r-egg@0.4.5 r-data-table@1.17.8 r-ckmeans-1d-dp@4.3.5 r-biostrings@2.78.0 r-bh@1.87.0-1
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://wenjie1991.github.io/CellBarcode/
Licenses: Artistic License 2.0
Build system: r
Synopsis: Cellular DNA Barcode Analysis toolkit
Description:

The package CellBarcode performs Cellular DNA Barcode analysis. It can handle all kinds of DNA barcodes, as long as the barcode is within a single sequencing read and has a pattern that can be matched by a regular expression. \codeCellBarcode can handle barcodes with flexible lengths, with or without UMI (unique molecular identifier). This tool also can be used for pre-processing some amplicon data such as CRISPR gRNA screening, immune repertoire sequencing, and metagenome data.

r-codex 1.42.0
Propagated dependencies: r-s4vectors@0.48.0 r-rsamtools@2.26.0 r-iranges@2.44.0 r-genomeinfodb@1.46.0 r-bsgenome-hsapiens-ucsc-hg19@1.4.3 r-biostrings@2.78.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://bioconductor.org/packages/CODEX
Licenses: GPL 2
Build system: r
Synopsis: Normalization and Copy Number Variation Detection Method for Whole Exome Sequencing
Description:

This package provides a normalization and copy number variation calling procedure for whole exome DNA sequencing data. CODEX relies on the availability of multiple samples processed using the same sequencing pipeline for normalization, and does not require matched controls. The normalization model in CODEX includes terms that specifically remove biases due to GC content, exon length and targeting and amplification efficiency, and latent systemic artifacts. CODEX also includes a Poisson likelihood-based recursive segmentation procedure that explicitly models the count-based exome sequencing data.

r-cma 1.68.0
Propagated dependencies: r-biobase@2.70.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://bioconductor.org/packages/CMA
Licenses: GPL 2+
Build system: r
Synopsis: Synthesis of microarray-based classification
Description:

This package provides a comprehensive collection of various microarray-based classification algorithms both from Machine Learning and Statistics. Variable Selection, Hyperparameter tuning, Evaluation and Comparison can be performed combined or stepwise in a user-friendly environment.

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-crisprbwa 1.14.0
Propagated dependencies: r-stringr@1.6.0 r-seqinfo@1.0.0 r-readr@2.1.6 r-rbwa@1.14.0 r-crisprbase@1.14.0 r-bsgenome@1.78.0 r-biocgenerics@0.56.0
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-cosmosr 1.18.0
Propagated dependencies: r-visnetwork@2.1.4 r-stringr@1.6.0 r-rlang@1.1.6 r-purrr@1.2.0 r-progress@1.2.3 r-igraph@2.2.1 r-gseabase@1.72.0 r-dplyr@1.1.4 r-dorothea@1.22.0 r-decoupler@2.16.0 r-carnival@2.20.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://github.com/saezlab/COSMOSR
Licenses: GPL 3
Build system: r
Synopsis: COSMOS (Causal Oriented Search of Multi-Omic Space)
Description:

COSMOS (Causal Oriented Search of Multi-Omic Space) is a method that integrates phosphoproteomics, transcriptomics, and metabolomics data sets based on prior knowledge of signaling, metabolic, and gene regulatory networks. It estimated the activities of transcrption factors and kinases and finds a network-level causal reasoning. Thereby, COSMOS provides mechanistic hypotheses for experimental observations across mulit-omics datasets.

r-cytokernel 1.16.0
Propagated dependencies: r-summarizedexperiment@1.40.0 r-s4vectors@0.48.0 r-rlang@1.1.6 r-rcpp@1.1.0 r-magrittr@2.0.4 r-dplyr@1.1.4 r-data-table@1.17.8 r-complexheatmap@2.26.0 r-circlize@0.4.16 r-biocparallel@1.44.0 r-ashr@2.2-63
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.

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