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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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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 search send a patch to ~whereiseveryone/toys@lists.sr.ht adding your channel as an entry in channels.scm.


r-cellmigration 1.20.0
Propagated dependencies: r-vioplot@0.5.1 r-tiff@0.1-12 r-spatialtools@1.0.5 r-sp@2.2-1 r-reshape2@1.4.5 r-matrixstats@1.5.0 r-hmisc@5.2-5 r-foreach@1.5.2 r-fme@1.3.6.4 r-factominer@2.13 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-cghmcr 1.70.0
Propagated dependencies: r-limma@3.66.0 r-dnacopy@1.84.0 r-cntools@1.68.0 r-biocgenerics@0.56.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://bioconductor.org/packages/cghMCR
Licenses: LGPL 2.0+
Build system: r
Synopsis: Find chromosome regions showing common gains/losses
Description:

This package provides functions to identify genomic regions of interests based on segmented copy number data from multiple samples.

r-ctsge 1.38.0
Propagated dependencies: r-stringr@1.6.0 r-shiny@1.11.1 r-reshape2@1.4.5 r-limma@3.66.0 r-ggplot2@4.0.2 r-ccapp@0.3.5
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://github.com/michalsharabi/ctsGE
Licenses: GPL 2
Build system: r
Synopsis: Clustering of Time Series Gene Expression data
Description:

Methodology for supervised clustering of potentially many predictor variables, such as genes etc., in time series datasets Provides functions that help the user assigning genes to predefined set of model profiles.

r-connectivitymap 1.48.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://bioconductor.org/packages/ConnectivityMap
Licenses: GPL 3
Build system: r
Synopsis: Functional connections between drugs, genes and diseases as revealed by common gene-expression changes
Description:

The Broad Institute's Connectivity Map (cmap02) is a "large reference catalogue of gene-expression data from cultured human cells perturbed with many chemicals and genetic reagents", containing more than 7000 gene expression profiles and 1300 small molecules.

r-combi 1.24.0
Propagated dependencies: r-vegan@2.7-2 r-tensor@1.5.1 r-summarizedexperiment@1.40.0 r-reshape2@1.4.5 r-phyloseq@1.54.1 r-nleqslv@3.3.5 r-matrix@1.7-4 r-limma@3.66.0 r-ggplot2@4.0.2 r-dbi@1.3.0 r-cobs@1.3-9-1 r-biobase@2.70.0 r-bb@2026.1.0 r-alabama@2025.1.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://bioconductor.org/packages/combi
Licenses: GPL 2
Build system: r
Synopsis: Compositional omics model based visual integration
Description:

This explorative ordination method combines quasi-likelihood estimation, compositional regression models and latent variable models for integrative visualization of several omics datasets. Both unconstrained and constrained integration are available. The results are shown as interpretable, compositional multiplots.

r-cimice 1.20.0
Propagated dependencies: r-visnetwork@2.1.4 r-tidyr@1.3.2 r-tidygraph@1.3.1 r-purrr@1.2.1 r-networkd3@0.4.1 r-matrix@1.7-4 r-maftools@2.26.0 r-igraph@2.2.2 r-glue@1.8.0 r-ggraph@2.2.2 r-ggplot2@4.0.2 r-ggcorrplot@0.1.4.1 r-expm@1.0-0 r-dplyr@1.2.0 r-assertthat@0.2.1
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://github.com/redsnic/CIMICE
Licenses: Artistic License 2.0
Build system: r
Synopsis: CIMICE-R: (Markov) Chain Method to Inferr Cancer Evolution
Description:

CIMICE is a tool in the field of tumor phylogenetics and its goal is to build a Markov Chain (called Cancer Progression Markov Chain, CPMC) in order to model tumor subtypes evolution. The input of CIMICE is a Mutational Matrix, so a boolean matrix representing altered genes in a collection of samples. These samples are assumed to be obtained with single-cell DNA analysis techniques and the tool is specifically written to use the peculiarities of this data for the CMPC construction.

r-chimphumanbraindata 1.50.0
Propagated dependencies: r-statmod@1.5.1 r-qvalue@2.42.0 r-limma@3.66.0 r-hexbin@1.28.5 r-affy@1.88.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://bioconductor.org/packages/ChimpHumanBrainData
Licenses: Expat
Build system: r
Synopsis: Chimp and human brain data package
Description:

This data package contains chimp and human brain data extracted from the ArrayExpress accession E-AFMX-2. Both human and chimp RNAs were run on human hgu95av2 Affymetrix arrays. It is a useful dataset for tutorials.

r-ccdata 1.38.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://bioconductor.org/packages/ccdata
Licenses: Expat
Build system: r
Synopsis: Data for Combination Connectivity Mapping (ccmap) Package
Description:

This package contains microarray gene expression data generated from the Connectivity Map build 02 and LINCS l1000. The data are used by the ccmap package to find drugs and drug combinations to mimic or reverse a gene expression signature.

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-cytopipelinegui 1.10.0
Propagated dependencies: r-shiny@1.11.1 r-plotly@4.12.0 r-ggplot2@4.0.2 r-flowcore@2.22.1 r-cytopipeline@1.12.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://uclouvain-cbio.github.io/CytoPipelineGUI
Licenses: GPL 3
Build system: r
Synopsis: GUI's for visualization of flow cytometry data analysis pipelines
Description:

This package is the companion of the `CytoPipeline` package. It provides GUI's (shiny apps) for the visualization of flow cytometry data analysis pipelines that are run with `CytoPipeline`. Two shiny applications are provided, i.e. an interactive flow frame assessment and comparison tool and an interactive scale transformations visualization and adjustment tool.

r-celaref 1.30.0
Propagated dependencies: r-tibble@3.3.1 r-summarizedexperiment@1.40.0 r-s4vectors@0.48.0 r-rlang@1.1.7 r-readr@2.2.0 r-matrix@1.7-4 r-mast@1.36.0 r-magrittr@2.0.4 r-ggplot2@4.0.2 r-dplyr@1.2.0 r-delayedarray@0.36.0 r-biocgenerics@0.56.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://bioconductor.org/packages/celaref
Licenses: GPL 3
Build system: r
Synopsis: Single-cell RNAseq cell cluster labelling by reference
Description:

After the clustering step of a single-cell RNAseq experiment, this package aims to suggest labels/cell types for the clusters, on the basis of similarity to a reference dataset. It requires a table of read counts per cell per gene, and a list of the cells belonging to each of the clusters, (for both test and reference data).

r-dorothea 1.23.0
Propagated dependencies: r-magrittr@2.0.4 r-dplyr@1.2.0 r-decoupler@2.16.0 r-bcellviper@1.46.0
Channel: guix-bioc
Location: guix-bioc/packages/d.scm (guix-bioc packages d)
Home page: https://saezlab.github.io/dorothea/
Licenses: FSDG-compatible
Build system: r
Synopsis: Collection Of Human And Mouse TF Regulons
Description:

DoRothEA is a gene regulatory network containing signed transcription factor (TF) - target gene interactions. DoRothEA regulons, the collection of a TF and its transcriptional targets, were curated and collected from different types of evidence for both human and mouse. A confidence level was assigned to each TF-target interaction based on the number of supporting evidence.

r-drugvsdisease 2.54.0
Propagated dependencies: r-xtable@1.8-8 r-runit@0.4.33.1 r-qvalue@2.42.0 r-limma@3.66.0 r-hgu133plus2-db@3.13.0 r-hgu133a2-db@3.13.0 r-hgu133a-db@3.13.0 r-geoquery@2.78.0 r-drugvsdiseasedata@1.48.0 r-cmap2data@1.48.0 r-biomart@2.66.1 r-biocgenerics@0.56.0 r-arrayexpress@1.70.0 r-annotate@1.88.0 r-affy@1.88.0
Channel: guix-bioc
Location: guix-bioc/packages/d.scm (guix-bioc packages d)
Home page: https://bioconductor.org/packages/DrugVsDisease
Licenses: GPL 3
Build system: r
Synopsis: Comparison of disease and drug profiles using Gene set Enrichment Analysis
Description:

This package generates ranked lists of differential gene expression for either disease or drug profiles. Input data can be downloaded from Array Express or GEO, or from local CEL files. Ranked lists of differential expression and associated p-values are calculated using Limma. Enrichment scores (Subramanian et al. PNAS 2005) are calculated to a reference set of default drug or disease profiles, or a set of custom data supplied by the user. Network visualisation of significant scores are output in Cytoscape format.

r-donapllp2013 1.50.0
Propagated dependencies: r-ebimage@4.52.0
Channel: guix-bioc
Location: guix-bioc/packages/d.scm (guix-bioc packages d)
Home page: https://bioconductor.org/packages/DonaPLLP2013
Licenses: Artistic License 2.0
Build system: r
Synopsis: Supplementary data package for Dona et al. (2013) containing example images and tables
Description:

An experiment data package associated with the publication Dona et al. (2013). Package contains runnable vignettes showing an example image segmentation for one posterior lateral line primordium, and also the data table and code used to analyze tissue-scale lifetime-ratio statistics.

r-dmcfb 1.26.0
Propagated dependencies: r-tibble@3.3.1 r-summarizedexperiment@1.40.0 r-speedglm@0.3-5 r-s4vectors@0.48.0 r-rtracklayer@1.70.1 r-matrixstats@1.5.0 r-mass@7.3-65 r-iranges@2.44.0 r-genomicranges@1.62.1 r-fastdummies@1.7.5 r-data-table@1.18.2.1 r-biocparallel@1.44.0 r-benchmarkme@1.0.8 r-arm@1.14-4
Channel: guix-bioc
Location: guix-bioc/packages/d.scm (guix-bioc packages d)
Home page: https://bioconductor.org/packages/DMCFB
Licenses: GPL 3
Build system: r
Synopsis: Differentially Methylated Cytosines via a Bayesian Functional Approach
Description:

DMCFB is a pipeline for identifying differentially methylated cytosines using a Bayesian functional regression model in bisulfite sequencing data. By using a functional regression data model, it tries to capture position-specific, group-specific and other covariates-specific methylation patterns as well as spatial correlation patterns and unknown underlying models of methylation data. It is robust and flexible with respect to the true underlying models and inclusion of any covariates, and the missing values are imputed using spatial correlation between positions and samples. A Bayesian approach is adopted for estimation and inference in the proposed method.

r-dcgsa 1.40.0
Propagated dependencies: r-matrix@1.7-4 r-biocparallel@1.44.0
Channel: guix-bioc
Location: guix-bioc/packages/d.scm (guix-bioc packages d)
Home page: https://bioconductor.org/packages/dcGSA
Licenses: GPL 2
Build system: r
Synopsis: Distance-correlation based Gene Set Analysis for longitudinal gene expression profiles
Description:

Distance-correlation based Gene Set Analysis for longitudinal gene expression profiles. In longitudinal studies, the gene expression profiles were collected at each visit from each subject and hence there are multiple measurements of the gene expression profiles for each subject. The dcGSA package could be used to assess the associations between gene sets and clinical outcomes of interest by fully taking advantage of the longitudinal nature of both the gene expression profiles and clinical outcomes.

r-degraph 1.64.0
Propagated dependencies: r-rrcov@1.7-7 r-rgraphviz@2.54.0 r-rbgl@1.86.0 r-r-utils@2.13.0 r-r-methodss3@1.8.2 r-ncigraph@1.60.0 r-mvtnorm@1.3-3 r-lattice@0.22-9 r-kegggraph@1.70.0 r-graph@1.88.1
Channel: guix-bioc
Location: guix-bioc/packages/d.scm (guix-bioc packages d)
Home page: https://bioconductor.org/packages/DEGraph
Licenses: GPL 3
Build system: r
Synopsis: Two-sample tests on a graph
Description:

DEGraph implements recent hypothesis testing methods which directly assess whether a particular gene network is differentially expressed between two conditions. This is to be contrasted with the more classical two-step approaches which first test individual genes, then test gene sets for enrichment in differentially expressed genes. These recent methods take into account the topology of the network to yield more powerful detection procedures. DEGraph provides methods to easily test all KEGG pathways for differential expression on any gene expression data set and tools to visualize the results.

r-deltacapturec 1.26.0
Propagated dependencies: r-tictoc@1.2.1 r-summarizedexperiment@1.40.0 r-iranges@2.44.0 r-ggplot2@4.0.2 r-genomicranges@1.62.1 r-deseq2@1.50.2
Channel: guix-bioc
Location: guix-bioc/packages/d.scm (guix-bioc packages d)
Home page: https://bioconductor.org/packages/deltaCaptureC
Licenses: Expat
Build system: r
Synopsis: This Package Discovers Meso-scale Chromatin Remodeling from 3C Data
Description:

This package discovers meso-scale chromatin remodelling from 3C data. 3C data is local in nature. It givens interaction counts between restriction enzyme digestion fragments and a preferred viewpoint region. By binning this data and using permutation testing, this package can test whether there are statistically significant changes in the interaction counts between the data from two cell types or two treatments.

r-dar 1.8.0
Propagated dependencies: r-upsetr@1.4.0 r-tidyr@1.3.2 r-tibble@3.3.1 r-stringr@1.6.0 r-scales@1.4.0 r-rlang@1.1.7 r-readr@2.2.0 r-purrr@1.2.1 r-phyloseq@1.54.1 r-mia@1.18.0 r-magrittr@2.0.4 r-heatmaply@1.6.0 r-gplots@3.3.0 r-glue@1.8.0 r-ggplot2@4.0.2 r-generics@0.1.4 r-dplyr@1.2.0 r-crayon@1.5.3 r-complexheatmap@2.26.1 r-cli@3.6.5 r-checkmate@2.3.4
Channel: guix-bioc
Location: guix-bioc/packages/d.scm (guix-bioc packages d)
Home page: https://github.com/MicrobialGenomics-IrsicaixaOrg/dar
Licenses: Expat
Build system: r
Synopsis: Differential Abundance Analysis by Consensus
Description:

Differential abundance testing in microbiome data challenges both parametric and non-parametric statistical methods, due to its sparsity, high variability and compositional nature. Microbiome-specific statistical methods often assume classical distribution models or take into account compositional specifics. These produce results that range within the specificity vs sensitivity space in such a way that type I and type II error that are difficult to ascertain in real microbiome data when a single method is used. Recently, a consensus approach based on multiple differential abundance (DA) methods was recently suggested in order to increase robustness. With dar, you can use dplyr-like pipeable sequences of DA methods and then apply different consensus strategies. In this way we can obtain more reliable results in a fast, consistent and reproducible way.

r-delocal 1.12.0
Propagated dependencies: r-summarizedexperiment@1.40.0 r-reshape2@1.4.5 r-matrixstats@1.5.0 r-limma@3.66.0 r-ggplot2@4.0.2 r-dplyr@1.2.0 r-deseq2@1.50.2
Channel: guix-bioc
Location: guix-bioc/packages/d.scm (guix-bioc packages d)
Home page: https://github.com/dasroy/DELocal
Licenses: Expat
Build system: r
Synopsis: Identifies differentially expressed genes with respect to other local genes
Description:

The goal of DELocal is to identify DE genes compared to their neighboring genes from the same chromosomal location. It has been shown that genes of related functions are generally very far from each other in the chromosome. DELocal utilzes this information to identify DE genes comparing with their neighbouring genes.

r-duplexdiscoverer 1.6.0
Propagated dependencies: r-vctrs@0.7.1 r-tidyr@1.3.2 r-tibble@3.3.1 r-stringr@1.6.0 r-scales@1.4.0 r-rtracklayer@1.70.1 r-rlang@1.1.7 r-purrr@1.2.1 r-interactionset@1.38.0 r-igraph@2.2.2 r-gviz@1.54.0 r-ggsci@4.2.0 r-genomicranges@1.62.1 r-genomicalignments@1.46.0 r-genomeinfodb@1.46.2 r-dplyr@1.2.0 r-biostrings@2.78.0
Channel: guix-bioc
Location: guix-bioc/packages/d.scm (guix-bioc packages d)
Home page: https://github.com/Egors01/DuplexDiscovereR/
Licenses: GPL 3
Build system: r
Synopsis: Analysis of the data from RNA duplex probing experiments
Description:

DuplexDiscovereR is a package designed for analyzing data from RNA cross-linking and proximity ligation protocols such as SPLASH, PARIS, LIGR-seq, and others. DuplexDiscovereR accepts input in the form of chimerically or split-aligned reads. It includes procedures for alignment classification, filtering, and efficient clustering of individual chimeric reads into duplex groups (DGs). Once DGs are identified, the package predicts RNA duplex formation and their hybridization energies. Additional metrics, such as p-values for random ligation hypothesis or mean DG alignment scores, can be calculated to rank final set of RNA duplexes. Data from multiple experiments or replicates can be processed separately and further compared to check the reproducibility of the experimental method.

r-dnacycp2 1.4.1
Propagated dependencies: r-reticulate@1.45.0 r-basilisk@1.22.0
Channel: guix-bioc
Location: guix-bioc/packages/d.scm (guix-bioc packages d)
Home page: https://github.com/jipingw/DNAcycP2
Licenses: Artistic License 2.0
Build system: r
Synopsis: DNA Cyclizability Prediction
Description:

This package performs prediction of intrinsic cyclizability of of every 50-bp subsequence in a DNA sequence. The input could be a file either in FASTA or text format. The output will be the C-score, the estimated intrinsic cyclizability score for each 50 bp sequences in each entry of the sequence set.

r-dvddata 1.48.0
Channel: guix-bioc
Location: guix-bioc/packages/d.scm (guix-bioc packages d)
Home page: https://bioconductor.org/packages/DvDdata
Licenses: GPL 3
Build system: r
Synopsis: Drug versus Disease Data
Description:

Data package which provides default drug and disease expression profiles for the DvD package.

r-dfplyr 1.6.0
Propagated dependencies: r-tidyselect@1.2.1 r-s4vectors@0.48.0 r-rlang@1.1.7 r-dplyr@1.2.0 r-biocgenerics@0.56.0
Channel: guix-bioc
Location: guix-bioc/packages/d.scm (guix-bioc packages d)
Home page: https://github.com/jonocarroll/DFplyr
Licenses: GPL 3
Build system: r
Synopsis: `DataFrame` (`S4Vectors`) backend for `dplyr`
Description:

This package provides `dplyr` verbs (`mutate`, `select`, `filter`, etc...) supporting `S4Vectors::DataFrame` objects. Importantly, this is achieved without conversion to an intermediate `tibble`. Adds grouping infrastructure to `DataFrame` which is respected by the transformation verbs.

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