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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-deltacapturec 1.24.0
Propagated dependencies: r-tictoc@1.2.1 r-summarizedexperiment@1.40.0 r-iranges@2.44.0 r-ggplot2@4.0.1 r-genomicranges@1.62.0 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-deconvobuddies 1.2.0
Channel: guix-bioc
Location: guix-bioc/packages/d.scm (guix-bioc packages d)
Home page: https://github.com/lahuuki/DeconvoBuddies
Licenses: Artistic License 2.0
Build system: r
Synopsis: Helper Functions for LIBD Deconvolution
Description:

Funtions helpful for LIBD deconvolution project. Includes tools for marker finding with mean ratio, expression plotting, and plotting deconvolution results. Working to include DLPFC datasets.

r-dmgsea 1.0.2
Propagated dependencies: r-summarizedexperiment@1.40.0 r-seqinfo@1.0.0 r-poolr@1.2-0 r-matrix@1.7-4 r-dqrng@0.4.1 r-biasedurn@2.0.12 r-annotationdbi@1.72.0
Channel: guix-bioc
Location: guix-bioc/packages/d.scm (guix-bioc packages d)
Home page: https://github.com/Bioconductor/dmGsea
Licenses: Artistic License 2.0
Build system: r
Synopsis: Efficient Gene Set Enrichment Analysis for DNA Methylation Data
Description:

The R package dmGsea provides efficient gene set enrichment analysis specifically for DNA methylation data. It addresses key biases, including probe dependency and varying probe numbers per gene. The package supports Illumina 450K, EPIC, and mouse methylation arrays. Users can also apply it to other omics data by supplying custom probe-to-gene mapping annotations. dmGsea is flexible, fast, and well-suited for large-scale epigenomic studies.

r-deeppincs 1.18.0
Propagated dependencies: r-webchem@1.3.1 r-ttgsea@1.18.0 r-tokenizers@0.3.0 r-tensorflow@2.20.0 r-stringdist@0.9.15 r-reticulate@1.44.1 r-rcdk@3.8.2 r-purrr@1.2.0 r-prroc@1.4 r-matlab@1.0.4.1 r-keras@2.16.1 r-catencoders@0.1.1
Channel: guix-bioc
Location: guix-bioc/packages/d.scm (guix-bioc packages d)
Home page: https://bioconductor.org/packages/DeepPINCS
Licenses: Artistic License 2.0
Build system: r
Synopsis: Protein Interactions and Networks with Compounds based on Sequences using Deep Learning
Description:

The identification of novel compound-protein interaction (CPI) is important in drug discovery. Revealing unknown compound-protein interactions is useful to design a new drug for a target protein by screening candidate compounds. The accurate CPI prediction assists in effective drug discovery process. To identify potential CPI effectively, prediction methods based on machine learning and deep learning have been developed. Data for sequences are provided as discrete symbolic data. In the data, compounds are represented as SMILES (simplified molecular-input line-entry system) strings and proteins are sequences in which the characters are amino acids. The outcome is defined as a variable that indicates how strong two molecules interact with each other or whether there is an interaction between them. In this package, a deep-learning based model that takes only sequence information of both compounds and proteins as input and the outcome as output is used to predict CPI. The model is implemented by using compound and protein encoders with useful features. The CPI model also supports other modeling tasks, including protein-protein interaction (PPI), chemical-chemical interaction (CCI), or single compounds and proteins. Although the model is designed for proteins, DNA and RNA can be used if they are represented as sequences.

r-dfplyr 1.4.0
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.

r-daglogo 1.48.0
Propagated dependencies: r-uniprot-ws@2.50.1 r-pheatmap@1.0.13 r-motifstack@1.54.0 r-httr@1.4.7 r-biostrings@2.78.0 r-biomart@2.66.0 r-biocgenerics@0.56.0
Channel: guix-bioc
Location: guix-bioc/packages/d.scm (guix-bioc packages d)
Home page: https://bioconductor.org/packages/dagLogo
Licenses: FSDG-compatible
Build system: r
Synopsis: dagLogo: a Bioconductor package for visualizing conserved amino acid sequence pattern in groups based on probability theory
Description:

Visualize significant conserved amino acid sequence pattern in groups based on probability theory.

r-diggit 1.42.0
Propagated dependencies: r-viper@1.44.0 r-ks@1.15.1 r-biobase@2.70.0
Channel: guix-bioc
Location: guix-bioc/packages/d.scm (guix-bioc packages d)
Home page: https://bioconductor.org/packages/diggit
Licenses: FSDG-compatible
Build system: r
Synopsis: Inference of Genetic Variants Driving Cellular Phenotypes
Description:

Inference of Genetic Variants Driving Cellullar Phenotypes by the DIGGIT algorithm.

r-dcgsa 1.38.0
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-demuxsnp 1.8.0
Propagated dependencies: r-variantannotation@1.56.0 r-summarizedexperiment@1.40.0 r-singlecellexperiment@1.32.0 r-seqinfo@1.0.0 r-matrixgenerics@1.22.0 r-matrix@1.7-4 r-kernelknn@1.1.6 r-iranges@2.44.0 r-ensembldb@2.34.0 r-dplyr@1.1.4 r-demuxmix@1.1.1-1.09a7918 r-class@7.3-23 r-biocgenerics@0.56.0
Channel: guix-bioc
Location: guix-bioc/packages/d.scm (guix-bioc packages d)
Home page: https://github.com/michaelplynch/demuxSNP
Licenses: GPL 3
Build system: r
Synopsis: scRNAseq demultiplexing using cell hashing and SNPs
Description:

This package assists in demultiplexing scRNAseq data using both cell hashing and SNPs data. The SNP profile of each group os learned using high confidence assignments from the cell hashing data. Cells which cannot be assigned with high confidence from the cell hashing data are assigned to their most similar group based on their SNPs. We also provide some helper function to optimise SNP selection, create training data and merge SNP data into the SingleCellExperiment framework.

r-duoclustering2018 1.28.0
Channel: guix-bioc
Location: guix-bioc/packages/d.scm (guix-bioc packages d)
Home page: https://bioconductor.org/packages/DuoClustering2018
Licenses: FSDG-compatible
Build system: r
Synopsis: Data, Clustering Results and Visualization Functions From Duò et al (2018)
Description:

Preprocessed experimental and simulated scRNA-seq data sets used for evaluation of clustering methods for scRNA-seq data in Duò et al (2018). Also contains results from applying several clustering methods to each of the data sets, and functions for plotting method performance.

r-drugvsdiseasedata 1.46.0
Channel: guix-bioc
Location: guix-bioc/packages/d.scm (guix-bioc packages d)
Home page: https://bioconductor.org/packages/DrugVsDiseasedata
Licenses: GPL 3
Build system: r
Synopsis: Drug versus Disease Data
Description:

Data package which provides default disease expression profiles, clusters and annotation information for use with the DrugVsDisease package.

r-drosophila2probe 2.18.0
Propagated dependencies: r-annotationdbi@1.72.0
Channel: guix-bioc
Location: guix-bioc/packages/d.scm (guix-bioc packages d)
Home page: https://bioconductor.org/packages/drosophila2probe
Licenses: LGPL 2.0+
Build system: r
Synopsis: Probe sequence data for microarrays of type drosophila2
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 Drosophila\_2\_probe\_tab.

r-dapar 1.42.0
Propagated dependencies: r-msnbase@2.36.0 r-highcharter@0.9.4 r-foreach@1.5.2 r-dapardata@1.40.0 r-biobase@2.70.0
Channel: guix-bioc
Location: guix-bioc/packages/d.scm (guix-bioc packages d)
Home page: http://www.prostar-proteomics.org/
Licenses: Artistic License 2.0
Build system: r
Synopsis: Tools for the Differential Analysis of Proteins Abundance with R
Description:

The package DAPAR is a Bioconductor distributed R package which provides all the necessary functions to analyze quantitative data from label-free proteomics experiments. Contrarily to most other similar R packages, it is endowed with rich and user-friendly graphical interfaces, so that no programming skill is required (see `Prostar` package).

r-dart 1.58.0
Propagated dependencies: r-igraph@2.2.1
Channel: guix-bioc
Location: guix-bioc/packages/d.scm (guix-bioc packages d)
Home page: https://bioconductor.org/packages/DART
Licenses: GPL 2
Build system: r
Synopsis: Denoising Algorithm based on Relevance network Topology
Description:

Denoising Algorithm based on Relevance network Topology (DART) is an algorithm designed to evaluate the consistency of prior information molecular signatures (e.g in-vitro perturbation expression signatures) in independent molecular data (e.g gene expression data sets). If consistent, a pruning network strategy is then used to infer the activation status of the molecular signature in individual samples.

r-dnazoodata 1.10.0
Propagated dependencies: r-s4vectors@0.48.0 r-rjson@0.2.23 r-hicexperiment@1.10.0 r-biocfilecache@3.0.0
Channel: guix-bioc
Location: guix-bioc/packages/d.scm (guix-bioc packages d)
Home page: https://github.com/js2264/DNAZooData
Licenses: Expat
Build system: r
Synopsis: DNA Zoo data package
Description:

DNAZooData is a data package giving programmatic access to genome assemblies and Hi-C contact matrices uniformly processed by the [DNA Zoo Consortium](https://www.dnazoo.org/). The matrices are available in the multi-resolution `.hic` format. A URL to corrected genome assemblies in `.fastq` format is also provided to the end-user.

r-duplexdiscoverer 1.4.0
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-dyebiasexamples 1.50.0
Propagated dependencies: r-marray@1.88.0 r-geoquery@2.78.0
Channel: guix-bioc
Location: guix-bioc/packages/d.scm (guix-bioc packages d)
Home page: http://www.holstegelab.nl/publications/margaritis_lijnzaad
Licenses: GPL 3
Build system: r
Synopsis: Example data for the dyebias package, which implements the GASSCO method
Description:

Data for the dyebias package, consisting of 4 self-self hybrizations of self-spotted yeast slides, as well as data from Array Express accession E-MTAB-32.

r-drosgenome1-db 3.13.0
Propagated dependencies: r-org-dm-eg-db@3.22.0 r-annotationdbi@1.72.0
Channel: guix-bioc
Location: guix-bioc/packages/d.scm (guix-bioc packages d)
Home page: https://bioconductor.org/packages/drosgenome1.db
Licenses: Artistic License 2.0
Build system: r
Synopsis: Affymetrix Affymetrix DrosGenome1 Array annotation data (chip drosgenome1)
Description:

Affymetrix Affymetrix DrosGenome1 Array annotation data (chip drosgenome1) assembled using data from public repositories.

r-debrowser 1.38.0
Channel: guix-bioc
Location: guix-bioc/packages/d.scm (guix-bioc packages d)
Home page: https://github.com/UMMS-Biocore/debrowser
Licenses: FSDG-compatible
Build system: r
Synopsis: Interactive Differential Expresion Analysis Browser
Description:

Bioinformatics platform containing interactive plots and tables for differential gene and region expression studies. Allows visualizing expression data much more deeply in an interactive and faster way. By changing the parameters, users can easily discover different parts of the data that like never have been done before. Manually creating and looking these plots takes time. With DEBrowser users can prepare plots without writing any code. Differential expression, PCA and clustering analysis are made on site and the results are shown in various plots such as scatter, bar, box, volcano, ma plots and Heatmaps.

r-drosgenome1cdf 2.18.0
Propagated dependencies: r-annotationdbi@1.72.0
Channel: guix-bioc
Location: guix-bioc/packages/d.scm (guix-bioc packages d)
Home page: https://bioconductor.org/packages/drosgenome1cdf
Licenses: LGPL 2.0+
Build system: r
Synopsis: drosgenome1cdf
Description:

This package provides a package containing an environment representing the DrosGenome1.CDF file.

r-dta 2.56.0
Propagated dependencies: r-scatterplot3d@0.3-44 r-lsd@4.1-0
Channel: guix-bioc
Location: guix-bioc/packages/d.scm (guix-bioc packages d)
Home page: https://bioconductor.org/packages/DTA
Licenses: Artistic License 2.0
Build system: r
Synopsis: Dynamic Transcriptome Analysis
Description:

Dynamic Transcriptome Analysis (DTA) can monitor the cellular response to perturbations with higher sensitivity and temporal resolution than standard transcriptomics. The package implements the underlying kinetic modeling approach capable of the precise determination of synthesis- and decay rates from individual microarray or RNAseq measurements.

r-dominoeffect 1.30.0
Propagated dependencies: r-variantannotation@1.56.0 r-summarizedexperiment@1.40.0 r-seqinfo@1.0.0 r-pwalign@1.6.0 r-iranges@2.44.0 r-genomicranges@1.62.0 r-data-table@1.17.8 r-biostrings@2.78.0 r-biomart@2.66.0 r-annotationdbi@1.72.0
Channel: guix-bioc
Location: guix-bioc/packages/d.scm (guix-bioc packages d)
Home page: https://bioconductor.org/packages/DominoEffect
Licenses: GPL 3+
Build system: r
Synopsis: Identification and Annotation of Protein Hotspot Residues
Description:

The functions support identification and annotation of hotspot residues in proteins. These are individual amino acids that accumulate mutations at a much higher rate than their surrounding regions.

r-desubs 1.36.0
Propagated dependencies: r-rbgl@1.86.0 r-pheatmap@1.0.13 r-nbpseq@0.3.1 r-matrix@1.7-4 r-locfit@1.5-9.12 r-limma@3.66.0 r-jsonlite@2.0.0 r-igraph@2.2.1 r-graph@1.88.0 r-ggplot2@4.0.1 r-edger@4.8.0 r-ebseq@2.8.0 r-deseq2@1.50.2 r-circlize@0.4.16
Channel: guix-bioc
Location: guix-bioc/packages/d.scm (guix-bioc packages d)
Home page: https://bioconductor.org/packages/DEsubs
Licenses: GPL 3
Build system: r
Synopsis: DEsubs: an R package for flexible identification of differentially expressed subpathways using RNA-seq expression experiments
Description:

DEsubs is a network-based systems biology package that extracts disease-perturbed subpathways within a pathway network as recorded by RNA-seq experiments. It contains an extensive and customizable framework covering a broad range of operation modes at all stages of the subpathway analysis, enabling a case-specific approach. The operation modes refer to the pathway network construction and processing, the subpathway extraction, visualization and enrichment analysis with regard to various biological and pharmacological features. Its capabilities render it a tool-guide for both the modeler and experimentalist for the identification of more robust systems-level biomarkers for complex diseases.

r-dlbcl 1.50.0
Propagated dependencies: r-graph@1.88.0 r-biobase@2.70.0
Channel: guix-bioc
Location: guix-bioc/packages/d.scm (guix-bioc packages d)
Home page: http://bionet.bioapps.biozentrum.uni-wuerzburg.de/
Licenses: FSDG-compatible
Build system: r
Synopsis: Diffuse large B-cell lymphoma expression data
Description:

This package provides additional expression data on diffuse large B-cell lymphomas for the BioNet package.

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Total results: 69112