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


r-flowgate 1.12.0
Propagated dependencies: r-tibble@3.3.1 r-shiny@1.11.1 r-rlang@1.1.7 r-purrr@1.2.1 r-ggplot2@4.0.2 r-ggcyto@1.38.1 r-flowworkspace@4.22.1 r-flowcore@2.22.1 r-dplyr@1.2.0 r-biocmanager@1.30.27
Channel: guix-bioc
Location: guix-bioc/packages/f.scm (guix-bioc packages f)
Home page: https://bioconductor.org/packages/flowGate
Licenses: Expat
Build system: r
Synopsis: Interactive Cytometry Gating in R
Description:

flowGate adds an interactive Shiny app to allow manual GUI-based gating of flow cytometry data in R. Using flowGate, you can draw 1D and 2D span/rectangle gates, quadrant gates, and polygon gates on flow cytometry data by interactively drawing the gates on a plot of your data, rather than by specifying gate coordinates. This package is especially geared toward wet-lab cytometerists looking to take advantage of R for cytometry analysis, without necessarily having a lot of R experience.

r-fishalyser 1.46.0
Propagated dependencies: r-ebimage@4.52.0 r-abind@1.4-8
Channel: guix-bioc
Location: guix-bioc/packages/f.scm (guix-bioc packages f)
Home page: https://bioconductor.org/packages/FISHalyseR
Licenses: Artistic License 2.0
Build system: r
Synopsis: FISHalyseR a package for automated FISH quantification
Description:

FISHalyseR provides functionality to process and analyse digital cell culture images, in particular to quantify FISH probes within nuclei. Furthermore, it extract the spatial location of each nucleus as well as each probe enabling spatial co-localisation analysis.

r-fgga 1.20.0
Propagated dependencies: r-rbgl@1.86.0 r-jsonlite@2.0.0 r-igraph@2.2.2 r-grbase@2.0.3 r-graph@1.88.1 r-e1071@1.7-17 r-curl@7.0.0 r-biocfilecache@3.0.0
Channel: guix-bioc
Location: guix-bioc/packages/f.scm (guix-bioc packages f)
Home page: https://github.com/fspetale/fgga
Licenses: GPL 3
Build system: r
Synopsis: Hierarchical ensemble method based on factor graph
Description:

Package that implements the FGGA algorithm. This package provides a hierarchical ensemble method based ob factor graphs for the consistent cross-ontology annotation of protein coding genes. FGGA embodies elements of predicate logic, communication theory, supervised learning and inference in graphical models.

r-fabia 2.58.0
Propagated dependencies: r-biobase@2.70.0
Channel: guix-bioc
Location: guix-bioc/packages/f.scm (guix-bioc packages f)
Home page: http://www.bioinf.jku.at/software/fabia/fabia.html
Licenses: LGPL 2.1+
Build system: r
Synopsis: FABIA: Factor Analysis for Bicluster Acquisition
Description:

Biclustering by "Factor Analysis for Bicluster Acquisition" (FABIA). FABIA is a model-based technique for biclustering, that is clustering rows and columns simultaneously. Biclusters are found by factor analysis where both the factors and the loading matrix are sparse. FABIA is a multiplicative model that extracts linear dependencies between samples and feature patterns. It captures realistic non-Gaussian data distributions with heavy tails as observed in gene expression measurements. FABIA utilizes well understood model selection techniques like the EM algorithm and variational approaches and is embedded into a Bayesian framework. FABIA ranks biclusters according to their information content and separates spurious biclusters from true biclusters. The code is written in C.

r-frmaexampledata 1.48.0
Channel: guix-bioc
Location: guix-bioc/packages/f.scm (guix-bioc packages f)
Home page: https://bioconductor.org/packages/frmaExampleData
Licenses: GPL 2+
Build system: r
Synopsis: Frma Example Data
Description:

Data files used by the examples in frma and frmaTools packages.

r-flowploidy 1.38.0
Propagated dependencies: r-shiny@1.11.1 r-rmarkdown@2.30 r-minpack-lm@1.2-4 r-knitr@1.51 r-flowcore@2.22.1 r-catools@1.18.3 r-car@3.1-5
Channel: guix-bioc
Location: guix-bioc/packages/f.scm (guix-bioc packages f)
Home page: https://github.com/plantarum/flowPloidy
Licenses: GPL 3
Build system: r
Synopsis: Analyze flow cytometer data to determine sample ploidy
Description:

Determine sample ploidy via flow cytometry histogram analysis. Reads Flow Cytometry Standard (FCS) files via the flowCore bioconductor package, and provides functions for determining the DNA ploidy of samples based on internal standards.

r-featseekr 1.12.0
Propagated dependencies: r-summarizedexperiment@1.40.0 r-pracma@2.4.6 r-pheatmap@1.0.13 r-mass@7.3-65
Channel: guix-bioc
Location: guix-bioc/packages/f.scm (guix-bioc packages f)
Home page: https://github.com/tcapraz/FeatSeekR
Licenses: GPL 3
Build system: r
Synopsis: FeatSeekR an R package for unsupervised feature selection
Description:

FeatSeekR performs unsupervised feature selection using replicated measurements. It iteratively selects features with the highest reproducibility across replicates, after projecting out those dimensions from the data that are spanned by the previously selected features. The selected a set of features has a high replicate reproducibility and a high degree of uniqueness.

r-flowcybar 1.48.0
Propagated dependencies: r-vegan@2.7-2 r-gplots@3.3.0
Channel: guix-bioc
Location: guix-bioc/packages/f.scm (guix-bioc packages f)
Home page: http://www.ufz.de/index.php?de=16773
Licenses: GPL 2
Build system: r
Synopsis: Analyze flow cytometric data using gate information
Description:

This package provides a package to analyze flow cytometric data using gate information to follow population/community dynamics.

r-flowdensity 1.46.0
Dependencies: libxml2@2.14.6
Propagated dependencies: r-polyclip@1.10-7 r-gplots@3.3.0 r-flowviz@1.74.0 r-flowcore@2.22.1 r-car@3.1-5
Channel: guix-bioc
Location: guix-bioc/packages/f.scm (guix-bioc packages f)
Home page: https://bioconductor.org/packages/flowDensity
Licenses: Artistic License 2.0
Build system: r
Synopsis: Sequential Flow Cytometry Data Gating
Description:

This package provides tools for automated sequential gating analogous to the manual gating strategy based on the density of the data.

r-fraq 1.0.0
Dependencies: zlib@1.3.1
Propagated dependencies: r-stringfish@0.18.0 r-shortread@1.68.0 r-rcppparallel@5.1.11-1 r-rcpp@1.1.1 r-edlibr@1.0.3 r-biostrings@2.78.0
Channel: guix-bioc
Location: guix-bioc/packages/f.scm (guix-bioc packages f)
Home page: https://github.com/traversc/fraq
Licenses: GPL 3
Build system: r
Synopsis: High-Throughput and Extensible Toolkit for Processing FASTQ Data
Description:

High-throughput extensible toolkit for processing FASTQ data. The goal of this package is to empower users to quickly build out small programmatic kernels to define any FASTQ processing task they may need. Builds on Intel TBB’s flow graph to orchestrate concurrent I/O and data processing; throughput can be as fast as compression and disk speed allows. The package also ships with a suite of predefined kernels for common FASTQ tasks.

r-flowplots 1.60.0
Channel: guix-bioc
Location: guix-bioc/packages/f.scm (guix-bioc packages f)
Home page: https://bioconductor.org/packages/flowPlots
Licenses: Artistic License 2.0
Build system: r
Synopsis: flowPlots: analysis plots and data class for gated flow cytometry data
Description:

Graphical displays with embedded statistical tests for gated ICS flow cytometry data, and a data class which stores "stacked" data and has methods for computing summary measures on stacked data, such as marginal and polyfunctional degree data.

r-frmatools 1.64.0
Propagated dependencies: r-preprocesscore@1.72.0 r-dbi@1.3.0 r-biobase@2.70.0 r-affy@1.88.0
Channel: guix-bioc
Location: guix-bioc/packages/f.scm (guix-bioc packages f)
Home page: http://bioconductor.org
Licenses: GPL 2+
Build system: r
Synopsis: Frozen RMA Tools
Description:

This package provides tools for advanced use of the frma package.

r-filterffpe 1.22.0
Propagated dependencies: r-s4vectors@0.48.0 r-rsamtools@2.26.0 r-iranges@2.44.0 r-genomicranges@1.62.1 r-foreach@1.5.2 r-doparallel@1.0.17
Channel: guix-bioc
Location: guix-bioc/packages/f.scm (guix-bioc packages f)
Home page: https://bioconductor.org/packages/FilterFFPE
Licenses: LGPL 3
Build system: r
Synopsis: FFPE Artificial Chimeric Read Filter for NGS data
Description:

This package finds and filters artificial chimeric reads specifically generated in next-generation sequencing (NGS) process of formalin-fixed paraffin-embedded (FFPE) tissues. These artificial chimeric reads can lead to a large number of false positive structural variation (SV) calls. The required input is an indexed BAM file of a FFPE sample.

r-findit2 1.18.0
Propagated dependencies: r-withr@3.0.2 r-tidyr@1.3.2 r-tibble@3.3.1 r-summarizedexperiment@1.40.0 r-stringr@1.6.0 r-seqinfo@1.0.0 r-s4vectors@0.48.0 r-rtracklayer@1.70.1 r-rlang@1.1.7 r-qvalue@2.42.0 r-purrr@1.2.1 r-progress@1.2.3 r-patchwork@1.3.2 r-multiassayexperiment@1.36.1 r-iranges@2.44.0 r-glmnet@4.1-10 r-ggrepel@0.9.7 r-ggplot2@4.0.2 r-genomicranges@1.62.1 r-genomicfeatures@1.62.0 r-dplyr@1.2.0 r-biocparallel@1.44.0 r-biocgenerics@0.56.0
Channel: guix-bioc
Location: guix-bioc/packages/f.scm (guix-bioc packages f)
Home page: https://github.com/shangguandong1996/FindIT2
Licenses: Artistic License 2.0
Build system: r
Synopsis: find influential TF and Target based on multi-omics data
Description:

This package implements functions to find influential TF and target based on different input type. It have five module: Multi-peak multi-gene annotaion(mmPeakAnno module), Calculate regulation potential(calcRP module), Find influential Target based on ChIP-Seq and RNA-Seq data(Find influential Target module), Find influential TF based on different input(Find influential TF module), Calculate peak-gene or peak-peak correlation(peakGeneCor module). And there are also some other useful function like integrate different source information, calculate jaccard similarity for your TF.

r-fdb-ucsc-trnas 1.0.1
Propagated dependencies: r-genomicfeatures@1.62.0 r-annotationdbi@1.72.0
Channel: guix-bioc
Location: guix-bioc/packages/f.scm (guix-bioc packages f)
Home page: https://bioconductor.org/packages/FDb.UCSC.tRNAs
Licenses: Artistic License 2.0
Build system: r
Synopsis: Annotation package for FeatureDb object(s)
Description:

Exposes an annotation databases generated from UCSC by exposing these as FeatureDb objects.

r-flowsorted-cordblood-450k 1.40.0
Propagated dependencies: r-minfi@1.56.0
Channel: guix-bioc
Location: guix-bioc/packages/f.scm (guix-bioc packages f)
Home page: https://bioconductor.org/packages/FlowSorted.CordBlood.450k
Licenses: Artistic License 2.0
Build system: r
Synopsis: Illumina 450k data on sorted cord blood cells
Description:

Raw data objects to be used for cord blood cell proportion estimation in minfi.

r-fly-db0 3.22.0
Propagated dependencies: r-annotationdbi@1.72.0
Channel: guix-bioc
Location: guix-bioc/packages/f.scm (guix-bioc packages f)
Home page: https://bioconductor.org/packages/fly.db0
Licenses: Artistic License 2.0
Build system: r
Synopsis: Base Level Annotation databases for fly
Description:

Base annotation databases for fly, intended ONLY to be used by AnnotationDbi to produce regular annotation packages.

r-flowtime 1.36.0
Propagated dependencies: r-tibble@3.3.1 r-rlang@1.1.7 r-plyr@1.8.9 r-magrittr@2.0.4 r-flowcore@2.22.1 r-dplyr@1.2.0
Channel: guix-bioc
Location: guix-bioc/packages/f.scm (guix-bioc packages f)
Home page: https://bioconductor.org/packages/flowTime
Licenses: Artistic License 2.0
Build system: r
Synopsis: Annotation and analysis of biological dynamical systems using flow cytometry
Description:

This package facilitates analysis of both timecourse and steady state flow cytometry experiments. This package was originially developed for quantifying the function of gene regulatory networks in yeast (strain W303) expressing fluorescent reporter proteins using BD Accuri C6 and SORP cytometers. However, the functions are for the most part general and may be adapted for analysis of other organisms using other flow cytometers. Functions in this package facilitate the annotation of flow cytometry data with experimental metadata, as often required for publication and general ease-of-reuse. Functions for creating, saving and loading gate sets are also included. In the past, we have typically generated summary statistics for each flowset for each timepoint and then annotated and analyzed these summary statistics. This method loses a great deal of the power that comes from the large amounts of individual cell data generated in flow cytometry, by essentially collapsing this data into a bulk measurement after subsetting. In addition to these summary functions, this package also contains functions to facilitate annotation and analysis of steady-state or time-lapse data utilizing all of the data collected from the thousands of individual cells in each sample.

r-funomics 1.6.0
Propagated dependencies: r-stringr@1.6.0 r-pathifier@1.50.0 r-org-hs-eg-db@3.22.0 r-nmf@0.28 r-keggrest@1.50.0 r-dplyr@1.2.0 r-annotationdbi@1.72.0
Channel: guix-bioc
Location: guix-bioc/packages/f.scm (guix-bioc packages f)
Home page: https://github.com/elisagdelope/funomics
Licenses: Expat
Build system: r
Synopsis: Aggregating Omics Data into Higher-Level Functional Representations
Description:

The funOmics package ggregates or summarizes omics data into higher level functional representations such as GO terms gene sets or KEGG metabolic pathways. The aggregated data matrix represents functional activity scores that facilitate the analysis of functional molecular sets while allowing to reduce dimensionality and provide easier and faster biological interpretations. Coordinated functional activity scores can be as informative as single molecules!

r-fletcher2013b 1.48.0
Propagated dependencies: r-rtn@2.36.0 r-reder@3.8.0 r-rcolorbrewer@1.1-3 r-igraph@2.2.2 r-fletcher2013a@1.48.0
Channel: guix-bioc
Location: guix-bioc/packages/f.scm (guix-bioc packages f)
Home page: http://dx.doi.org/10.1038/ncomms3464
Licenses: GPL 2+
Build system: r
Synopsis: Master regulators of FGFR2 signalling and breast cancer risk
Description:

This package reproduces the systems biology analysis for the data in package Fletcher2013a using RTN.

r-flowbin 1.48.0
Propagated dependencies: r-snow@0.4-4 r-limma@3.66.0 r-flowfp@1.70.0 r-flowcore@2.22.1 r-class@7.3-23 r-biocgenerics@0.56.0
Channel: guix-bioc
Location: guix-bioc/packages/f.scm (guix-bioc packages f)
Home page: https://bioconductor.org/packages/flowBin
Licenses: Artistic License 2.0
Build system: r
Synopsis: Combining multitube flow cytometry data by binning
Description:

Software to combine flow cytometry data that has been multiplexed into multiple tubes with common markers between them, by establishing common bins across tubes in terms of the common markers, then determining expression within each tube for each bin in terms of the tube-specific markers.

r-grenits 1.64.0
Propagated dependencies: r-reshape2@1.4.5 r-rcpparmadillo@15.2.3-1 r-rcpp@1.1.1 r-ggplot2@4.0.2
Channel: guix-bioc
Location: guix-bioc/packages/g.scm (guix-bioc packages g)
Home page: https://bioconductor.org/packages/GRENITS
Licenses: GPL 2+
Build system: r
Synopsis: Gene Regulatory Network Inference Using Time Series
Description:

The package offers four network inference statistical models using Dynamic Bayesian Networks and Gibbs Variable Selection: a linear interaction model, two linear interaction models with added experimental noise (Gaussian and Student distributed) for the case where replicates are available and a non-linear interaction model.

r-genetonic 3.6.0
Propagated dependencies: r-visnetwork@2.1.4 r-viridis@0.6.5 r-tippy@0.1.0 r-tidyr@1.3.2 r-summarizedexperiment@1.40.0 r-shinywidgets@0.9.1 r-shinycssloaders@1.1.0 r-shinyace@0.4.4 r-shiny@1.11.1 r-scales@1.4.0 r-s4vectors@0.48.0 r-rmarkdown@2.30 r-rlang@1.1.7 r-rintrojs@0.3.4 r-rcolorbrewer@1.1-3 r-plotly@4.12.0 r-mosdef@1.6.0 r-matrixstats@1.5.0 r-igraph@2.2.2 r-go-db@3.22.0 r-ggridges@0.5.7 r-ggrepel@0.9.7 r-ggplot2@4.0.2 r-ggforce@0.5.0 r-expm@1.0-0 r-dynamictreecut@1.63-1 r-dt@0.34.0 r-dplyr@1.2.0 r-deseq2@1.50.2 r-dendextend@1.19.1 r-complexupset@1.3.3 r-complexheatmap@2.26.1 r-colourpicker@1.3.0 r-colorspace@2.1-2 r-circlize@0.4.17 r-bs4dash@2.3.5 r-backbone@3.0.4 r-annotationdbi@1.72.0
Channel: guix-bioc
Location: guix-bioc/packages/g.scm (guix-bioc packages g)
Home page: https://github.com/federicomarini/GeneTonic
Licenses: Expat
Build system: r
Synopsis: Enjoy Analyzing And Integrating The Results From Differential Expression Analysis And Functional Enrichment Analysis
Description:

This package provides functionality to combine the existing pieces of the transcriptome data and results, making it easier to generate insightful observations and hypothesis. Its usage is made easy with a Shiny application, combining the benefits of interactivity and reproducibility e.g. by capturing the features and gene sets of interest highlighted during the live session, and creating an HTML report as an artifact where text, code, and output coexist. Using the GeneTonicList as a standardized container for all the required components, it is possible to simplify the generation of multiple visualizations and summaries.

r-gwena 1.22.0
Propagated dependencies: r-wgcna@1.74 r-tidyr@1.3.2 r-tibble@3.3.1 r-summarizedexperiment@1.40.0 r-stringr@1.6.0 r-rlist@0.4.6.2 r-rcolorbrewer@1.1-3 r-purrr@1.2.1 r-netrep@1.2.9 r-matrixstats@1.5.0 r-magrittr@2.0.4 r-igraph@2.2.2 r-gprofiler2@0.2.4 r-ggplot2@4.0.2 r-dynamictreecut@1.63-1 r-dplyr@1.2.0 r-cluster@2.1.8.2
Channel: guix-bioc
Location: guix-bioc/packages/g.scm (guix-bioc packages g)
Home page: https://bioconductor.org/packages/GWENA
Licenses: GPL 3
Build system: r
Synopsis: Pipeline for augmented co-expression analysis
Description:

The development of high-throughput sequencing led to increased use of co-expression analysis to go beyong single feature (i.e. gene) focus. We propose GWENA (Gene Whole co-Expression Network Analysis) , a tool designed to perform gene co-expression network analysis and explore the results in a single pipeline. It includes functional enrichment of modules of co-expressed genes, phenotypcal association, topological analysis and comparison of networks configuration between conditions.

Page: 13334353637126
Total packages: 3017