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      /\__ \     / /\ \ \\ \ \_/ / /     / / /\ \__
     / /_ \ \   / / /\ \ \\ \___/ /     / / /\ \___\
    / / /\ \ \ / / /  \ \_\\ \ \_/      \ \ \ \/___/
   / / /  \/_// / /   / / / \ \ \        \ \ \
  / / /      / / /   / / /   \ \ \   _    \ \ \
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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-clariomshumanhttranscriptcluster-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/clariomshumanhttranscriptcluster.db
Licenses: Artistic License 2.0
Build system: r
Synopsis: Affymetrix clariomshumanht annotation data (chip clariomshumanhttranscriptcluster)
Description:

Affymetrix clariomshumanht annotation data (chip clariomshumanhttranscriptcluster) assembled using data from public repositories.

r-clustifyrdatahub 1.20.0
Propagated dependencies: r-experimenthub@3.0.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://rnabioco.github.io/clustifyrdatahub/
Licenses: Expat
Build system: r
Synopsis: External data sets for clustifyr in ExperimentHub
Description:

References made from external single-cell mRNA sequencing data sets, stored as average gene expression matrices. For use with clustifyr <https://bioconductor.org/packages/clustifyr> to assign cell type identities.

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-canineprobe 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/canineprobe
Licenses: LGPL 2.0+
Build system: r
Synopsis: Probe sequence data for microarrays of type canine
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\_probe\_tab.

r-cytomds 1.6.1
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://uclouvain-cbio.github.io/CytoMDS
Licenses: GPL 3
Build system: r
Synopsis: Low Dimensions projection of cytometry samples
Description:

This package implements a low dimensional visualization of a set of cytometry samples, in order to visually assess the distances between them. This, in turn, can greatly help the user to identify quality issues like batch effects or outlier samples, and/or check the presence of potential sample clusters that might align with the exeprimental design. The CytoMDS algorithm combines, on the one hand, the concept of Earth Mover's Distance (EMD), a.k.a. Wasserstein metric and, on the other hand, the Multi Dimensional Scaling (MDS) algorithm for the low dimensional projection. Also, the package provides some diagnostic tools for both checking the quality of the MDS projection, as well as tools to help with the interpretation of the axes of the projection.

r-cfdnakit 1.8.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://bioconductor.org/packages/cfdnakit
Licenses: GPL 3
Build system: r
Synopsis: Fragmen-length analysis package from high-throughput sequencing of cell-free DNA (cfDNA)
Description:

This package provides basic functions for analyzing shallow whole-genome sequencing (~0.3X or more) of cell-free DNA (cfDNA). The package basically extracts the length of cfDNA fragments and aids the vistualization of fragment-length information. The package also extract fragment-length information per non-overlapping fixed-sized bins and used it for calculating ctDNA estimation score (CES).

r-dvddata 1.46.0
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-dmchmm 1.32.0
Propagated dependencies: r-summarizedexperiment@1.40.0 r-s4vectors@0.48.0 r-rtracklayer@1.70.0 r-multcomp@1.4-29 r-iranges@2.44.0 r-genomicranges@1.62.0 r-fdrtool@1.2.18 r-calibrate@1.7.7 r-biocparallel@1.44.0
Channel: guix-bioc
Location: guix-bioc/packages/d.scm (guix-bioc packages d)
Home page: https://bioconductor.org/packages/DMCHMM
Licenses: GPL 3
Build system: r
Synopsis: Differentially Methylated CpG using Hidden Markov Model
Description:

This package provides a pipeline for identifying differentially methylated CpG sites using Hidden Markov Model in bisulfite sequencing data. DNA methylation studies have enabled researchers to understand methylation patterns and their regulatory roles in biological processes and disease. However, only a limited number of statistical approaches have been developed to provide formal quantitative analysis. Specifically, a few available methods do identify differentially methylated CpG (DMC) sites or regions (DMR), but they suffer from limitations that arise mostly due to challenges inherent in bisulfite sequencing data. These challenges include: (1) that read-depths vary considerably among genomic positions and are often low; (2) both methylation and autocorrelation patterns change as regions change; and (3) CpG sites are distributed unevenly. Furthermore, there are several methodological limitations: almost none of these tools is capable of comparing multiple groups and/or working with missing values, and only a few allow continuous or multiple covariates. The last of these is of great interest among researchers, as the goal is often to find which regions of the genome are associated with several exposures and traits. To tackle these issues, we have developed an efficient DMC identification method based on Hidden Markov Models (HMMs) called “DMCHMM” which is a three-step approach (model selection, prediction, testing) aiming to address the aforementioned drawbacks.

r-demixt 1.26.0
Channel: guix-bioc
Location: guix-bioc/packages/d.scm (guix-bioc packages d)
Home page: https://bioconductor.org/packages/DeMixT
Licenses: GPL 3
Build system: r
Synopsis: Cell type-specific deconvolution of heterogeneous tumor samples with two or three components using expression data from RNAseq or microarray platforms
Description:

DeMixT is a software package that performs deconvolution on transcriptome data from a mixture of two or three components.

r-deeptarget 1.4.0
Channel: guix-bioc
Location: guix-bioc/packages/d.scm (guix-bioc packages d)
Home page: https://bioconductor.org/packages/DeepTarget
Licenses: GPL 2
Build system: r
Synopsis: Deep characterization of cancer drugs
Description:

This package predicts a drug’s primary target(s) or secondary target(s) by integrating large-scale genetic and drug screens from the Cancer Dependency Map project run by the Broad Institute. It further investigates whether the drug specifically targets the wild-type or mutated target forms. To show how to use this package in practice, we provided sample data along with step-by-step example.

r-dep 1.32.0
Channel: guix-bioc
Location: guix-bioc/packages/d.scm (guix-bioc packages d)
Home page: https://bioconductor.org/packages/DEP
Licenses: Artistic License 2.0
Build system: r
Synopsis: Differential Enrichment analysis of Proteomics data
Description:

This package provides an integrated analysis workflow for robust and reproducible analysis of mass spectrometry proteomics data for differential protein expression or differential enrichment. It requires tabular input (e.g. txt files) as generated by quantitative analysis softwares of raw mass spectrometry data, such as MaxQuant or IsobarQuant. Functions are provided for data preparation, filtering, variance normalization and imputation of missing values, as well as statistical testing of differentially enriched / expressed proteins. It also includes tools to check intermediate steps in the workflow, such as normalization and missing values imputation. Finally, visualization tools are provided to explore the results, including heatmap, volcano plot and barplot representations. For scientists with limited experience in R, the package also contains wrapper functions that entail the complete analysis workflow and generate a report. Even easier to use are the interactive Shiny apps that are provided by the package.

r-ddct 1.66.0
Propagated dependencies: r-xtable@1.8-4 r-rcolorbrewer@1.1-3 r-lattice@0.22-7 r-biocgenerics@0.56.0 r-biobase@2.70.0
Channel: guix-bioc
Location: guix-bioc/packages/d.scm (guix-bioc packages d)
Home page: https://bioconductor.org/packages/ddCt
Licenses: LGPL 3
Build system: r
Synopsis: The ddCt Algorithm for the Analysis of Quantitative Real-Time PCR (qRT-PCR)
Description:

The Delta-Delta-Ct (ddCt) Algorithm is an approximation method to determine relative gene expression with quantitative real-time PCR (qRT-PCR) experiments. Compared to other approaches, it requires no standard curve for each primer-target pair, therefore reducing the working load and yet returning accurate enough results as long as the assumptions of the amplification efficiency hold. The ddCt package implements a pipeline to collect, analyse and visualize qRT-PCR results, for example those from TaqMan SDM software, mainly using the ddCt method. The pipeline can be either invoked by a script in command-line or through the API consisting of S4-Classes, methods and functions.

r-doser 1.26.0
Channel: guix-bioc
Location: guix-bioc/packages/d.scm (guix-bioc packages d)
Home page: https://bioconductor.org/packages/doseR
Licenses: GPL 2+ GPL 3+
Build system: r
Synopsis: doseR
Description:

doseR package is a next generation sequencing package for sex chromosome dosage compensation which can be applied broadly to detect shifts in gene expression among an arbitrary number of pre-defined groups of loci. doseR is a differential gene expression package for count data, that detects directional shifts in expression for multiple, specific subsets of genes, broad utility in systems biology research. doseR has been prepared to manage the nature of the data and the desired set of inferences. doseR uses S4 classes to store count data from sequencing experiment. It contains functions to normalize and filter count data, as well as to plot and calculate statistics of count data. It contains a framework for linear modeling of count data. The package has been tested using real and simulated data.

r-ddpcrclust 1.30.0
Channel: guix-bioc
Location: guix-bioc/packages/d.scm (guix-bioc packages d)
Home page: https://github.com/bgbrink/ddPCRclust
Licenses: Artistic License 2.0
Build system: r
Synopsis: Clustering algorithm for ddPCR data
Description:

The ddPCRclust algorithm can automatically quantify the CPDs of non-orthogonal ddPCR reactions with up to four targets. In order to determine the correct droplet count for each target, it is crucial to both identify all clusters and label them correctly based on their position. For more information on what data can be analyzed and how a template needs to be formatted, please check the vignette.

r-demand 1.40.0
Propagated dependencies: r-kernsmooth@2.23-26
Channel: guix-bioc
Location: guix-bioc/packages/d.scm (guix-bioc packages d)
Home page: https://bioconductor.org/packages/DeMAND
Licenses: FSDG-compatible
Build system: r
Synopsis: DeMAND
Description:

DEMAND predicts Drug MoA by interrogating a cell context specific regulatory network with a small number (N >= 6) of compound-induced gene expression signatures, to elucidate specific proteins whose interactions in the network is dysregulated by the compound.

r-dmcfb 1.24.0
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-dapardata 1.40.0
Propagated dependencies: r-msnbase@2.36.0
Channel: guix-bioc
Location: guix-bioc/packages/d.scm (guix-bioc packages d)
Home page: http://www.prostar-proteomics.org/
Licenses: GPL 2
Build system: r
Synopsis: Data accompanying the DAPAR and Prostar packages
Description:

Mass-spectrometry based UPS proteomics data sets from Ramus C, Hovasse A, Marcellin M, Hesse AM, Mouton-Barbosa E, Bouyssie D, Vaca S, Carapito C, Chaoui K, Bruley C, Garin J, Cianferani S, Ferro M, Dorssaeler AV, Burlet-Schiltz O, Schaeffer C, Coute Y, Gonzalez de Peredo A. Spiked proteomic standard dataset for testing label-free quantitative software and statistical methods. Data Brief. 2015 Dec 17;6:286-94 and Giai Gianetto, Q., Combes, F., Ramus, C., Bruley, C., Coute, Y., Burger, T. (2016). Calibration plot for proteomics: A graphical tool to visually check the assumptions underlying FDR control in quantitative experiments. Proteomics, 16(1), 29-32.

r-drosophila2-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/drosophila2.db
Licenses: Artistic License 2.0
Build system: r
Synopsis: Affymetrix Affymetrix Drosophila_2 Array annotation data (chip drosophila2)
Description:

Affymetrix Affymetrix Drosophila_2 Array annotation data (chip drosophila2) assembled using data from public repositories.

r-degcre 1.6.0
Propagated dependencies: r-txdb-hsapiens-ucsc-hg38-knowngene@3.22.0 r-seqinfo@1.0.0 r-s4vectors@0.48.0 r-qvalue@2.42.0 r-plotgardener@1.16.0 r-org-hs-eg-db@3.22.0 r-iranges@2.44.0 r-interactionset@1.38.0 r-genomicranges@1.62.0 r-biocparallel@1.44.0 r-biocgenerics@0.56.0
Channel: guix-bioc
Location: guix-bioc/packages/d.scm (guix-bioc packages d)
Home page: https://github.com/brianSroberts/DegCre
Licenses: Expat
Build system: r
Synopsis: Probabilistic association of DEGs to CREs from differential data
Description:

DegCre generates associations between differentially expressed genes (DEGs) and cis-regulatory elements (CREs) based on non-parametric concordance between differential data. The user provides GRanges of DEG TSS and CRE regions with differential p-value and optionally log-fold changes and DegCre returns an annotated Hits object with associations and their calculated probabilities. Additionally, the package provides functionality for visualization and conversion to other formats.

r-delayeddataframe 1.26.0
Propagated dependencies: r-s4vectors@0.48.0 r-delayedarray@0.36.0 r-biocgenerics@0.56.0
Channel: guix-bioc
Location: guix-bioc/packages/d.scm (guix-bioc packages d)
Home page: https://github.com/Bioconductor/DelayedDataFrame
Licenses: GPL 3
Build system: r
Synopsis: Delayed operation on DataFrame using standard DataFrame metaphor
Description:

Based on the standard DataFrame metaphor, we are trying to implement the feature of delayed operation on the DelayedDataFrame, with a slot of lazyIndex, which saves the mapping indexes for each column of DelayedDataFrame. Methods like show, validity check, [/[[ subsetting, rbind/cbind are implemented for DelayedDataFrame to be operated around lazyIndex. The listData slot stays untouched until a realization call e.g., DataFrame constructor OR as.list() is invoked.

r-drivernet 1.50.0
Channel: guix-bioc
Location: guix-bioc/packages/d.scm (guix-bioc packages d)
Home page: https://bioconductor.org/packages/DriverNet
Licenses: GPL 3
Build system: r
Synopsis: Drivernet: uncovering somatic driver mutations modulating transcriptional networks in cancer
Description:

DriverNet is a package to predict functional important driver genes in cancer by integrating genome data (mutation and copy number variation data) and transcriptome data (gene expression data). The different kinds of data are combined by an influence graph, which is a gene-gene interaction network deduced from pathway data. A greedy algorithm is used to find the possible driver genes, which may mutated in a larger number of patients and these mutations will push the gene expression values of the connected genes to some extreme values.

r-dreamlet 1.8.0
Channel: guix-bioc
Location: guix-bioc/packages/d.scm (guix-bioc packages d)
Home page: https://DiseaseNeurogenomics.github.io/dreamlet
Licenses: Artistic License 2.0
Build system: r
Synopsis: Scalable differential expression analysis of single cell transcriptomics datasets with complex study designs
Description:

Recent advances in single cell/nucleus transcriptomic technology has enabled collection of cohort-scale datasets to study cell type specific gene expression differences associated disease state, stimulus, and genetic regulation. The scale of these data, complex study designs, and low read count per cell mean that characterizing cell type specific molecular mechanisms requires a user-frieldly, purpose-build analytical framework. We have developed the dreamlet package that applies a pseudobulk approach and fits a regression model for each gene and cell cluster to test differential expression across individuals associated with a trait of interest. Use of precision-weighted linear mixed models enables accounting for repeated measures study designs, high dimensional batch effects, and varying sequencing depth or observed cells per biosample.

r-difflogo 2.34.0
Propagated dependencies: r-cba@0.2-25
Channel: guix-bioc
Location: guix-bioc/packages/d.scm (guix-bioc packages d)
Home page: https://github.com/mgledi/DiffLogo/
Licenses: GPL 2+
Build system: r
Synopsis: DiffLogo: A comparative visualisation of biooligomer motifs
Description:

DiffLogo is an easy-to-use tool to visualize motif differences.

r-dresscheck 0.48.0
Propagated dependencies: r-biobase@2.70.0
Channel: guix-bioc
Location: guix-bioc/packages/d.scm (guix-bioc packages d)
Home page: https://bioconductor.org/packages/dressCheck
Licenses: Artistic License 2.0
Build system: r
Synopsis: data and software for checking Dressman JCO 25(5) 2007
Description:

data and software for checking Dressman JCO 25(5) 2007.

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Total results: 69112