_            _    _        _         _
      /\ \         /\ \ /\ \     /\_\      / /\
      \_\ \       /  \ \\ \ \   / / /     / /  \
      /\__ \     / /\ \ \\ \ \_/ / /     / / /\ \__
     / /_ \ \   / / /\ \ \\ \___/ /     / / /\ \___\
    / / /\ \ \ / / /  \ \_\\ \ \_/      \ \ \ \/___/
   / / /  \/_// / /   / / / \ \ \        \ \ \
  / / /      / / /   / / /   \ \ \   _    \ \ \
 / / /      / / /___/ / /     \ \ \ /_/\__/ / /
/_/ /      / / /____\/ /       \ \_\\ \/___/ /
\_\/       \/_________/         \/_/ \_____\/

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-globalseq 1.38.0
Channel: guix-bioc
Location: guix-bioc/packages/g.scm (guix-bioc packages g)
Home page: https://github.com/rauschenberger/globalSeq
Licenses: GPL 3
Build system: r
Synopsis: Global Test for Counts
Description:

The method may be conceptualised as a test of overall significance in regression analysis, where the response variable is overdispersed and the number of explanatory variables exceeds the sample size. Useful for testing for association between RNA-Seq and high-dimensional data.

r-gsri 2.58.0
Propagated dependencies: r-les@1.60.0 r-gseabase@1.72.0 r-genefilter@1.92.0 r-fdrtool@1.2.18 r-biobase@2.70.0
Channel: guix-bioc
Location: guix-bioc/packages/g.scm (guix-bioc packages g)
Home page: https://bioconductor.org/packages/GSRI
Licenses: GPL 3
Build system: r
Synopsis: Gene Set Regulation Index
Description:

The GSRI package estimates the number of differentially expressed genes in gene sets, utilizing the concept of the Gene Set Regulation Index (GSRI).

r-gsar 1.44.0
Propagated dependencies: r-igraph@2.2.1
Channel: guix-bioc
Location: guix-bioc/packages/g.scm (guix-bioc packages g)
Home page: https://bioconductor.org/packages/GSAR
Licenses: FSDG-compatible
Build system: r
Synopsis: Gene Set Analysis in R
Description:

Gene set analysis using specific alternative hypotheses. Tests for differential expression, scale and net correlation structure.

r-gdnax 1.8.2
Propagated dependencies: r-summarizedexperiment@1.40.0 r-seqinfo@1.0.0 r-s4vectors@0.48.0 r-rsamtools@2.26.0 r-rcolorbrewer@1.1-3 r-plotrix@3.8-13 r-matrixstats@1.5.0 r-iranges@2.44.0 r-genomicranges@1.62.0 r-genomicfiles@1.46.0 r-genomicfeatures@1.62.0 r-genomicalignments@1.46.0 r-genomeinfodb@1.46.0 r-cli@3.6.5 r-bitops@1.0-9 r-biostrings@2.78.0 r-biocparallel@1.44.0 r-biocgenerics@0.56.0 r-annotationhub@4.0.0 r-annotationdbi@1.72.0
Channel: guix-bioc
Location: guix-bioc/packages/g.scm (guix-bioc packages g)
Home page: https://github.com/functionalgenomics/gDNAx
Licenses: Artistic License 2.0
Build system: r
Synopsis: Diagnostics for assessing genomic DNA contamination in RNA-seq data
Description:

This package provides diagnostics for assessing genomic DNA contamination in RNA-seq data, as well as plots representing these diagnostics. Moreover, the package can be used to get an insight into the strand library protocol used and, in case of strand-specific libraries, the strandedness of the data. Furthermore, it provides functionality to filter out reads of potential gDNA origin.

r-gwascatdata 0.99.6
Propagated dependencies: r-data-table@1.17.8
Channel: guix-bioc
Location: guix-bioc/packages/g.scm (guix-bioc packages g)
Home page: https://bioconductor.org/packages/gwascatData
Licenses: Artistic License 2.0
Build system: r
Synopsis: text file in cloud with March 30 2021 snapshot of EBI/EMBL GWAS catalog
Description:

This package manages a text file in cloud with March 30 2021 snapshot of EBI/EMBL GWAS catalog.This simplifies access to a snapshot of EBI GWASCAT. More current images can be obtained using the gwascat package.

r-gemma-r 3.6.1
Channel: guix-bioc
Location: guix-bioc/packages/g.scm (guix-bioc packages g)
Home page: https://pavlidislab.github.io/gemma.R/
Licenses: FSDG-compatible
Build system: r
Synopsis: wrapper for Gemma's Restful API to access curated gene expression data and differential expression analyses
Description:

Low- and high-level wrappers for Gemma's RESTful API. They enable access to curated expression and differential expression data from over 10,000 published studies. Gemma is a web site, database and a set of tools for the meta-analysis, re-use and sharing of genomics data, currently primarily targeted at the analysis of gene expression profiles.

r-gem 1.36.0
Propagated dependencies: r-ggplot2@4.0.1
Channel: guix-bioc
Location: guix-bioc/packages/g.scm (guix-bioc packages g)
Home page: https://bioconductor.org/packages/GEM
Licenses: Artistic License 2.0
Build system: r
Synopsis: GEM: fast association study for the interplay of Gene, Environment and Methylation
Description:

This package provides tools for analyzing EWAS, methQTL and GxE genome widely.

r-gmapr 1.51.1
Dependencies: zlib@1.3.1
Propagated dependencies: r-variantannotation@1.56.0 r-seqinfo@1.0.0 r-s4vectors@0.48.0 r-rtracklayer@1.70.0 r-rsamtools@2.26.0 r-iranges@2.44.0 r-genomicranges@1.62.0 r-genomicfeatures@1.62.0 r-genomicalignments@1.46.0 r-bsgenome@1.78.0 r-biostrings@2.78.0 r-biocparallel@1.44.0 r-biocio@1.20.0 r-biocgenerics@0.56.0 r-biobase@2.70.0
Channel: guix-bioc
Location: guix-bioc/packages/g.scm (guix-bioc packages g)
Home page: https://bioconductor.org/packages/gmapR
Licenses: Artistic License 2.0
Build system: r
Synopsis: An R interface to the GMAP/GSNAP/GSTRUCT suite
Description:

GSNAP and GMAP are a pair of tools to align short-read data written by Tom Wu. This package provides convenience methods to work with GMAP and GSNAP from within R. In addition, it provides methods to tally alignment results on a per-nucleotide basis using the bam_tally tool.

r-generecommender 1.82.0
Propagated dependencies: r-biobase@2.70.0
Channel: guix-bioc
Location: guix-bioc/packages/g.scm (guix-bioc packages g)
Home page: https://bioconductor.org/packages/geneRecommender
Licenses: GPL 2+
Build system: r
Synopsis: gene recommender algorithm to identify genes coexpressed with a query set of genes
Description:

This package contains a targeted clustering algorithm for the analysis of microarray data. The algorithm can aid in the discovery of new genes with similar functions to a given list of genes already known to have closely related functions.

r-gars 1.30.0
Propagated dependencies: r-summarizedexperiment@1.40.0 r-mlseq@2.28.0 r-ggplot2@4.0.1 r-damirseq@2.22.0 r-cluster@2.1.8.1
Channel: guix-bioc
Location: guix-bioc/packages/g.scm (guix-bioc packages g)
Home page: https://bioconductor.org/packages/GARS
Licenses: GPL 2+
Build system: r
Synopsis: GARS: Genetic Algorithm for the identification of Robust Subsets of variables in high-dimensional and challenging datasets
Description:

Feature selection aims to identify and remove redundant, irrelevant and noisy variables from high-dimensional datasets. Selecting informative features affects the subsequent classification and regression analyses by improving their overall performances. Several methods have been proposed to perform feature selection: most of them relies on univariate statistics, correlation, entropy measurements or the usage of backward/forward regressions. Herein, we propose an efficient, robust and fast method that adopts stochastic optimization approaches for high-dimensional. GARS is an innovative implementation of a genetic algorithm that selects robust features in high-dimensional and challenging datasets.

r-gigsea 1.28.0
Propagated dependencies: r-matrix@1.7-4 r-mass@7.3-65 r-locfdr@1.1-8
Channel: guix-bioc
Location: guix-bioc/packages/g.scm (guix-bioc packages g)
Home page: https://bioconductor.org/packages/GIGSEA
Licenses: LGPL 3
Build system: r
Synopsis: Genotype Imputed Gene Set Enrichment Analysis
Description:

We presented the Genotype-imputed Gene Set Enrichment Analysis (GIGSEA), a novel method that uses GWAS-and-eQTL-imputed trait-associated differential gene expression to interrogate gene set enrichment for the trait-associated SNPs. By incorporating eQTL from large gene expression studies, e.g. GTEx, GIGSEA appropriately addresses such challenges for SNP enrichment as gene size, gene boundary, SNP distal regulation, and multiple-marker regulation. The weighted linear regression model, taking as weights both imputation accuracy and model completeness, was used to perform the enrichment test, properly adjusting the bias due to redundancy in different gene sets. The permutation test, furthermore, is used to evaluate the significance of enrichment, whose efficiency can be largely elevated by expressing the computational intensive part in terms of large matrix operation. We have shown the appropriate type I error rates for GIGSEA (<5%), and the preliminary results also demonstrate its good performance to uncover the real signal.

r-geneplast-data 0.99.9
Channel: guix-bioc
Location: guix-bioc/packages/g.scm (guix-bioc packages g)
Home page: https://bioconductor.org/packages/geneplast.data
Licenses: Artistic License 2.0
Build system: r
Synopsis: Input data for the geneplast package via AnnotationHub
Description:

The package geneplast.data provides datasets from different sources via AnnotationHub to use in geneplast pipelines. The datasets have species, phylogenetic trees, and orthology relationships among eukaryotes from different orthologs databases.

r-genextender 1.36.0
Propagated dependencies: r-wordcloud@2.6 r-tm@0.7-16 r-snowballc@0.7.1 r-rtracklayer@1.70.0 r-rcolorbrewer@1.1-3 r-org-rn-eg-db@3.22.0 r-networkd3@0.4.1 r-go-db@3.22.0 r-dplyr@1.1.4 r-data-table@1.17.8 r-biocstyle@2.38.0 r-annotationdbi@1.72.0
Channel: guix-bioc
Location: guix-bioc/packages/g.scm (guix-bioc packages g)
Home page: https://github.com/Bohdan-Khomtchouk/geneXtendeR
Licenses: GPL 3+
Build system: r
Synopsis: Optimized Functional Annotation Of ChIP-seq Data
Description:

geneXtendeR optimizes the functional annotation of ChIP-seq peaks by exploring relative differences in annotating ChIP-seq peak sets to variable-length gene bodies. In contrast to prior techniques, geneXtendeR considers peak annotations beyond just the closest gene, allowing users to see peak summary statistics for the first-closest gene, second-closest gene, ..., n-closest gene whilst ranking the output according to biologically relevant events and iteratively comparing the fidelity of peak-to-gene overlap across a user-defined range of upstream and downstream extensions on the original boundaries of each gene's coordinates. Since different ChIP-seq peak callers produce different differentially enriched peaks with a large variance in peak length distribution and total peak count, annotating peak lists with their nearest genes can often be a noisy process. As such, the goal of geneXtendeR is to robustly link differentially enriched peaks with their respective genes, thereby aiding experimental follow-up and validation in designing primers for a set of prospective gene candidates during qPCR.

r-geneattribution 1.36.0
Propagated dependencies: r-seqinfo@1.0.0 r-rtracklayer@1.70.0 r-org-hs-eg-db@3.22.0 r-iranges@2.44.0 r-genomicranges@1.62.0 r-genomicfeatures@1.62.0 r-biocgenerics@0.56.0
Channel: guix-bioc
Location: guix-bioc/packages/g.scm (guix-bioc packages g)
Home page: https://bioconductor.org/packages/geneAttribution
Licenses: Artistic License 2.0
Build system: r
Synopsis: Identification of candidate genes associated with genetic variation
Description:

Identification of the most likely gene or genes through which variation at a given genomic locus in the human genome acts. The most basic functionality assumes that the closer gene is to the input locus, the more likely the gene is to be causative. Additionally, any empirical data that links genomic regions to genes (e.g. eQTL or genome conformation data) can be used if it is supplied in the UCSC .BED file format.

r-gsgalgor 1.20.0
Propagated dependencies: r-survival@3.8-3 r-proxy@0.4-27 r-nsga2r@1.1 r-matchingr@2.0.0 r-foreach@1.5.2 r-doparallel@1.0.17 r-cluster@2.1.8.1
Channel: guix-bioc
Location: guix-bioc/packages/g.scm (guix-bioc packages g)
Home page: https://github.com/harpomaxx/GSgalgoR
Licenses: Expat
Build system: r
Synopsis: An Evolutionary Framework for the Identification and Study of Prognostic Gene Expression Signatures in Cancer
Description:

This package provides a multi-objective optimization algorithm for disease sub-type discovery based on a non-dominated sorting genetic algorithm. The Galgo framework combines the advantages of clustering algorithms for grouping heterogeneous omics data and the searching properties of genetic algorithms for feature selection. The algorithm search for the optimal number of clusters determination considering the features that maximize the survival difference between sub-types while keeping cluster consistency high.

r-ggseqalign 1.4.0
Propagated dependencies: r-pwalign@1.6.0 r-ggplot2@4.0.1 r-dplyr@1.1.4
Channel: guix-bioc
Location: guix-bioc/packages/g.scm (guix-bioc packages g)
Home page: https://github.com/simeross/ggseqalign
Licenses: Artistic License 2.0
Build system: r
Synopsis: Minimal Visualization of Sequence Alignments
Description:

Simple visualizations of alignments of DNA or AA sequences as well as arbitrary strings. Compatible with Biostrings and ggplot2. The plots are fully customizable using ggplot2 modifiers such as theme().

r-gatefinder 1.30.0
Propagated dependencies: r-splancs@2.01-45 r-mvoutlier@2.1.4 r-flowfp@1.68.0 r-flowcore@2.22.0 r-diptest@0.77-2
Channel: guix-bioc
Location: guix-bioc/packages/g.scm (guix-bioc packages g)
Home page: https://bioconductor.org/packages/GateFinder
Licenses: Artistic License 2.0
Build system: r
Synopsis: Projection-based Gating Strategy Optimization for Flow and Mass Cytometry
Description:

Given a vector of cluster memberships for a cell population, identifies a sequence of gates (polygon filters on 2D scatter plots) for isolation of that cell type.

r-gpaexample 1.22.0
Channel: guix-bioc
Location: guix-bioc/packages/g.scm (guix-bioc packages g)
Home page: http://dongjunchung.github.io/GPA/
Licenses: GPL 2+
Build system: r
Synopsis: Example data for the GPA package (Genetic analysis incorporating Pleiotropy and Annotation)
Description:

Example data for the GPA package, consisting of the p-values of 1,219,805 SNPs for five psychiatric disorder GWAS from the psychiatric GWAS consortium (PGC), with the annotation data using genes preferentially expressed in the central nervous system (CNS).

r-genefu 2.42.0
Propagated dependencies: r-survcomp@1.60.0 r-mclust@6.1.2 r-limma@3.66.0 r-impute@1.84.0 r-ic10trainingdata@2.0.1 r-ic10@2.0.2 r-biomart@2.66.0 r-amap@0.8-20 r-aims@1.42.0
Channel: guix-bioc
Location: guix-bioc/packages/g.scm (guix-bioc packages g)
Home page: http://www.pmgenomics.ca/bhklab/software/genefu
Licenses: Artistic License 2.0
Build system: r
Synopsis: Computation of Gene Expression-Based Signatures in Breast Cancer
Description:

This package contains functions implementing various tasks usually required by gene expression analysis, especially in breast cancer studies: gene mapping between different microarray platforms, identification of molecular subtypes, implementation of published gene signatures, gene selection, and survival analysis.

r-gdr 1.8.0
Propagated dependencies: r-gdrutils@1.8.0 r-gdrimport@1.8.1 r-gdrcore@1.8.0
Channel: guix-bioc
Location: guix-bioc/packages/g.scm (guix-bioc packages g)
Home page: https://github.com/gdrplatform/gDR
Licenses: Artistic License 2.0
Build system: r
Synopsis: Umbrella package for R packages in the gDR suite
Description:

Package is a part of the gDR suite. It reexports functions from other packages in the gDR suite that contain critical processing functions and utilities. The vignette walks through the full processing pipeline for drug response analyses that the gDR suite offers.

r-gsalightning 1.38.0
Propagated dependencies: r-matrix@1.7-4 r-data-table@1.17.8
Channel: guix-bioc
Location: guix-bioc/packages/g.scm (guix-bioc packages g)
Home page: https://github.com/billyhw/GSALightning
Licenses: FSDG-compatible
Build system: r
Synopsis: Fast Permutation-based Gene Set Analysis
Description:

GSALightning provides a fast implementation of permutation-based gene set analysis for two-sample problem. This package is particularly useful when testing simultaneously a large number of gene sets, or when a large number of permutations is necessary for more accurate p-values estimation.

r-grmetrics 1.36.0
Propagated dependencies: r-summarizedexperiment@1.40.0 r-s4vectors@0.48.0 r-plotly@4.11.0 r-ggplot2@4.0.1 r-drc@3.0-1
Channel: guix-bioc
Location: guix-bioc/packages/g.scm (guix-bioc packages g)
Home page: https://github.com/uc-bd2k/GRmetrics
Licenses: GPL 3
Build system: r
Synopsis: Calculate growth-rate inhibition (GR) metrics
Description:

This package provides functions for calculating and visualizing growth-rate inhibition (GR) metrics.

r-genesis 2.40.0
Propagated dependencies: r-snprelate@1.44.0 r-seqvartools@1.48.0 r-seqarray@1.50.0 r-s4vectors@0.48.0 r-reshape2@1.4.5 r-matrix@1.7-4 r-iranges@2.44.0 r-igraph@2.2.1 r-gwastools@1.56.0 r-genomicranges@1.62.0 r-gdsfmt@1.46.0 r-data-table@1.17.8 r-biocparallel@1.44.0 r-biocgenerics@0.56.0 r-biobase@2.70.0
Channel: guix-bioc
Location: guix-bioc/packages/g.scm (guix-bioc packages g)
Home page: https://github.com/UW-GAC/GENESIS
Licenses: GPL 3
Build system: r
Synopsis: GENetic EStimation and Inference in Structured samples (GENESIS): Statistical methods for analyzing genetic data from samples with population structure and/or relatedness
Description:

The GENESIS package provides methodology for estimating, inferring, and accounting for population and pedigree structure in genetic analyses. The current implementation provides functions to perform PC-AiR (Conomos et al., 2015, Gen Epi) and PC-Relate (Conomos et al., 2016, AJHG). PC-AiR performs a Principal Components Analysis on genome-wide SNP data for the detection of population structure in a sample that may contain known or cryptic relatedness. Unlike standard PCA, PC-AiR accounts for relatedness in the sample to provide accurate ancestry inference that is not confounded by family structure. PC-Relate uses ancestry representative principal components to adjust for population structure/ancestry and accurately estimate measures of recent genetic relatedness such as kinship coefficients, IBD sharing probabilities, and inbreeding coefficients. Additionally, functions are provided to perform efficient variance component estimation and mixed model association testing for both quantitative and binary phenotypes.

Total results: 2911