k3ylabs/cosoco-image-dataset huggingface dataset:
Package: r-bioc-nanostringqcpro (1.26.0-1)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/NanoStringQCPro/
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-api-bioc-3.14, r-bioc-annotationdbi (>= 1.26.0), r-bioc-org.hs.eg.db (>= 2.14.0), r-bioc-biobase (>= 2.24.0), r-cran-knitr (>= 1.12), r-cran-nmf (>= 0.20.5), r-cran-rcolorbrewer (>= 1.0-5), r-cran-png (>= 0.1-7)
Description:  processing and QA for NanoString mRNA expression data NanoStringQCPro provides a set of quality metrics that can be used to assess the quality of NanoString mRNA gene expression data -- i.e. to identify outlier probes and outlier samples. It also provides different background subtraction and normalization approaches for this data. It outputs suggestions for flagging samples/probes and an easily sharable html quality control output.
Package: r-bioc-netsam (1.30.0-3)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/NetSAM/
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-api-bioc-3.14, r-cran-igraph (>= 0.6-1), r-cran-seriation (>= 1.0-6), r-bioc-graph (>= 1.34.0)
Description:  Network Seriation And Modularization The NetSAM (Network Seriation and Modularization) package takes an edge-list representation of a network as an input, performs network seriation and modularization analysis, and generates as files that can be used as an input for the one-dimensional network visualization tool NetGestalt (http://www.netgestalt.org) or other network analysis.
Package: r-bioc-noiseq (2.38.0-1)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/NOISeq/
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-api-bioc-3.14, r-bioc-biobase (>= 2.13.11), r-cran-matrix (>= 1.2)
Description:  Exploratory analysis and differential expression for RNA-seq data Analysis of RNA-seq expression data or other similar kind of data. Exploratory plots to evualuate saturation, count distribution, expression per chromosome, type of detected features, features length, etc. Differential expression between two experimental conditions with no parametric assumptions.
Package: r-bioc-oligo (1.58.0+ds-1)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/oligo/
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-api-bioc-3.14, r-bioc-biocgenerics (>= 0.13.11), r-bioc-oligoclasses (>= 1.29.6), r-bioc-biobase (>= 2.27.3), r-bioc-biostrings (>= 2.35.12), r-bioc-affyio (>= 1.35.0), r-bioc-affxparser (>= 1.39.4), r-cran-dbi (>= 0.3.1), r-cran-ff, r-bioc-preprocesscore (>= 1.29.0), r-cran-rsqlite (>= 1.0.0), r-bioc-zlibbioc, libc6 (>= 2.29), zlib1g (>= 1:1.1.4)
Description:  Preprocessing tools for oligonucleotide arrays A package to analyze oligonucleotide arrays (expression/SNP/tiling/exon) at probe-level. It currently supports Affymetrix (CEL files) and NimbleGen arrays (XYS files).
Package: r-bioc-oligoclasses (1.56.0-1)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/oligoClasses/
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-api-bioc-3.14, r-bioc-biocgenerics (>= 0.27.1), r-bioc-biobase (>= 2.17.8), r-bioc-iranges (>= 2.5.17), r-bioc-genomicranges (>= 1.23.7), r-bioc-summarizedexperiment, r-bioc-biostrings (>= 2.23.6), r-bioc-affyio (>= 1.23.2), r-cran-foreach, r-cran-biocmanager, r-bioc-s4vectors (>= 0.9.25), r-cran-rsqlite, r-cran-dbi, r-cran-ff
Description:  Classes for high-throughput arrays supported by oligo and crlmm This package contains class definitions, validity checks, and initialization methods for classes used by the oligo and crlmm packages.
Package: r-bioc-org.hs.eg.db (3.14.0-1)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/data/experiment/org.Hs.eg.db/
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-bioc-annotationdbi (>= 1.55.1)
Description:  genome-wide annotation for Human This package provides descriptions of parts of the human genome that have been identified to be coding for RNA, and likely also for proteins. It also offers links to entries of equivalent (orthologous) genes in other species. . This package is prepared from the BioConductor community and contributes to many workflows and routine analyses in computational biology.
Package: r-bioc-organismdbi (1.36.0-1)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/OrganismDbi/
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-api-bioc-3.14, r-bioc-biocgenerics (>= 0.15.10), r-bioc-annotationdbi (>= 1.33.15), r-bioc-genomicfeatures (>= 1.39.4), r-bioc-biobase, r-cran-biocmanager, r-bioc-genomicranges (>= 1.31.13), r-bioc-graph, r-bioc-iranges, r-bioc-rbgl, r-cran-dbi, r-bioc-s4vectors (>= 0.9.25)
Description:  smooth interfacing of different database packages The package enables a simple unified interface to several annotation packages each of which has its own schema by taking advantage of the fact that each of these packages implements a select methods.
Package: r-bioc-pcamethods (1.86.0-1)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/pcaMethods/
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-api-bioc-3.14, r-bioc-biobase, r-bioc-biocgenerics, r-cran-rcpp (>= 0.11.3), r-cran-mass, libc6 (>= 2.14), libgcc-s1 (>= 3.0), libstdc++6 (>= 11)
Description:  BioConductor collection of PCA methods Provides Bayesian PCA, Probabilistic PCA, Nipals PCA, Inverse Non-Linear PCA and the conventional SVD PCA. A cluster based method for missing value estimation is included for comparison. BPCA, PPCA and NipalsPCA may be used to perform PCA on incomplete data as well as for accurate missing value estimation. A set of methods for printing and plotting the results is also provided. All PCA methods make use of the same data structure (pcaRes) to provide a common interface to the PCA results. Initiated at the Max-Planck Institute for Molecular Plant Physiology, Golm, Germany.
Package: r-bioc-phyloseq (1.38.0+dfsg-1)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/phyloseq/
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-api-bioc-3.14, r-cran-ade4 (>= 1.7-4), r-cran-ape (>= 5.0), r-bioc-biobase (>= 2.36.2), r-bioc-biocgenerics (>= 0.22.0), r-bioc-biomformat (>= 1.0.0), r-bioc-biostrings (>= 2.40.0), r-cran-cluster (>= 2.0.4), r-cran-data.table (>= 1.10.4), r-cran-foreach (>= 1.4.3), r-cran-ggplot2 (>= 2.1.0), r-cran-igraph (>= 1.0.1), r-bioc-multtest (>= 2.28.0), r-cran-plyr (>= 1.8.3), r-cran-reshape2 (>= 1.4.1), r-cran-scales (>= 0.4.0), r-cran-vegan (>= 2.5)
Description:  GNU R handling and analysis of high-throughput microbiome census data The Bioconductor module phyloseq provides a set of classes and tools to facilitate the import, storage, analysis, and graphical display of microbiome census data.
Package: r-bioc-preprocesscore (1.56.0+ds-1)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/preprocessCore/
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-api-bioc-3.14, libc6 (>= 2.34), liblapack3 | liblapack.so.3
Description:  BioConductor collection of pre-processing functions This BioConductor module contains a library of pre-processing functions.  It is imported by several other BioConductor modules.
Package: r-bioc-progeny (1.16.0+ds-2)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/progeny/
Depends: r-base-core (>= 4.1.2-1ubuntu2), r-api-4.0, r-api-bioc-3.14, r-bioc-biobase, r-cran-dplyr, r-cran-tidyr, r-cran-ggplot2, r-cran-ggrepel, r-cran-gridextra
Description:  activity inference from gene expression This package provides a function to infer pathway activity from gene expression using PROGENy. It contains the linear model which is described in the publication "Perturbation-response genes reveal signaling footprints in cancer gene expression".
Package: r-bioc-protgenerics (1.26.0-1)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/ProtGenerics/
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-api-bioc-3.14
Description:  S4 generic functions for Bioconductor proteomics infrastructure This Bioconductor package provides S4 generic functions needed by Bioconductor proteomics packages.
Package: r-bioc-purecn (2.0.1+dfsg-1)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/PureCN/
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-api-bioc-3.14, r-bioc-dnacopy, r-bioc-variantannotation (>= 1.14.1), r-bioc-genomicranges (>= 1.20.3), r-bioc-iranges (>= 2.2.1), r-cran-rcolorbrewer, r-bioc-s4vectors, r-cran-data.table, r-bioc-summarizedexperiment, r-bioc-genomeinfodb, r-bioc-genomicfeatures, r-bioc-rsamtools, r-bioc-biobase, r-bioc-biostrings, r-bioc-biocgenerics, r-bioc-rtracklayer, r-cran-ggplot2, r-cran-gridextra, r-cran-futile.logger, r-cran-vgam, r-cran-mclust, r-bioc-rhdf5, r-cran-matrix
Description:  copy number calling and SNV classification using targeted short read sequencing This package estimates tumor purity, copy number, and loss of heterozygosity (LOH), and classifies single nucleotide variants (SNVs) by somatic status and clonality. PureCN is designed for targeted short read sequencing data, integrates well with standard somatic variant detection and copy number pipelines, and has support for tumor samples without matching normal samples.
Package: r-bioc-pwmenrich (4.30.0-1)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/PWMEnrich/
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-api-bioc-3.14, r-bioc-biocgenerics, r-bioc-biostrings, r-bioc-seqlogo, r-cran-gdata, r-cran-evd, r-bioc-s4vectors
Description:  PWM enrichment analysis A toolkit of high-level functions for DNA motif scanning and enrichment analysis built upon Biostrings. The main functionality is PWM enrichment analysis of already known PWMs (e.g. from databases such as MotifDb), but the package also implements high-level functions for PWM scanning and visualisation. The package does not perform "de novo" motif discovery, but is instead focused on using motifs that are either experimentally derived or computationally constructed by other tools.
Package: r-bioc-qtlizer (1.8.0+dfsg-1)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/Qtlizer/
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-api-bioc-3.14, r-cran-httr, r-cran-curl, r-bioc-genomicranges, r-cran-stringi
Description:  Comprehensive QTL annotation of GWAS results This R package provides access to the Qtlizer web server. Qtlizer annotates lists of common small variants (mainly SNPs) and genes in humans with associated changes in gene expression using the most comprehensive database of published quantitative trait loci (QTLs).
Package: r-bioc-qusage (2.28.0-1)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/qusage/
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-api-bioc-3.14, r-bioc-limma (>= 3.14), r-bioc-biobase, r-cran-nlme, r-cran-emmeans, r-cran-fftw
Description:  qusage: Quantitative Set Analysis for Gene Expression This package is an implementation the Quantitative Set Analysis for Gene Expression (QuSAGE) method described in (Yaari G. et al, Nucl Acids Res, 2013). This is a novel Gene Set Enrichment-type test, which is designed to provide a faster, more accurate, and easier to understand test for gene expression studies. qusage accounts for inter-gene correlations using the Variance Inflation Factor technique proposed by Wu et al. (Nucleic Acids Res, 2012). In addition, rather than simply evaluating the deviation from a null hypothesis with a single number (a P value), qusage quantifies gene set activity with a complete probability density function (PDF). From this PDF, P values and confidence intervals can be easily extracted. Preserving the PDF also allows for post-hoc analysis (e.g., pair-wise comparisons of gene set activity) while maintaining statistical traceability. Finally, while qusage is compatible with individual gene statistics from existing methods (e.g., LIMMA), a Welch-based method is implemented that is shown to improve specificity. For questions, contact Chris Bolen (cbolen1@gmail.com) or Steven Kleinstein (steven.kleinstein@yale.edu)
Package: r-bioc-qvalue (2.26.0-1)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/qvalue/
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-api-bioc-3.14, r-cran-ggplot2, r-cran-reshape2
Description:  GNU R package for Q-value estimation for FDR control This package takes a list of p-values resulting from the simultaneous testing of many hypotheses and estimates their q-values. The q-value of a test measures the proportion of false positives incurred (called the false discovery rate) when that particular test is called significant. Various plots are automatically generated, allowing one to make sensible significance cut-offs. Several mathematical results have recently been shown on the conservative accuracy of the estimated q-values from this software. The software can be applied to problems in genomics, brain imaging, astrophysics, and data mining.
Package: r-bioc-rbgl (1.70.0+dfsg-1)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/RBGL/
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-api-bioc-3.14, r-bioc-graph, r-cran-bh, libc6 (>= 2.14), libgcc-s1 (>= 3.0), libstdc++6 (>= 11)
Description:  R interface to the graph algorithms contained in the BOOST library RBGL is part of the BioConductor GNU R suite. It is a fairly extensive and comprehensive interface to the graph algorithms contained in the BOOST C++ libraries.
Package: r-bioc-rcpi (1.30.0+ds-1)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/Rcpi/
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-api-bioc-3.14, r-cran-rcurl, r-cran-rjson, r-cran-foreach, r-cran-doparallel, r-bioc-biostrings, r-bioc-gosemsim, r-bioc-chemminer, r-bioc-fmcsr, r-cran-rcdk (>= 3.3.8)
Description:  molecular informatics toolkit for compound-protein interaction Rcpi offers a molecular informatics toolkit with a comprehensive integration of bioinformatics and chemoinformatics tools for drug discovery.
Package: r-bioc-residualmatrix (1.4.0+dfsg-1)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/ResidualMatrix/
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-api-bioc-3.14, r-cran-matrix, r-bioc-s4vectors, r-bioc-delayedarray
Description:  Creating a DelayedMatrix of Regression Residuals Provides delayed computation of a matrix of residuals after fitting a linear model to each column of an input matrix. Also supports partial computation of residuals where selected factors are to be preserved in the output matrix. Implements a number of efficient methods for operating on the delayed matrix of residuals, most notably matrix multiplication and calculation of row/column sums or means.
Package: r-bioc-rgsepd (1.26.0-1)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/rgsepd/
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-api-bioc-3.14, r-bioc-deseq2, r-bioc-goseq (>= 1.28), r-cran-gplots, r-bioc-biomart, r-bioc-org.hs.eg.db, r-bioc-go.db, r-bioc-summarizedexperiment, r-cran-hash, r-bioc-annotationdbi
Description:  GNU R gene set enrichment / projection displays R/GSEPD is a bioinformatics package for R to help disambiguate transcriptome samples (a matrix of RNA-Seq counts at transcript IDs) by automating differential expression (with DESeq2), then gene set enrichment (with GOSeq), and finally a N-dimensional projection to quantify in which ways each sample is like either treatment group.
Package: r-bioc-rhdf5 (2.38.0+dfsg-2)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/rhdf5/
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-api-bioc-3.14, r-bioc-rhdf5lib (>= 1.13.4), r-bioc-rhdf5filters, libc6 (>= 2.14), libgcc-s1 (>= 3.0), libhdf5-103-1, libstdc++6 (>= 5)
Description:  BioConductor HDF5 interface to R This package provides an interface between HDF5 and R. HDF5's main features are the ability to store and access very large and/or complex datasets and a wide variety of metadata on mass storage (disk) through a completely portable file format. The rhdf5 package is thus suited for the exchange of large and/or complex datasets between R and other software package, and for letting R applications work on datasets that are larger than the available RAM.
Package: r-bioc-rhdf5filters (1.6.0+dfsg-1)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/rhdf5filters/
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-api-bioc-3.14, r-bioc-rhdf5lib, libblosc1 (>= 1.21.1+ds1), libbz2-1.0, libc6 (>= 2.4)
Description:  GNU R HDF5 compression filters This Bioconductor package provides a collection of compression filters for use with HDF5 datasets. . One of the advantages of using HDF5 is that data stored on disk can be compressed, reducing both the space required to store them and the time needed to read those data. This data compression is applied as part of the HDF5 “filter pipeline” that modifies data during I/O operations. HDF5 includes several filter algorithms as standard, and the version of the HDF5 library found in Rhdf5lib is additionally compiled with support for the deflate and szip compression filters which rely on third-party compression libraries. Collectively HDF5 refer to these as the “internal” filters. It is possible to use any combination of these (including none) when writing data using rhdf5.
Package: r-bioc-rhdf5lib (1.16.0+dfsg-1)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/Rhdf5lib/
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-api-bioc-3.14, libc6 (>= 2.4), libhdf5-103-1, libhdf5-dev
Description:  GNU R hdf5 library This GNU R package provides an interface to the C and C++ hdf5 libraries. . HDF5 is a file format and library for storing scientific data.
Package: r-bioc-rhtslib (1.26.0+dfsg-1)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/Rhtslib/
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-api-bioc-3.14, r-bioc-zlibbioc, libbz2-1.0, libc6 (>= 2.34), libcurl4 (>= 7.18.0), liblzma5 (>= 5.1.1alpha+20120614), zlib1g (>= 1:1.2.0)
Description:  HTSlib high-throughput sequencing library as GNU R package This package provides version 1.7 of the 'HTSlib' C library for high-throughput sequence analysis. The package is primarily useful to developers of other R packages who wish to make use of HTSlib. Motivation and instructions for use of this package are in the vignette, vignette(package="Rhtslib", "Rhtslib").
Package: r-bioc-rots (1.22.0-1)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/ROTS/
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-api-bioc-3.14, r-cran-rcpp, r-bioc-biobase, libc6 (>= 2.14), libgcc-s1 (>= 3.0), libstdc++6 (>= 5.2)
Description:  GNU R Teproducibility-Optimized Test Statistic This BioConductor package calculates the Reproducibility-Optimized Test Statistic (ROTS) for differential testing in omics data.
Package: r-bioc-rsamtools (2.10.0-1)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/Rsamtools/
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-api-bioc-3.14, r-bioc-genomeinfodb (>= 1.1.3), r-bioc-genomicranges (>= 1.31.8), r-bioc-biostrings (>= 2.47.6), r-bioc-biocgenerics (>= 0.25.1), r-bioc-s4vectors (>= 0.17.25), r-bioc-iranges (>= 2.13.12), r-bioc-xvector (>= 0.19.7), r-bioc-zlibbioc, r-cran-bitops, r-bioc-biocparallel, r-bioc-rhtslib (>= 1.17.7), libc6 (>= 2.34), libcurl4 (>= 7.18.0), libgcc-s1 (>= 3.0), libstdc++6 (>= 11)
Description:  GNU R binary alignment (BAM), variant call (BCF), or tabix file import This package provides an interface to the 'samtools', 'bcftools', and 'tabix' utilities for manipulating SAM (Sequence Alignment / Map), binary variant call (BCF) and compressed indexed tab-delimited (tabix) files.
Package: r-bioc-rsubread (2.8.1-1)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/Rsubread/
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-api-bioc-3.14, r-cran-matrix, libc6 (>= 2.34), zlib1g (>= 1:1.2.2.4)
Description:  Subread Sequence Alignment and Counting for R Alignment, quantification and analysis of second and third generation sequencing data. Includes functionality for read mapping, read counting, SNP calling, structural variant detection and gene fusion discovery. . Can be applied to all major sequencing techologies and to both short and long sequence reads.
Package: r-bioc-rtracklayer (1.54.0-1)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/rtracklayer/
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-api-bioc-3.14, r-bioc-genomicranges (>= 1.37.2), r-cran-xml (>= 1.98-0), r-bioc-biocgenerics (>= 0.35.3), r-bioc-s4vectors (>= 0.23.18), r-bioc-iranges (>= 2.13.13), r-bioc-xvector (>= 0.19.7), r-bioc-genomeinfodb (>= 1.15.2), r-bioc-biostrings (>= 2.47.6), r-bioc-zlibbioc, r-cran-rcurl (>= 1.4-2), r-bioc-rsamtools (>= 1.31.2), r-bioc-genomicalignments (>= 1.15.6), r-bioc-biocio, r-cran-restfulr (>= 0.0.13), libc6 (>= 2.34), zlib1g (>= 1:1.1.4)
Description:  GNU R interface to genome browsers and their annotation tracks Extensible framework for interacting with multiple genome browsers (currently UCSC built-in) and manipulating annotation tracks in various formats (currently GFF, BED, bedGraph, BED15, WIG, BigWig and 2bit built-in). The user may export/import tracks to/from the supported browsers, as well as query and modify the browser state, such as the current viewport.
Package: r-bioc-rwikipathways (1.14.0+dfsg-1)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/rWikiPathways/
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-api-bioc-3.14, r-cran-httr, r-cran-xml, r-cran-rjson, r-cran-data.table, r-cran-tidyr, r-cran-rcurl
Description:  GNU R client library for the WikiPathways API WikiPathways is a well-known repository for biological pathways that provides unique tools to the research community for content creation, editing and utilization. . The package rWikiPathways leverages the WikiPathways API to communicate between GNU R and WikiPathways, allowing any pathway to be queried, interrogated and downloaded in both data and image formats. Queries are typically performed based on "Xrefs", standardized identifiers for genes, proteins and metabolites. Once you can identified a pathway, you can use the WPID (WikiPathways identifier) to make additional queries.
Package: r-bioc-s4vectors (0.32.3-1)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/S4Vectors/
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-api-bioc-3.14, r-bioc-biocgenerics (>= 0.37.0), libc6 (>= 2.14)
Description:  BioConductor S4 implementation of vectors and lists The S4Vectors package defines the Vector and List virtual classes and a set of generic functions that extend the semantic of ordinary vectors and lists in R. Package developers can easily implement vector-like or list-like objects as concrete subclasses of Vector or List. In addition, a few low-level concrete subclasses of general interest (e.g. DataFrame, Rle, and Hits) are implemented in the S4Vectors package itself (many more are implemented in the IRanges package and in other Bioconductor infrastructure packages).
Package: r-bioc-savr (1.32.0-1)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/savR/
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-api-bioc-3.14, r-cran-ggplot2, r-cran-reshape2, r-cran-scales, r-cran-gridextra, r-cran-xml
Description:  GNU R parse and analyze Illumina SAV files This BioConductor module enables to parse Illumina Sequence Analysis Viewer (SAV) files, access data, and generate QC plots.
Package: r-bioc-scaledmatrix (1.2.0+dfsg-1)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/ScaledMatrix/
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-api-bioc-3.14, r-cran-matrix, r-bioc-s4vectors, r-bioc-delayedarray
Description:  creating a DelayedMatrix of scaled and centered values using GNU R Provides delayed computation of a matrix of scaled and centered values. The result is equivalent to using the scale() function but avoids explicit realization of a dense matrix during block processing. This permits greater efficiency in common operations, most notably matrix multiplication.