k3ylabs/cosoco-image-dataset huggingface dataset:
Package: r-bioc-bioccheck (1.30.0+dfsg-1)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/BiocCheck/
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-api-bioc-3.14, r-bioc-biocviews (>= 1.33.7), r-cran-biocmanager, r-cran-stringdist, r-bioc-graph, r-cran-httr, r-cran-optparse, r-cran-codetools, r-cran-knitr
Description:  Bioconductor-specific package checks Executes Bioconductor-specific package checks.
Package: r-bioc-biocfilecache (2.2.1+dfsg-1)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/BiocFileCache/
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-api-bioc-3.14, r-cran-dbplyr (>= 1.0.0), r-cran-dplyr, r-cran-rsqlite, r-cran-dbi, r-cran-rappdirs, r-cran-filelock, r-cran-curl, r-cran-httr
Description:  GNU R management of files across sessions This package creates a persistent on-disk cache of files that the user can add, update, and retrieve. It is useful for managing resources (such as custom Txdb objects) that are costly or difficult to create, web resources, and data files used across sessions.
Package: r-bioc-biocgenerics (0.40.0-1)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/BiocGenerics/
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0
Description:  generic functions for Bioconductor S4 generic functions needed by many other Bioconductor packages. . Bioconductor provides tools for the analysis and comprehension of high-throughput genomic data. Bioconductor uses the R statistical programming language, and is open source and open development.
Package: r-bioc-biocio (1.4.0+dfsg-1)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/BiocIO/
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-api-bioc-3.14, r-bioc-biocgenerics, r-bioc-s4vectors
Description:  standard input and output for Bioconductor packages Implements `import()` and `export()` standard generics for importing and exporting biological data formats. `import()` supports whole-file as well as chunk-wise iterative import. The `import()` interface optionally provides a standard mechanism for 'lazy' access via `filter()` (on row or element-like components of the file resource), `select()` (on column-like components of the file resource) and `collect()`. The `import()` interface optionally provides transparent access to remote (e.g. via https) as well as local access. Developers can register a file extension, e.g., `.loom` for dispatch from character-based URIs to specific `import()` / `export()` methods based on classes representing file types, e.g., `LoomFile()`.
Package: r-bioc-biocneighbors (1.12.0+ds-1)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/BiocNeighbors/
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-api-bioc-3.14, r-cran-rcpp, r-bioc-s4vectors, r-bioc-biocparallel, r-cran-matrix, r-cran-rcpphnsw, libc6 (>= 2.34), libgcc-s1 (>= 3.0), libstdc++6 (>= 11)
Description:  Nearest Neighbor Detection for Bioconductor Packages Implements exact and approximate methods for nearest neighbor detection, in a framework that allows them to be easily switched within Bioconductor packages or workflows. Exact searches can be performed using the k-means for k-nearest neighbors algorithm or with vantage point trees. Approximate searches can be performed using the Annoy or HNSW libraries. Searching on either Euclidean or Manhattan distances is supported. Parallelization is achieved for all methods by using BiocParallel. Functions are also provided to search for all neighbors within a given distance.
Package: r-bioc-biocparallel (1.28.3-1)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/BiocParallel/
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-api-bioc-3.14, r-cran-futile.logger, r-cran-snow, r-cran-bh, libc6 (>= 2.34), libgcc-s1 (>= 3.0), libstdc++6 (>= 5.2)
Description:  BioConductor facilities for parallel evaluation This BioConductor package provides modified versions and novel implementation of functions for parallel evaluation, tailored to use with Bioconductor objects.
Package: r-bioc-biocsingular (1.10.0+ds-1)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/BiocSingular/
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-api-bioc-3.14, r-bioc-biocgenerics, r-bioc-s4vectors, r-cran-matrix, r-bioc-delayedarray, r-bioc-biocparallel, r-bioc-scaledmatrix, r-cran-irlba, r-cran-rsvd, r-cran-rcpp, r-bioc-beachmat, libc6 (>= 2.14), libgcc-s1 (>= 3.0), libstdc++6 (>= 11)
Description:  Singular Value Decomposition for Bioconductor Packages Implements exact and approximate methods for singular value decomposition and principal components analysis, in a framework that allows them to be easily switched within Bioconductor packages or workflows. Where possible, parallelization is achieved using the BiocParallel framework.
Package: r-bioc-biocstyle (2.22.0+dfsg-1)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/BiocStyle/
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-api-bioc-3.14, r-cran-bookdown, r-cran-knitr (>= 1.30), r-cran-rmarkdown (>= 1.2), r-cran-yaml, r-cran-biocmanager, texlive-bibtex-extra
Description:  standard styles for vignettes and other Bioconductor documents Provides standard formatting styles for Bioconductor PDF and HTML documents. Package vignettes illustrate use and functionality.
Package: r-bioc-biocversion (3.14.0-1)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/BiocVersion/
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-api-bioc-3.14
Description:  set the appropriate version of Bioconductor packages This package provides repository information for the appropriate version of Bioconductor.
Package: r-bioc-biocviews (1.62.1-1)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/biocViews/
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-api-bioc-3.14, r-bioc-biobase, r-bioc-graph (>= 1.9.26), r-bioc-rbgl (>= 1.13.5), r-cran-xml, r-cran-rcurl, r-cran-runit, r-cran-biocmanager
Description:  Categorized views of R package repositories Infrastructure to support 'views' used to classify Bioconductor packages. 'biocViews' are directed acyclic graphs of terms from a controlled vocabulary. There are three major classifications, corresponding to 'software', 'annotation', and 'experiment data' packages.
Package: r-bioc-biomart (2.50.3+dfsg-1)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/biomaRt/
Depends: r-base-core (>= 4.1.2-1ubuntu2), r-api-4.0, r-api-bioc-3.14, r-cran-xml, r-bioc-annotationdbi, r-cran-progress, r-cran-stringr, r-cran-httr, r-cran-digest, r-bioc-biocfilecache, r-cran-rappdirs, r-cran-xml2
Description:  GNU R Interface to BioMart databases (Ensembl, COSMIC, Wormbase and Gramene) In recent years a wealth of biological data has become available in public data repositories. Easy access to these valuable data resources and firm integration with data analysis is needed for comprehensive bioinformatics data analysis. biomaRt provides an interface to a growing collection of databases implementing the BioMart software suite (http://www.biomart.org). The package enables retrieval of large amounts of data in a uniform way without the need to know the underlying database schemas or write complex SQL queries. Examples of BioMart databases are Ensembl, COSMIC, Uniprot, HGNC, Gramene, Wormbase and dbSNP mapped to Ensembl. These major databases give biomaRt users direct access to a diverse set of data and enable a wide range of powerful online queries from gene annotation to database mining.
Package: r-bioc-biomformat (1.22.0+dfsg-1)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/biomformat/
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-api-bioc-3.14, r-cran-plyr (>= 1.8), r-cran-jsonlite (>= 0.9.16), r-cran-matrix (>= 1.2)
Description:  GNU R interface package for the BIOM file format This is an R package for interfacing with the BIOM format. This package includes basic tools for reading biom-format files, accessing and subsetting data tables from a biom object (which is more complex than a single table), as well as limited support for writing a biom-object back to a biom-format file. The design of this API is intended to match the Python API and other tools included with the biom-format project, but with a decidedly "R flavor" that should be familiar to R users. This includes S4 classes and methods, as well as extensions of common core functions/methods.
Package: r-bioc-biostrings (2.62.0-1)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/Biostrings/
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-api-bioc-3.14, r-bioc-biocgenerics (>= 0.37.0), r-bioc-s4vectors (>= 0.27.12), r-bioc-iranges (>= 2.23.9), r-bioc-xvector (>= 0.29.2), r-bioc-genomeinfodb, r-cran-crayon, libc6 (>= 2.14)
Description:  GNU R string objects representing biological sequences Memory efficient string containers, string matching algorithms, and other utilities, for fast manipulation of large biological sequences or set of sequences.
Package: r-bioc-biovizbase (1.42.0-1)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/biovizBase/
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-api-bioc-3.14, r-cran-scales, r-cran-hmisc, r-cran-rcolorbrewer, r-cran-dichromat, r-bioc-biocgenerics, r-bioc-s4vectors (>= 0.23.19), r-bioc-iranges (>= 1.99.28), r-bioc-genomeinfodb (>= 1.5.14), r-bioc-genomicranges (>= 1.23.21), r-bioc-summarizedexperiment, r-bioc-biostrings (>= 2.33.11), r-bioc-rsamtools (>= 1.17.28), r-bioc-genomicalignments (>= 1.1.16), r-bioc-genomicfeatures (>= 1.21.19), r-bioc-annotationdbi, r-bioc-variantannotation (>= 1.11.4), r-bioc-ensembldb (>= 1.99.13), r-bioc-annotationfilter (>= 0.99.8), r-cran-rlang, libc6 (>= 2.2.5)
Description:  GNU R basic graphic utilities for visualization of genomic data The biovizBase package is designed to provide a set of utilities, color schemes and conventions for genomic data. It serves as the base for various high-level packages for biological data visualization. This saves development effort and encourages consistency.
Package: r-bioc-bitseq (1.38.0+dfsg-1)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/BitSeq/
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-api-bioc-3.14, r-bioc-rsamtools (>= 1.99.3), r-bioc-s4vectors, r-bioc-iranges, r-bioc-rhtslib (>= 1.15.5), libc6 (>= 2.34), libcurl4 (>= 7.18.0), libgcc-s1 (>= 3.0), libgomp1 (>= 6), libstdc++6 (>= 11)
Description:  transcript expression inference and analysis for RNA-seq data The BitSeq package is targeted for transcript expression analysis and differential expression analysis of RNA-seq data in two stage process. In the first stage it uses Bayesian inference methodology to infer expression of individual transcripts from individual RNA-seq experiments. The second stage of BitSeq embraces the differential expression analysis of transcript expression. Providing expression estimates from replicates of multiple conditions, Log-Normal model of the estimates is used for inferring the condition mean transcript expression and ranking the transcripts based on the likelihood of differential expression.
Package: r-bioc-bladderbatch (1.32.0-1)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/data/experiment/bladderbatch/
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-api-bioc-3.14, r-bioc-biobase
Description:  GNU R bladder gene expression data illustrating batch effects This package contains microarray gene expression data on 57 bladder samples from 5 batches. The data are used as an illustrative example for the sva package.
Package: r-bioc-bluster (1.4.0+dfsg-1)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/bluster/
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-api-bioc-3.14, r-cran-cluster, r-cran-matrix, r-cran-rcpp, r-cran-igraph, r-bioc-s4vectors, r-bioc-biocparallel, r-bioc-biocneighbors, libc6 (>= 2.14), libgcc-s1 (>= 3.0), libstdc++6 (>= 11)
Description:  Clustering Algorithms for Bioconductor Wraps common clustering algorithms in an easily extended S4 framework. Backends are implemented for hierarchical, k-means and graph-based clustering. Several utilities are also provided to compare and evaluate clustering results.
Package: r-bioc-bsgenome (1.62.0-1)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/BSgenome/
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-api-bioc-3.14, r-bioc-biocgenerics (>= 0.13.8), r-bioc-s4vectors (>= 0.17.28), r-bioc-iranges (>= 2.13.16), r-bioc-genomeinfodb (>= 1.25.6), r-bioc-genomicranges (>= 1.31.10), r-bioc-biostrings (>= 2.47.6), r-bioc-rtracklayer (>= 1.39.7), r-cran-matrixstats, r-bioc-xvector (>= 0.29.3), r-bioc-rsamtools
Description:  BioConductor infrastructure for Biostrings-based genome data packages This BioConductor module provides some basic infrastructure for Biostrings-based genome data packages.
Package: r-bioc-chemminer (3.46.0+dfsg-1)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/ChemmineR/
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-api-bioc-3.14, r-cran-rjson, r-cran-rcurl, r-cran-dbi, r-cran-digest, r-bioc-biocgenerics, r-cran-rcpp (>= 0.11.0), r-cran-ggplot2, r-cran-gridextra, r-cran-png, r-cran-base64enc, r-cran-dt, r-cran-rsvg, r-cran-jsonlite, r-cran-stringi, r-cran-bh, libc6 (>= 2.14), libgcc-s1 (>= 3.0), libstdc++6 (>= 11)
Description:  Cheminformatics Toolkit for R ChemmineR is a cheminformatics package for analyzing drug-like small molecule data in R. Its latest version contains functions for efficient processing of large numbers of molecules, physicochemical/structural property predictions, structural similarity searching, classification and clustering of compound libraries with a wide spectrum of algorithms. In addition, it offers visualization functions for compound clustering results and chemical structures.
Package: r-bioc-cner (1.30.0+dfsg-1)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/CNEr/
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-api-bioc-3.14, r-bioc-biostrings (>= 2.33.4), r-cran-dbi (>= 0.7), r-cran-rsqlite (>= 0.11.4), r-bioc-genomeinfodb (>= 1.1.3), r-bioc-genomicranges (>= 1.23.16), r-bioc-rtracklayer (>= 1.25.5), r-bioc-xvector (>= 0.5.4), r-bioc-genomicalignments (>= 1.1.9), r-bioc-s4vectors (>= 0.13.13), r-bioc-iranges (>= 2.5.27), r-cran-readr (>= 0.2.2), r-bioc-biocgenerics, r-cran-reshape2 (>= 1.4.1), r-cran-ggplot2 (>= 2.1.0), r-cran-powerlaw (>= 0.60.3), r-bioc-annotate (>= 1.50.0), r-bioc-go.db (>= 3.3.0), r-cran-r.utils (>= 2.3.0), r-bioc-keggrest (>= 1.14.0), libc6 (>= 2.33)
Description:  CNE Detection and Visualization Large-scale identification and advanced visualization of sets of conserved noncoding elements.
Package: r-bioc-complexheatmap (2.10.0+dfsg-1)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/ComplexHeatmap/
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-api-bioc-3.14, r-cran-circlize (>= 0.4.5), r-cran-getoptlong, r-cran-colorspace, r-cran-clue, r-cran-rcolorbrewer, r-cran-globaloptions (>= 0.1.0), r-cran-png, r-cran-digest, r-bioc-iranges, r-cran-matrixstats, r-cran-foreach, r-cran-doparallel
Description:  make complex heatmaps using GNU R Complex heatmaps are efficient to visualize associations between different sources of data sets and reveal potential patterns. Here the ComplexHeatmap package provides a highly flexible way to arrange multiple heatmaps and supports various annotation graphics.
Package: r-bioc-consensusclusterplus (1.58.0-1)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/ConsensusClusterPlus/
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-api-bioc-3.14, r-bioc-biobase, r-bioc-all, r-cran-cluster
Description:  GNU R determining cluster count and membership ConsensusClusterPlus is a BioCOnductor package providing an algorithm for determining cluster count and membership by stability evidence in unsupervised analysis.
Package: r-bioc-ctc (1.68.0-1)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/ctc/
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-api-bioc-3.14, r-cran-amap
Description:  Cluster and Tree Conversion Tools for export and import classification trees and clusters to other programs.
Package: r-bioc-cummerbund (2.36.0-1)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/cummeRbund/
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-api-bioc-3.14, r-bioc-biocgenerics (>= 0.3.2), r-cran-rsqlite, r-cran-ggplot2, r-cran-reshape2, r-cran-fastcluster, r-bioc-rtracklayer, r-bioc-gviz, r-cran-plyr, r-bioc-s4vectors (>= 0.9.25), r-bioc-biobase
Description:  tool for analysis of Cufflinks RNA-Seq output Allows for persistent storage, access, exploration, and manipulation of Cufflinks high-throughput sequencing data. In addition, provides numerous plotting functions for commonly used visualizations.
Package: r-bioc-dada2 (1.22.0+dfsg-1build2)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/dada2/
Depends: r-base-core (>= 4.1.2-1ubuntu2), r-api-4.0, r-api-bioc-3.14, r-cran-rcpp (>= 0.12.0), r-bioc-biostrings (>= 2.42.1), r-cran-ggplot2 (>= 2.1.0), r-cran-reshape2 (>= 1.4.1), r-bioc-shortread (>= 1.32.0), r-cran-rcppparallel (>= 4.3.0), r-bioc-iranges (>= 2.6.0), r-bioc-xvector (>= 0.16.0), r-bioc-biocgenerics (>= 0.22.0), libc6 (>= 2.34), libgcc-s1 (>= 3.0), libstdc++6 (>= 11)
Description:  sample inference from amplicon sequencing data The dada2 package contributes to software workflows to interpret sequencing data from microbiota - the relative abundance of bacterial and/or yeast, typically measured in the gut. It infers exact amplicon sequence variants (ASVs) from high-throughput amplicon sequencing data, replacing the coarser and less accurate OTU clustering approach. The dada2 pipeline takes as input demultiplexed fastq files, and outputs the sequence variants and their sample-wise abundances after removing substitution and chimera errors. Taxonomic classification is available via a native implementation of the RDP naive Bayesian classifier, and species-level assignment to 16S rRNA gene fragments by exact matching.
Package: r-bioc-degnorm (1.4.0+ds-1)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/DegNorm/
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-api-bioc-3.14, r-cran-rcpp (>= 1.0.2), r-bioc-genomicfeatures, r-cran-foreach, r-bioc-s4vectors, r-cran-doparallel, r-bioc-rsamtools (>= 1.31.2), r-bioc-genomicalignments, r-cran-heatmaply, r-cran-data.table, r-cran-ggplot2, r-bioc-genomicranges, r-bioc-iranges, r-cran-plyr, r-cran-plotly, r-cran-viridis, r-cran-rcpparmadillo, libblas3 | libblas.so.3, libc6 (>= 2.29), libgcc-s1 (>= 3.0), libgomp1 (>= 4.9), libstdc++6 (>= 9)
Description:  DegNorm: degradation normalization for RNA-seq data This package performs degradation normalization in bulk RNA-seq data to improve differential expression analysis accuracy.
Package: r-bioc-degreport (1.30.0+dfsg-1)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/DEGreport/
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-broom, r-cran-circlize, r-bioc-complexheatmap, r-cran-cowplot, r-bioc-consensusclusterplus, r-cran-cluster, r-bioc-deseq2, r-cran-dplyr, r-bioc-edger, r-cran-ggplot2, r-cran-ggdendro, r-cran-ggrepel, r-cran-knitr, r-cran-logging, r-cran-lasso2, r-cran-magrittr, r-cran-nozzle.r1, r-cran-psych, r-cran-rcolorbrewer, r-cran-reshape, r-cran-rlang, r-cran-scales, r-cran-stringr, r-bioc-s4vectors, r-bioc-summarizedexperiment, r-cran-tidyr, r-cran-tibble
Description:  BioConductor report of DEG analysis Creation of a HTML report of differential expression analyses of count data. It integrates some of the code mentioned in DESeq2 and edgeR vignettes, and report a ranked list of genes according to the fold changes mean and variability for each selected gene.
Package: r-bioc-delayedarray (0.20.0+dfsg-1)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/DelayedArray/
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-api-bioc-3.14, r-cran-matrix, r-bioc-biocgenerics (>= 0.37.0), r-bioc-matrixgenerics (>= 1.1.3), r-bioc-s4vectors (>= 0.27.2), r-bioc-iranges (>= 2.17.3), libc6 (>= 2.4)
Description:  BioConductor delayed operations on array-like objects Wrapping an array-like object (typically an on-disk object) in a DelayedArray object allows one to perform common array operations on it without loading the object in memory. In order to reduce memory usage and optimize performance, operations on the object are either delayed or executed using a block processing mechanism. Note that this also works on in-memory array-like objects like DataFrame objects (typically with Rle columns), Matrix objects, and ordinary arrays and data frames.
Package: r-bioc-delayedmatrixstats (1.16.0+ds-1)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/DelayedMatrixStats/
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-api-bioc-3.14, r-bioc-matrixgenerics (>= 1.5.3), r-bioc-delayedarray (>= 0.17.6), r-cran-matrixstats (>= 0.60.0), r-bioc-sparsematrixstats, r-cran-matrix, r-bioc-s4vectors (>= 0.17.5), r-bioc-iranges (>= 2.25.10)
Description:  Functions on Rows and Columns of 'DelayedMatrix' Objects A port of the 'matrixStats' API for use with DelayedMatrix objects from the 'DelayedArray' package. High-performing functions operating on rows and columns of DelayedMatrix objects, e.g. col / rowMedians(), col / rowRanks(), and col / rowSds(). Functions optimized per data type and for subsetted calculations such that both memory usage and processing time is minimized.
Package: r-bioc-demixt (1.10.0-1)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/DeMixT/
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-api-bioc-3.14, r-cran-rcpp (>= 1.0.0), r-bioc-summarizedexperiment, r-cran-knitr, r-cran-kernsmooth, r-cran-matrixcalc, r-cran-rmarkdown, r-cran-matrixstats, r-cran-truncdist, r-cran-base64enc, r-cran-ggplot2, libc6 (>= 2.29), libgcc-s1 (>= 3.0), libgomp1 (>= 4.9), libstdc++6 (>= 5.2)
Description:  Cell type-specific deconvolution of heterogeneous tumor samples When studying cancer cells from tumors excised from patients, the samples will be a mixture of tumors and healthy cells, e.g. from invading immune cells. For comparing samples, the interest may be more on comparing the transcriptome of the tumors themselves. . This package prepares the statistical separation (deconvolution) of RNAseq or microarray generated expression data for two or three components.
Package: r-bioc-deseq2 (1.34.0+dfsg-1)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/DESeq2/
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-api-bioc-3.14, r-bioc-s4vectors (>= 0.23.18), r-bioc-iranges, r-bioc-genomicranges, r-bioc-summarizedexperiment (>= 1.1.6), r-bioc-biocgenerics (>= 0.7.5), r-bioc-biobase, r-bioc-biocparallel, r-bioc-genefilter, r-cran-locfit, r-bioc-geneplotter, r-cran-ggplot2, r-cran-rcpp (>= 0.11.0), r-cran-rcpparmadillo, libblas3 | libblas.so.3, libc6 (>= 2.29), libgcc-s1 (>= 3.0), liblapack3 | liblapack.so.3, libstdc++6 (>= 9)
Description:  R package for RNA-Seq Differential Expression Analysis Differential gene expression analysis based on the negative binomial distribution. Estimate variance-mean dependence in count data from high-throughput sequencing assays and test for differential expression based on a model using the negative binomial distribution.
Package: r-bioc-deseq (1.39.0-7)
Section: universe/gnu-r
Homepage: https://bioconductor.org/packages/DESeq/
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-api-bioc-3.14, r-bioc-biocgenerics (>= 0.7.5), r-bioc-biobase (>= 2.21.7), r-cran-locfit, r-cran-lattice, r-bioc-genefilter, r-bioc-geneplotter, r-cran-mass, r-cran-rcolorbrewer, libc6 (>= 2.4)
Description:  GNU R differential gene expression analysis BioConductor package to estimate variance-mean dependence in count data from high-throughput sequencing assays and test for differential expression based on a model using the negative binomial distribution.