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Provides `dplyr` verbs (`mutate`, `select`, `filter`, etc...) supporting `S4Vectors::DataFrame` objects. Importantly, this is achieved without conversion to an intermediate `tibble`. Adds grouping infrastructure to `DataFrame` which is respected by the transformation verbs.

Extends beachmat to initialize tatami matrices from TileDB-backed arrays. This allows C++ code in downstream packages to directly call the TileDB C/C++ library to access array data, without the need for block processing via DelayedArray. Developers only need to import this package to automatically extend the capabilities of beachmat::initializeCpp to TileDBArray instances.

GraphExperiment provides users and developers with an S4 class that extends `SingleCellExperiment` by offering infrastructure to store and retrieve networks (`igraph` objects) representing how assay features and/or observations are associated with each other. The class was designed to store networks inferred from high-dimensional quantitative data, with feature-feature networks including gene coexpression networks (GCNs), gene regulatory networks (GRNs), and co-abundance networks (from proteomics and metabolomics), and observation-observation network including cell-cell distances, species-species relationships, and sample-sample similarities.

Implements a DelayedArray backend for reading and writing dense or sparse arrays in the TileDB format. The resulting TileDBArrays are compatible with all Bioconductor pipelines that can accept DelayedArray instances.

Provides a consistent C++ class interface for reading from a variety of commonly used matrix types. Ordinary matrices and several sparse/dense Matrix classes are directly supported, along with a subset of the delayed operations implemented in the DelayedArray package. All other matrix-like objects are supported by calling back into R.

Save Bioconductor data structures into file artifacts, and load them back into memory. This is a more robust and portable alternative to serialization of such objects into RDS files. Each artifact is associated with metadata for further interpretation; downstream applications can enrich this metadata with context-specific properties.

A comprehensive package for visualizing multi-set intersections and extracting detailed subset information. VennDetail generates high-resolution visualizations including traditional Venn diagrams, Venn-pie plots, and UpSet-style plots. It provides functions to extract and combine subset details with user datasets in various formats. The package is particularly useful for bioinformatics applications but can be used for any multi-set analysis.

Analyze and visualize Mutation Annotation Format (MAF) files from large scale sequencing studies. This package provides various functions to perform most commonly used analyses in cancer genomics and to create feature rich customizable visualzations with minimal effort.

Defines a S4 class that is based on SingleCellExperiment. In addition to the usual gene layer the object can also store data for immune genes such as HLAs, Igs and KIRs at allele and functional level. The package is part of a workflow named single-cell ImmunoGenomic Diversity (scIGD), that firstly incorporates allele-aware quantification data for immune genes. This new data can then be used with the here implemented data structure and functionalities for further data handling and data analysis.

Read in imaging-based spatial transcriptomics technology data. Current available modules are for Xenium by 10X Genomics, CosMx by Nanostring, MERSCOPE by Vizgen, or STARmapPLUS from Broad Institute. You can choose to read the data in as a SpatialExperiment or a SingleCellExperiment object.

Defines an S4 class for storing data from spatial -omics experiments. The class extends SingleCellExperiment to support storage and retrieval of additional information from spot-based and molecule-based platforms, including spatial coordinates, images, and image metadata. A specialized constructor function is included for data from the 10x Genomics Visium platform.

Implements bindings for SQL tables that are compatible with Bioconductor S4 data structures, namely the DataFrame and DelayedArray. This allows SQL-derived data to be easily used inside other Bioconductor objects (e.g., SummarizedExperiments) while keeping everything on disk.

Implements a DelayedArray of random values where the realization of the sampled values is delayed until they are needed. Reproducible sampling within any subarray is achieved by chunking where each chunk is initialized with a different random seed and stream. The usual distributions in the stats package are supported, along with scalar, vector and arrays for the parameters.

Parses BioPAX files and represents them in R, at the moment BioPAX level 2 and level 3 are supported.

GA4GHclient provides an easy way to access public data servers through Global Alliance for Genomics and Health (GA4GH) genomics API. It provides low-level access to GA4GH API and translates response data into Bioconductor-based class objects.