GenomicCoordinates

Infrastructure

Extends string parsing capabilities for genomic coordinates, supporting various formats including comma-separated numbers, space-delimited coordinates, and automatic detection of GRanges, GPos, and GInteractions objects.

Source attribution

Related resources

The HDF5Array package is an HDF5 backend for DelayedArray objects. It implements the HDF5Array, H5SparseMatrix, H5ADMatrix, and TENxMatrix classes, 4 convenient and memory-efficient array-like containers for representing and manipulating either: (1) a conventional (a.k.a. dense) HDF5 dataset, (2) an HDF5 sparse matrix (stored in CSR/CSC/Yale format), (3) the central matrix of an h5ad file (or any matrix in the /layers group), or (4) a 10x Genomics sparse matrix. All these containers are DelayedArray extensions and thus support all operations (delayed or block-processed) supported by DelayedArray objects.

The Seqinfo class stores the names, lengths, circularity flags, and genomes for a particular collection of sequences. These sequences are typically the chromosomes and/or scaffolds of a specific genome assembly of a given organism. Seqinfo objects are rarely used as standalone objects. Instead, they are used as part of higher-level objects to represent their seqinfo() component. Examples of such higher-level objects are GRanges, RangedSummarizedExperiment, VCF, GAlignments, etc... defined in other Bioconductor infrastructure packages.

A set of tools to forge BSgenome data packages. Supersedes the old seed-based tools from the BSgenome software package. This package allows the user to create a BSgenome data package in one function call, simplifying the old seed-based process.

VariantExperiment is a Bioconductor package for saving data in VCF/GDS format into RangedSummarizedExperiment object. The high-throughput genetic/genomic data are saved in GDSArray objects. The annotation data for features/samples are saved in DelayedDataFrame format with mono-dimensional GDSArray in each column. The on-disk representation of both assay data and annotation data achieves on-disk reading and processing and saves memory space significantly. The interface of RangedSummarizedExperiment data format enables easy and common manipulations for high-throughput genetic/genomic data with common SummarizedExperiment metaphor in R and Bioconductor.

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, ordinary arrays and, data frames.

The ability to efficiently represent and manipulate genomic annotations and alignments is playing a central role when it comes to analyzing high-throughput sequencing data (a.k.a. NGS data). The GenomicRanges package defines general purpose containers for storing and manipulating genomic intervals and variables defined along a genome. More specialized containers for representing and manipulating short alignments against a reference genome, or a matrix-like summarization of an experiment, are defined in the GenomicAlignments and SummarizedExperiment packages, respectively. Both packages build on top of the GenomicRanges infrastructure.