alabaster.bumpy

DataImport
R
MIT + file LICENSE

Save BumpyMatrix objects into file artifacts, and load them back into memory. This is a more 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.

Source attribution

  • Bioconductoralabaster.bumpy

Related resources

Uses platform-specific implemenations of the GatingML2.0 standard to exchange gated cytometry data with other software platforms.

353 months ago
HTML
AGPL-3.0

This package is designed to facilitate the automated gating methods in sequential way to mimic the manual gating strategy.

Representing nucleotide modifications in a nucleotide sequence is usually done via special characters from a number of sources. This represents a challenge to work with in R and the Biostrings package. The Modstrings package implements this functionallity for RNA and DNA sequences containing modified nucleotides by translating the character internally in order to work with the infrastructure of the Biostrings package. For this the ModRNAString and ModDNAString classes and derivates and functions to construct and modify these objects despite the encoding issues are implemenented. In addition the conversion from sequences to list like location information (and the reverse operation) is implemented as well.

The LoomExperiment package provide a means to easily convert the Bioconductor "Experiment" classes to loom files and vice versa.

A package for RNA basepair analysis, including the visualization of basepairs as arc diagrams for easy comparison and annotation of sequence and structure. Arc diagrams can additionally be projected onto multiple sequence alignments to assess basepair conservation and covariation, with numerical methods for computing statistics for each.

Toolbox for larger-than-memory scientific computing and visualization, providing efficient out-of-core data structures using files or shared memory, for dense and sparse vectors, matrices, and arrays, with applications to nonuniformly sampled signals and images.