Package Recipe 'bioconductor-hdf5array'

recipe bioconductor-hdf5array

HDF5 datasets as array-like objects in R

Homepage:: https://bioconductor.org/packages/3.20/bioc/html/HDF5Array.html
License:: Artistic-2.0
Recipe:: /bioconductor-hdf5array/meta.yaml
Links:: biotools: hdf5array, doi: 10.1038/nmeth.3252

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.

package bioconductor-hdf5array¶

Versions:

1.38.0-0, 1.34.0-1, 1.34.0-0, 1.30.0-1, 1.30.0-0, 1.28.1-0, 1.26.0-2, 1.26.0-1, 1.22.1-1,

1.38.0-0, 1.34.0-1, 1.34.0-0, 1.30.0-1, 1.30.0-0, 1.28.1-0, 1.26.0-2, 1.26.0-1, 1.22.1-1, 1.22.1-0, 1.22.0-1, 1.20.0-1, 1.20.0-0, 1.18.1-0, 1.18.0-0, 1.16.0-0, 1.14.0-0, 1.12.1-0, 1.10.1-0, 1.8.1-0, 1.6.0-0

Depends:

on bioconductor-biocgenerics >=0.56.0,<0.57.0
on bioconductor-delayedarray >=0.36.0,<0.37.0
on bioconductor-h5mread >=1.2.0,<1.3.0
on bioconductor-iranges >=2.44.0,<2.45.0
on bioconductor-rhdf5 >=2.54.0,<2.55.0
on bioconductor-s4arrays >=1.10.0,<1.11.0
on bioconductor-s4vectors >=0.48.0,<0.49.0
on bioconductor-sparsearray >=1.10.0,<1.11.0
on r-base >=4.5,<4.6.0a0
on r-matrix

Additional platforms:

linux-aarch64, osx-arm64

Installation¶

You need a conda-compatible package manager (currently either pixi, conda, or micromamba) and the Bioconda channel already activated (see Usage). Below, we show how to install with either pixi or conda (for micromamba and mamba, commands are essentially the same as with conda).

Pixi¶

With pixi installed and the Bioconda channel set up (see Usage), to install globally, run:

pixi global install bioconductor-hdf5array

to add into an existing workspace instead, run:

pixi add bioconductor-hdf5array

In the latter case, make sure to first add bioconda and conda-forge to the channels considered by the workspace:

pixi workspace channel add conda-forge
pixi workspace channel add bioconda

Conda¶

With conda installed and the Bioconda channel set up (see Usage), to install into an existing and activated environment, run:

conda install bioconductor-hdf5array

Alternatively, to install into a new environment, run:

conda create -n envname bioconductor-hdf5array

with envname being the name of the desired environment.

Container¶

Alternatively, every Bioconda package is available as a container image for usage with your preferred container runtime. For e.g. docker, run:

docker pull quay.io/biocontainers/bioconductor-hdf5array:<tag>

(see bioconductor-hdf5array/tags for valid values for <tag>).

Integrated deployment¶

Finally, note that many scientific workflow management systems directly integrate both conda and container based software deployment. Thus, workflow steps can be often directly annotated to use the package, leading to automatic deployment by the respective workflow management system, thereby improving reproducibility and transparency. Check the documentation of your workflow management system to find out about the integration.

Download stats¶

Link to this page¶

Render an badge with the following MarkDown:

[![install with bioconda](https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg?style=flat)](http://bioconda.github.io/recipes/bioconductor-hdf5array/README.html)