recipe bioconductor-scarray.sat

Large-scale single-cell RNA-seq data analysis using GDS files and Seurat

Homepage:

https://bioconductor.org/packages/3.18/bioc/html/SCArray.sat.html

License:

GPL-3

Recipe:

/bioconductor-scarray.sat/meta.yaml

Extends the Seurat classes and functions to support Genomic Data Structure (GDS) files as a DelayedArray backend for data representation. It relies on the implementation of GDS-based DelayedMatrix in the SCArray package to represent single cell RNA-seq data. The common optimized algorithms leveraging GDS-based and single cell-specific DelayedMatrix (SC_GDSMatrix) are implemented in the SCArray package. SCArray.sat introduces a new SCArrayAssay class (derived from the Seurat Assay), which wraps raw counts, normalized expressions and scaled data matrix based on GDS-specific DelayedMatrix. It is designed to integrate seamlessly with the Seurat package to provide common data analysis in the SeuratObject-based workflow. Compared with Seurat, SCArray.sat significantly reduces the memory usage without downsampling and can be applied to very large datasets.

package bioconductor-scarray.sat

versions:

1.2.0-0,  1.0.2-0

depends bioconductor-biocgenerics:

>=0.48.0,<0.49.0

depends bioconductor-biocparallel:

>=1.36.0,<1.37.0

depends bioconductor-biocsingular:

>=1.18.0,<1.19.0

depends bioconductor-delayedarray:

>=0.28.0,<0.29.0

depends bioconductor-gdsfmt:

>=1.38.0,<1.39.0

depends bioconductor-s4vectors:

>=0.40.0,<0.41.0

depends bioconductor-scarray:

>=1.10.0,<1.11.0

depends bioconductor-summarizedexperiment:

>=1.32.0,<1.33.0

depends r-base:

>=4.3,<4.4.0a0

depends r-seurat:

>=4.0

depends r-seuratobject:

>=4.0

requirements:

Installation

You need a conda-compatible package manager (currently either micromamba, mamba, or conda) and the Bioconda channel already activated (see set-up-channels).

While any of above package managers is fine, it is currently recommended to use either micromamba or mamba (see here for installation instructions). We will show all commands using mamba below, but the arguments are the same for the two others.

Given that you already have a conda environment in which you want to have this package, install with:

   mamba install bioconductor-scarray.sat

and update with::

   mamba update bioconductor-scarray.sat

To create a new environment, run:

mamba create --name myenvname bioconductor-scarray.sat

with myenvname being a reasonable name for the environment (see e.g. the mamba docs for details and further options).

Alternatively, use the docker container:

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

(see `bioconductor-scarray.sat/tags`_ for valid values for ``<tag>``)

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