Package Recipe 'bioconductor-rcsl'

recipe bioconductor-rcsl

Rank Constrained Similarity Learning for single cell RNA sequencing data

Homepage:: https://bioconductor.org/packages/3.20/bioc/html/RCSL.html
License:: Artistic-2.0
Recipe:: /bioconductor-rcsl/meta.yaml

A novel clustering algorithm and toolkit RCSL (Rank Constrained Similarity Learning) to accurately identify various cell types using scRNA-seq data from a complex tissue. RCSL considers both lo-cal similarity and global similarity among the cells to discern the subtle differences among cells of the same type as well as larger differences among cells of different types. RCSL uses Spearman’s rank correlations of a cell’s expression vector with those of other cells to measure its global similar-ity, and adaptively learns neighbour representation of a cell as its local similarity. The overall similar-ity of a cell to other cells is a linear combination of its global similarity and local similarity.

package bioconductor-rcsl¶

Versions:

1.18.0-0, 1.14.0-0, 1.8.0-0, 1.6.0-0, 1.2.0-0, 1.0.0-0

Depends:

on bioconductor-matrixgenerics >=1.22.0,<1.23.0
on bioconductor-matrixgenerics >=1.22.0,<1.23.0a0
on bioconductor-singlecellexperiment >=1.32.0,<1.33.0
on bioconductor-singlecellexperiment >=1.32.0,<1.33.0a0
on libblas >=3.9.0,<4.0a0
on libgcc >=14
on liblapack >=3.9.0,<4.0a0
on liblzma >=5.8.2,<6.0a0
on libstdcxx >=14
on libzlib >=1.3.1,<2.0a0
on r-base >=4.5,<4.6.0a0
on r-ggplot2 >=3.4.0
on r-igraph
on r-nbclust
on r-pracma
on r-rcpp >=0.11.0
on r-rcppannoy
on r-rtsne
on r-umap

Additional platforms:

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-rcsl

to add into an existing workspace instead, run:

pixi add bioconductor-rcsl

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-rcsl

Alternatively, to install into a new environment, run:

conda create -n envname bioconductor-rcsl

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-rcsl:<tag>

(see bioconductor-rcsl/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-rcsl/README.html)