recipe bioconductor-speckle

Statistical methods for analysing single cell RNA-seq data

Homepage:

https://bioconductor.org/packages/3.18/bioc/html/speckle.html

License:

GPL-3

Recipe:

/bioconductor-speckle/meta.yaml

The speckle package contains functions for the analysis of single cell RNA-seq data. The speckle package currently contains functions to analyse differences in cell type proportions. There are also functions to estimate the parameters of the Beta distribution based on a given counts matrix, and a function to normalise a counts matrix to the median library size. There are plotting functions to visualise cell type proportions and the mean-variance relationship in cell type proportions and counts. As our research into specialised analyses of single cell data continues we anticipate that the package will be updated with new functions.

package bioconductor-speckle

(downloads) docker_bioconductor-speckle

versions:

1.2.0-0,  1.0.0-0

depends bioconductor-edger:

>=4.0.0,<4.1.0

depends bioconductor-limma:

>=3.58.0,<3.59.0

depends bioconductor-singlecellexperiment:

>=1.24.0,<1.25.0

depends r-base:

>=4.3,<4.4.0a0

depends r-ggplot2:

depends r-seurat:

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-speckle

and update with::

   mamba update bioconductor-speckle

To create a new environment, run:

mamba create --name myenvname bioconductor-speckle

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-speckle:<tag>

(see `bioconductor-speckle/tags`_ for valid values for ``<tag>``)

Download stats

Link to this page

Render an install-with-bioconda 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-speckle/README.html)