Package Recipe 'bioconductor-cardelino'

recipe bioconductor-cardelino

Clone Identification from Single Cell Data

Homepage:: https://bioconductor.org/packages/3.20/bioc/html/cardelino.html
License:: GPL-3
Recipe:: /bioconductor-cardelino/meta.yaml

Methods to infer clonal tree configuration for a population of cells using single-cell RNA-seq data (scRNA-seq), and possibly other data modalities. Methods are also provided to assign cells to inferred clones and explore differences in gene expression between clones. These methods can flexibly integrate information from imperfect clonal trees inferred based on bulk exome-seq data, and sparse variant alleles expressed in scRNA-seq data. A flexible beta-binomial error model that accounts for stochastic dropout events as well as systematic allelic imbalance is used.

package bioconductor-cardelino¶

Versions:

1.12.0-0, 1.8.0-0, 1.4.0-0, 1.2.0-0, 1.0.0-0

Depends:

on bioconductor-genomeinfodb >=1.46.0,<1.47.0
on bioconductor-genomicranges >=1.62.0,<1.63.0
on bioconductor-ggtree >=4.0.0,<4.1.0
on bioconductor-s4vectors >=0.48.0,<0.49.0
on bioconductor-snpstats >=1.60.0,<1.61.0
on bioconductor-variantannotation >=1.56.0,<1.57.0
on r-base >=4.5,<4.6.0a0
on r-combinat
on r-ggplot2
on r-matrix
on r-matrixstats
on r-pheatmap
on r-vcfr

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-cardelino

to add into an existing workspace instead, run:

pixi add bioconductor-cardelino

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-cardelino

Alternatively, to install into a new environment, run:

conda create -n envname bioconductor-cardelino

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-cardelino:<tag>

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