recipe bioconductor-cellbarcode

Cellular DNA Barcode Analysis toolkit

Homepage:

https://bioconductor.org/packages/3.20/bioc/html/CellBarcode.html

License:

Artistic-2.0

Recipe:

/bioconductor-cellbarcode/meta.yaml

The package CellBarcode performs Cellular DNA Barcode analysis. It can handle all kinds of DNA barcodes, as long as the barcode is within a single sequencing read and has a pattern that can be matched by a regular expression. \code{CellBarcode} can handle barcodes with flexible lengths, with or without UMI (unique molecular identifier). This tool also can be used for pre-processing some amplicon data such as CRISPR gRNA screening, immune repertoire sequencing, and metagenome data.

package bioconductor-cellbarcode

versions:

1.12.0-0,  1.8.0-0,  1.6.0-0,  1.4.0-1,  1.4.0-0,  1.0.0-2,  1.0.0-1,  1.0.0-0

depends bioconductor-biostrings:

>=2.74.0,<2.75.0

depends bioconductor-biostrings:

>=2.74.0,<2.75.0a0

depends bioconductor-rsamtools:

>=2.22.0,<2.23.0

depends bioconductor-rsamtools:

>=2.22.0,<2.23.0a0

depends bioconductor-s4vectors:

>=0.44.0,<0.45.0

depends bioconductor-s4vectors:

>=0.44.0,<0.45.0a0

depends bioconductor-shortread:

>=1.64.0,<1.65.0

depends bioconductor-shortread:

>=1.64.0,<1.65.0a0

depends bioconductor-zlibbioc:

>=1.52.0,<1.53.0

depends bioconductor-zlibbioc:

>=1.52.0,<1.53.0a0

depends libblas:

>=3.9.0,<4.0a0

depends libgcc:

>=13

depends liblapack:

>=3.9.0,<4.0a0

depends libstdcxx:

>=13

depends libzlib:

>=1.3.1,<2.0a0

depends r-base:

>=4.4,<4.5.0a0

depends r-bh:

depends r-ckmeans.1d.dp:

depends r-data.table:

>=1.12.6

depends r-egg:

depends r-ggplot2:

depends r-magrittr:

depends r-plyr:

depends r-rcpp:

>=1.0.5

depends r-seqinr:

depends r-stringr:

requirements:

additional platforms:

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-cellbarcode

and update with::

   mamba update bioconductor-cellbarcode

To create a new environment, run:

mamba create --name myenvname bioconductor-cellbarcode

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-cellbarcode:<tag>

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

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-cellbarcode/README.html)