Package Recipe 'purge_dups'

recipe purge_dups

purge_dups is a package used to purge haplotigs and overlaps in an assembly based on read depth.

Homepage:: https://github.com/dfguan/purge_dups
Documentation:: https://github.com/dfguan/purge_dups/blob/v{[ version }}/README.md
License:: MIT / MIT
Recipe:: /purge_dups/meta.yaml
Links:: biotools: purge_dups, usegalaxy-eu: purge_dups, doi: 10.1093/bioinformatics/btaa025

package purge_dups¶

Versions:

1.2.6-3, 1.2.6-2, 1.2.6-1, 1.2.6-0, 1.2.5-2, 1.2.5-1, 1.2.5-0, 1.0.1-0

Depends:

on libgcc >=13
on libzlib >=1.3.1,<2.0a0
on matplotlib-base
on minimap2
on purge-dups-runner
on python >=3

Additional platforms:

linux-aarch64, osx-arm64

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 purge_dups

to add into an existing workspace instead, run:

pixi add purge_dups

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 purge_dups

Alternatively, to install into a new environment, run:

conda create -n envname purge_dups

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/purge_dups:<tag>

(see purge_dups/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/purge_dups/README.html)