Package Recipe 'pegas'

recipe pegas

PeGAS is a Snakemake pipeline for genome analysis (with a lightweight CLI option)

Homepage:: https://github.com/liviurotiul/PeGAS
Documentation:: https://github.com/liviurotiul/PeGAS#readme
Developer docs:: https://github.com/liviurotiul/PeGAS/issues
License:: GPL / GPL-2.0-or-later
Recipe:: /pegas/meta.yaml

PeGAS is a Snakemake pipeline for genome analysis. It is designed to be lightweight, easy to install, and easy to use. A separate lite entrypoint is provided for running the pipeline without Snakemake.

package pegas¶

Versions:

1.2.4-0, 1.2.3-0, 1.2.1-0, 1.1.0-0, 1.0.9-0, 1.0.8-0, 1.0.7-0, 1.0.6-0, 1.0.5-0,

1.2.4-0, 1.2.3-0, 1.2.1-0, 1.1.0-0, 1.0.9-0, 1.0.8-0, 1.0.7-0, 1.0.6-0, 1.0.5-0, 1.0.4-0, 1.0.3-0, 1.0.2-0, 1.0.1-0, 0.2.13-0

Depends:

on pegas-snakemake 1.2.4.*

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 pegas

to add into an existing workspace instead, run:

pixi add pegas

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 pegas

Alternatively, to install into a new environment, run:

conda create -n envname pegas

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/pegas:<tag>

(see pegas/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.

package pegas-lite¶

Versions:

1.2.4-0, 1.2.3-0, 1.2.1-0

Depends:

on beautifulsoup4 >=4.12.3
on conda >=24.7.1
on jinja2 >=3.0
on matplotlib-base >=3.9.2
on networkx >=3.2
on numpy
on pandas >=1.3.5
on plotly >=5.0.0,<6
on python >=3.10
on tqdm >=4.66.5

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 pegas-lite

to add into an existing workspace instead, run:

pixi add pegas-lite

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 pegas-lite

Alternatively, to install into a new environment, run:

conda create -n envname pegas-lite

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/pegas-lite:<tag>

(see pegas-lite/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.

package pegas-snakemake¶

Versions:

1.2.4-0

Depends:

on pegas-lite 1.2.4.*
on python
on snakemake-minimal >=7.32.4

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 pegas-snakemake

to add into an existing workspace instead, run:

pixi add pegas-snakemake

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 pegas-snakemake

Alternatively, to install into a new environment, run:

conda create -n envname pegas-snakemake

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/pegas-snakemake:<tag>

(see pegas-snakemake/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/pegas/README.html)