Package Recipe 'yleaf-pipelines'

recipe yleaf-pipelines

Yleaf-pipelines - A pipeline-optimized version of Yleaf, a tool for Y-chromosome haplogroup prediction.

Homepage:: https://github.com/trianglegrrl/Yleaf-pipelines
License:: MIT / MIT
Recipe:: /yleaf-pipelines/meta.yaml
Links:: doi: 10.1093/molbev/msy032

Yleaf-pipelines is a pipeline-optimized version of Yleaf, a tool for Y-chromosome haplogroup prediction from next-generation sequencing data. It provides a comprehensive solution for analyzing Y-chromosome genetic data and determining haplogroup assignments.

package yleaf-pipelines¶

Versions:

3.3.0-0

Depends:

on graphviz >=2.40
on networkx >=2.6
on numpy
on pandas >=1.3
on pip
on python
on python-dateutil >=2.8
on pytz >=2021
on six >=1.16

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 yleaf-pipelines

to add into an existing workspace instead, run:

pixi add yleaf-pipelines

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 yleaf-pipelines

Alternatively, to install into a new environment, run:

conda create -n envname yleaf-pipelines

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/yleaf-pipelines:<tag>

(see yleaf-pipelines/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.

Notes¶

Yleaf requires reference genome files for analysis. These will be downloaded automatically when needed, or you can specify their location in the config.txt file. Basic usage:

Yleaf -fastq input.fastq -rg hg38 -o output_dir -fg /path/to/full-genome.fa -yr /path/to/ychr.fa"

For more information, see the documentation at:: https://github.com/trianglegrrl/Yleaf-pipelines

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/yleaf-pipelines/README.html)