Package Recipe 'pyeasyfuse'

recipe pyeasyfuse

EasyFuse is a pipeline to detect fusion transcripts from RNA-seq data with high accuracy. The current version of EasyFuse uses two fusion gene detection tools, STAR-Fusion and Fusioncatcher along with a powerful read filtering strategy, stringent re-quantification of supporting reads and machine learning for highly accurate predictions.

Homepage:: https://github.com/TRON-bioinformatics/easyfuse-src
Documentation:: https://github.com/TRON-Bioinformatics/EasyFuse
Developer docs:: https://pypi.org/project/pyeasyfuse/
License:: GPL / GPL-3.0-only
Recipe:: /pyeasyfuse/meta.yaml
Links:: doi: 10.1038/s41587-022-01247-9

package pyeasyfuse¶

Versions:

2.0.3-0

Depends:

on biopython 1.73.*
on bx-python 0.8.*
on gffutils 0.10.*
on importlib-metadata
on logzero 1.7.*
on numpy 1.21.*
on pandas >=1.0.0
on pysam >=0.15.3
on python >=3.7,<3.8
on python-xxhash 1.4.*
on pytz 2022.7.*
on r-base >=4.2,<4.3.0a0
on r-dplyr
on r-optparse
on r-randomforest
on r-readr
on r-stringr
on r-tidyr
on r-tidyselect
on r-xml

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 pyeasyfuse

to add into an existing workspace instead, run:

pixi add pyeasyfuse

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 pyeasyfuse

Alternatively, to install into a new environment, run:

conda create -n envname pyeasyfuse

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/pyeasyfuse:<tag>

(see pyeasyfuse/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/pyeasyfuse/README.html)