- 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:
- Documentation:
- Developer docs:
- License:
GPL / GPL-3.0-only
- Recipe:
- Links:
- package pyeasyfuse¶
- versions:
2.0.3-0
- depends biopython:
1.73.*
- depends bx-python:
0.8.*
- depends gffutils:
0.10.*
- depends importlib-metadata:
- depends logzero:
1.7.*
- depends numpy:
1.21.*
- depends pandas:
>=1.0.0
- depends pysam:
>=0.15.3
- depends python:
>=3.7,<3.8
- depends python-xxhash:
1.4.*
- depends pytz:
2022.7.*
- depends r-base:
>=4.2,<4.3.0a0
- depends r-dplyr:
- depends r-optparse:
- depends r-randomforest:
- depends r-readr:
- depends r-stringr:
- depends r-tidyr:
- depends r-tidyselect:
- depends r-xml:
- requirements:
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 pyeasyfuse and update with:: mamba update pyeasyfuse
To create a new environment, run:
mamba create --name myenvname pyeasyfuse
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/pyeasyfuse:<tag> (see `pyeasyfuse/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/pyeasyfuse/README.html)