- recipe deepchopper
A Genomic Language Model for Chimera Artifact Detection in Nanopore Direct RNA Sequencing.
- Homepage:
- License:
Apache / Apache-2.0
- Recipe:
DeepChopper is a genomic language model designed to identify artificial sequences. It provides functionality for encoding FASTQ files, making predictions, and chopping sequences.
- package deepchopper¶
-
- Versions:
1.2.9-1,1.2.9-0,1.2.6-1,1.2.6-0,1.2.5-1,1.2.5-0,1.2.4-0- Depends:
on datasets
2.14.2on deepchopper-cli
>=1.2.5on evaluate
>=0.4.1on fastapi
0.112.2on gradio
5.0.1on hydra-core
>=1.3.2on libgcc
>=14on lightning
>=2.1.2on omegaconf
>=2.3.0on pyarrow
20.0.0on python
>=3.10,<3.11.0a0on python-multipart
0.0.12on python_abi
3.10.* *_cp310on pytorch
>=2.1.0on rich
>=13.7.0on safetensors
>=0.4.2on scikit-learn
>=1.5.2on torchmetrics
>=1.2.0on transformers
>=4.37.2on typer
>=0.12.0
- 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 deepchopper
to add into an existing workspace instead, run:
pixi add deepchopper
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 deepchopper
Alternatively, to install into a new environment, run:
conda create -n envname deepchopper
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/deepchopper:<tag>
(see deepchopper/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:
[](http://bioconda.github.io/recipes/deepchopper/README.html)