Package Recipe 'bioflowkit' — Bioconda documentation

recipe bioflowkit

One-line comparative-genomics recipes + Tier-A SDK over per-tool Docker BioContainers

Homepage:: hope9901/bioflow
Documentation:: https://hope9901.github.io/bioflow/
License:: MIT / MIT
Recipe:: /bioflowkit/meta.yaml

bioflow is a bioinformatics SDK + cookbook for one-line comparative-genomics analyses on a single workstation. Each tool runs in its own Docker BioContainer (no native installs), each recipe is one CLI call, and an optional privacy-first LLM companion is available.

Requires a reachable Docker daemon at run time — bioflow launches each pipeline stage as a sibling container via the host Docker socket. Run `bioflow doctor` after install to verify the host.

The PyPI/conda distribution name is `bioflowkit`; the Python import name and CLI command are both `bioflow`.

package bioflowkit#

Versions:

0.3.1-0

Depends:

on docker-py >=7.1
on jsonschema >=4.22
on matplotlib-base >=3.6
on pandas >=1.5
on psutil >=5.9
on pydantic >=2.7
on pynvml >=11.5
on python >=3.9
on pyyaml >=6.0
on questionary >=2.0
on rich >=13.7
on typer >=0.12

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 bioflowkit

to add into an existing workspace instead, run:

pixi add bioflowkit

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 bioflowkit

Alternatively, to install into a new environment, run:

conda create -n envname bioflowkit

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/bioflowkit:<tag>

(see bioflowkit/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

.. Create all the necessary plots for each package by loading all the correct specs and data. Important points on the place and implementation of this script block: 1. It is here, and not in a separate HTML file, as it needs to have the `package.name` rendered in for each package. 2. All packages are handled in one `window.onload` function, as multiple instances of this throughout a (rendered) HTML just overwrite each other.

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/bioflowkit/README.html)