recipe polars-bio

Blazing fast genomic operations on large Python dataframes

Homepage:

biodatageeks/polars-bio

Documentation:

https://biodatageeks.org/polars-bio/

License:

Apache / Apache-2.0

Recipe:

/polars-bio/meta.yaml

Links:

doi: 10.1093/bioinformatics/btaf640

polars-bio is a Python library for genomics built on top of Polars, Apache Arrow and Apache DataFusion. It provides a DataFrame API for genomics data and is designed to be fast, memory efficient and easy to use.

Key features:

- Popular genomic interval operations with a DataFrame API - SQL-powered querying of bioinformatics data - Native parallel engine powered by Apache DataFusion - Out-of-core / streaming processing - Reading from cloud storage - Zero-copy data exchange with Apache Arrow - Support for VCF, BAM, CRAM, SAM, FASTQ, FASTA, BED, GFF, GTF and

BigWig/BigBed

package polars-bio#

(downloads) docker_polars-bio

Versions:

0.34.0-0,  0.33.1-0

Depends:

  • on __osx >=11.0

  • on datafusion >=53.0.0,<54

  • on libcxx >=19

  • on polars >=1.37.1

  • on polars-config-meta >=0.3.0,<1

  • on pyarrow >=23.0.1,<25

  • on python >=3.11,<3.12.0a0

  • on python_abi 3.11.* *_cp311

  • on tqdm >=4.67.0,<5

Additional platforms:
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 polars-bio

to add into an existing workspace instead, run:

pixi add polars-bio

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 polars-bio

Alternatively, to install into a new environment, run:

conda create -n envname polars-bio

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/polars-bio:<tag>

(see polars-bio/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 install-with-bioconda 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/polars-bio/README.html)