Metadata-Version: 2.4
Name: pyfauxseq
Version: 0.1.0
Summary: This package can generate synthetic timeseries RNA-seq data with a fraction of rhythmic genes and empirical relationship between mean expression and variability across replicates of genes.
Project-URL: bugs, https://github.com/bharathananth/pyfauxseq/issues
Project-URL: homepage, https://github.com/bharathananth/pyfauxseq
Project-URL: documentation, https://bharathananth.github.io/pypfauxseq
Author-email: Bharath Ananthasubramaniam <bharath.ananthasubramaniam@hu-berlin.de>
Maintainer-email: Bharath Ananthasubramaniam <bharath.ananthasubramaniam@hu-berlin.de>
License-Expression: MIT
License-File: LICENSE
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Healthcare Industry
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Requires-Python: >=3.10
Requires-Dist: numpy
Requires-Dist: pandas
Requires-Dist: scipy
Provides-Extra: docs
Requires-Dist: mkdocs; extra == 'docs'
Requires-Dist: mkdocs-material; extra == 'docs'
Requires-Dist: mkdocstrings-python; extra == 'docs'
Provides-Extra: test
Requires-Dist: coverage; extra == 'test'
Requires-Dist: hypothesis; extra == 'test'
Requires-Dist: pytest; extra == 'test'
Requires-Dist: ruff; extra == 'test'
Requires-Dist: ty; extra == 'test'
Description-Content-Type: text/markdown

# pyfauxseq
### A python Implementation of the R package fauxseq

![PyPI - Version](https://img.shields.io/pypi/v/pyfauxseq)
![PyPI - Downloads](https://img.shields.io/pypi/dm/pyfauxseq)
![GitHub Downloads (all assets, all releases)](https://img.shields.io/github/downloads/bharathananth/pyfauxseq/total)

## What pyfauxseq does

This package can generate synthetic timeseries RNA-seq data with a fraction of rhythmic genes and empirical relationship between mean expression and variability across replicates of genes.

`pyfauxseq` improves upon previous tools as follows:
- generates negative-binomial count data with empirically-estimated mean-dispersion properties.
- generates data with either differential expression or differential rhythmicity or both.

## How to install pyfauxseq
```python -m pip install pyfauxseq```

## Get started with pyfauxseq
Get started with synthetic RNA-seq data with the ground truth with the default parameters using
```python
import pyfauxseq as pf
sim_data = pf.generate_rhythmic_rnaseq()
sim_data["counts"] # the count data
sim_data["params"] # parameters of the rhythmic genes
sim_data["exp_design"] # time labels of the individual sample (columns) of count data
```
## How to cite pyfauxseq
Please cite this software using CITATION.CFF or the "Cite this repository" link in the right sidebar.

## Credits

This package was created with [Cookiecutter](https://github.com/audreyfeldroy/cookiecutter) and the [audreyfeldroy/cookiecutter-pypackage](https://github.com/audreyfeldroy/cookiecutter-pypackage) project template.
