Metadata-Version: 2.1
Name: pyInfinityFlow
Version: 0.1
Summary: Impute Flow Cytometry values between overlapping panels with XGBoost regression.
Home-page: http://github.com/
Author: Kyle Ferchen
Author-email: Kyle Ferchen <ferchenkyle@gmail.com>
License: MIT
Project-URL: Homepage, https://github.com/
Project-URL: Bug Tracker, https://github.com/
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE

# pyInfinityFlow

**pyInfinityFlow** is a Python package that enables imputation of hundreds of features from Flow Cytometry using XGBoost regression. It is an adaptation of the [original implementation in R](https://github.com/ebecht/infinityFlow) [<sup>1</sup>](https://www.science.org/doi/full/10.1126/sciadv.abg0505) with the goal of optimizing the workflow for large datasets by increasing the speed and memory efficiency of the analysis pipeline. 

The package includes tools to read and write FCS files, following the FCS3.1 file standard

Downstream analyses


## Graphical Summary
![graphical summary of pyinfinityflow workflow](images/graphical_summary.png "Graphical Summary")

## Recommended Installation

## Quickstart

```console

```

## Selected References
[<font size="2"><sup>1</sup> Becht, E., Tolstrup, D., Dutertre, C. A., Morawski, P. A., Campbell, D. J., Ginhoux, F., ... & Headley, M. B. (2021). High-throughput single-cell quantification of hundreds of proteins using conventional flow cytometry and machine learning. Science advances, 7(39), eabg0505. </font>](https://www.science.org/doi/full/10.1126/sciadv.abg0505)
