Metadata-Version: 2.1
Name: pysoar
Version: 1.0.1
Summary: A data analysis tool for translocations in nanopores
Home-page: https://github.com/VladimirIvanovImperial/PySOAR.git
Author: Vladimir Ivanov
Author-email: vi4018@ic.ac.uk
License: MIT
Keywords: nanopore sensing,single molecule detection,signal processing,data analysis
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering :: Chemistry
Classifier: Topic :: Scientific/Engineering :: Physics
Classifier: Topic :: Scientific/Engineering
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
License-File: LICENSE.txt

# PySOAR

PySOAR is a Python (3.9+) package for data analysis of translocation events during nanopore sensing. The main features include:
* Baseline correction function.
* Splitting the current into bins and doing a Poisson fit on that data to help the user visually decide on what threshold should be used for this data.
* Finding peaks function based on the threshold chosen.
* Ability to extract features from the events using both CUSUM and ADEPT methods.
* Histogram plots of peak curretn and dwell time data.

# Installation

To install with pip:
'''

pip install --user pysoar

'''

PySOAR utilises the following external libraries:
* [NumPy](https://numpy.org/)
* [SciPy]((https://scipy.org/))
* [ruptures](https://centre-borelli.github.io/ruptures-docs/)
* [matplotlib](https://matplotlib.org/)

# Acknowledgements
Developed by Vladimir Ivanov as part of the MSci final year project while working with the Edel's group at Imperial College London

