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A comprehensive package for solid state nanopore data analysis and visualization.

Project description

Nanosense

Nanosense is a powerful and comprehensive Python package designed for analyzing and visualizing nanopore data. It provides a suite of 12 applications that offer a wide range of tools and functionalities to facilitate the exploration, processing, and interpretation of nanopore measurements.

Features

  • Plotting and Selecting: Plot .abf and .hdf5 files, apply low-pass filters, and select specific parts of the file based on various conditions.
  • Data Reduction: Reduce nanopore data, perform event fitting, standardization, and ML-based data reduction using parallel processing.
  • Data Visualisation: Plot data files, perform PCA analysis, generate correlation matrices, and create density plots.
  • Frequency and multi-plots: Plot data from different files, calculate the frequency of events per second, and filter data using various filters.
  • Event Analysis: Analyze individual events in nanopore data and extract meaningful information.
  • Combine Datasets and files: Merge datasets from data reduction or ML data obtained from different files.
  • Clustering and Data Reduction: Cluster events and perform data reduction on individual events for both ML and normal analysis.
  • ML Analysis: Train and test different ensemble-based and deep learning-based classifiers on nanopore data.
  • Spectrogram and PSD: Calculate and plot spectrograms and Power Spectral Density (PSD) for selected data.
  • Nanopore Size Calc: Determine the size of nanopores based on conductance and solution conductivity measurements.
  • Resource Monitor: Monitor the utilization of computer resources, including GPU, CPU cores, and RAM.
  • Database Viewer: Easily view and review the settings used for data reduction as well as make some preliminary plots.

Installation

You can install Nanosense using pip:

pip install nanosense

Usage

To get started with Nanosense, simply import the package in your Python script:

import nanosense

Contributing

Contributions to Nanosense are welcome! If you encounter any issues, have suggestions for improvements, or would like to contribute new features, please open an issue or submit a pull request on the GitHub repository.

License

Nanosense is open-source software released under the MIT License.

Contact

For any questions or inquiries, please contact Shankar Dutt at shankar.dutt@anu.edu.au.

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