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ionique

Pylint Pytest Documentation License: MIT

A modular nanopore signal analysis framework for ionic current data. Load recordings, filter noise, detect translocation events, segment sub-states, and extract features — all through a composable Python API or an interactive GUI.

Built for experimentalists who need custom analysis workflows without writing everything from scratch.

Quick start

from ionique.io import EDHReader
from ionique.datatypes import TraceFile
from ionique.parsers import AutoSquareParser
from ionique.utils import Filter, Trimmer, extract_features

# Load and preprocess
metadata, current, voltage = EDHReader("experiment.edh", voltage_compress=True)
trace = TraceFile(current, voltage=voltage, metadata=metadata)
Filter(cutoff_frequency=5000, filter_type="lowpass",
       sampling_frequency=trace.sampling_freq)(trace.current)
Trimmer(samples_to_remove=500)(trace)

# Detect events and extract features
detector = AutoSquareParser(threshold_baseline=0.7, expected_conductance=1.9)
trace.parse(detector, newrank="event", at_child_rank="vstepgap")
df = extract_features(trace, "event", ["mean", "std", "duration"])

Features

  • File I/O — read EDH, OPT, and ABF nanopore recordings
  • Signal preprocessing — lowpass/highpass/bandpass filtering, clock interference removal, voltage-step edge trimming
  • Event detection — AutoSquareParser for rectangular blockades, SpikeParser for brief spikes, lambda_event_parser for simple thresholds
  • Sub-state segmentation — SpeedyStatSplit (Cython-accelerated) resolves multi-level current structure within events
  • Feature extraction — export event statistics to pandas DataFrames
  • Visualization — quick-plot traces with qp_trace(), interactive dashboards with Panel/Bokeh
  • GUI workflows — Panel widgets for loading files, configuring parsers, and inspecting events in Jupyter

Installation

Python 3.10–3.13. Requires a C compiler for the Cython extension. To get the latest release:

pip install ionique

For latest unreleased version directly from GitHub:

pip install git+https://github.com/wanunulab/ionique.git

For development:

git clone https://github.com/wanunulab/ionique.git
cd ionique
pip install -e .

For GUI/dashboard features (Panel, Bokeh):

pip install ionique[panel]

Or in a development install:

pip install -e ".[panel]"

Documentation

Full user guide, tutorials, and API reference at ionique.readthedocs.io.

License

MIT License — see LICENSE for details.

© 2026 The Wanunu Lab.

About

Ionique is a new nanopore data analysis package from the Wanunu Lab, offering rapid, retraceable computations on ionic current data. Created by Ali Fallahi.

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