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Spike detection and automatic clustering for spike sorting

Project description

# Klusta: automatic spike sorting up to 64 channels

[![Build Status](https://img.shields.io/travis/kwikteam/klusta.svg)](https://travis-ci.org/kwikteam/klusta) [![codecov.io](https://img.shields.io/codecov/c/github/kwikteam/klusta.svg)](http://codecov.io/github/kwikteam/klusta?branch=master) [![Documentation Status](https://readthedocs.org/projects/klusta/badge/?version=latest)](http://klusta.readthedocs.org/en/latest/) [![PyPI release](https://img.shields.io/pypi/v/klusta.svg)](https://pypi.python.org/pypi/klusta) [![GitHub release](https://img.shields.io/github/release/kwikteam/klusta.svg)](https://github.com/kwikteam/klusta/releases/latest)

[klusta](https://github.com/kwikteam/klusta) is an open source package for automatic spike sorting of multielectrode neurophysiological recordings made with probes containing up to a few dozens of sites.

We are also working actively on more sophisticated algorithms that will scale to hundreds/thousands of channels. This work is being done within the [phy project](https://github.com/kwikteam/phy), which is still experimental at this point.

## Overview

klusta implements the following features:

  • Kwik: An HDF5-based file format that stores the results of a spike sorting session.

  • Spike detection (also known as SpikeDetekt): an algorithm designed for probes containing tens of channels, based on a flood-fill algorithm in the adjacency graph formed by the recording sites in the probe.

  • Automatic clustering (also known as Masked KlustaKwik): an automatic clustering algorithm designed for high-dimensional structured datasets.

## GUI

You will need a GUI to visualize the spike sorting results.

We have developed two GUI programs with the same features:

  • phy KwikGUI: newer project, scales to hundreds/thousands of channels, still relatively experimental. It will be automatically installed if you follow the install instructions below.

  • [KlustaViewa](https://github.com/klusta-team/klustaviewa): widely used, but older and a bit hard to install since it relies on very old dependencies.

Both GUIs work with the same Kwik format.

## Quick install guide

The following instructions will install both klusta and the phy KwikGUI.

  1. Make sure that you have [miniconda](http://conda.pydata.org/miniconda.html) installed. You can choose the Python 3.5 64-bit version for your operating system (Linux, Windows, or OS X).

  2. [Download the environment file.](https://raw.githubusercontent.com/kwikteam/klusta/master/installer/environment.yml)

  3. Open a terminal (on Windows, cmd, not Powershell) in the directory where you saved the file and type:

    `bash conda env create -n klusta -f environment.yml `

  4. Done! Now, to use klusta and the phy KwikGUI, enter the directory that contains your files and type:

    `bash source activate klusta # omit the `source` on Windows klusta yourfile.prm # spikesort your data with a PRM file phy kwik-gui yourfile.kwik # open the GUI `

    See the documentation for more details.

### Updating the software

To get the latest version of the software, open a terminal and type:

` source activate klusta # omit the `source` on Windows pip install klusta phy phycontrib --upgrade `

## Technical details

klusta is written in pure Python. The clustering code, written in Python and Cython, currently lives in [another repository](https://github.com/kwikteam/klustakwik2/).

## Links

## Credits

klusta is developed by [Cyrille Rossant](http://cyrille.rossant.net), [Shabnam Kadir](https://iris.ucl.ac.uk/iris/browse/profile?upi=SKADI56), [Dan Goodman](http://thesamovar.net/), [Max Hunter](https://iris.ucl.ac.uk/iris/browse/profile?upi=MLDHU99), and [Kenneth Harris](https://iris.ucl.ac.uk/iris/browse/profile?upi=KDHAR02), in the [Cortexlab](https://www.ucl.ac.uk/cortexlab), University College London.

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