Skip to main content

Calcium Imaging Pipeline Tool

Project description

optinist optinist

PYPI PYPI

OptiNiSt(Optical Neuroimage Studio) is a GUI based workflow pipeline tools for processing two-photon calcium imaging data.

OptiNiSt helps researchers try multiple data analysis methods, visualize the results, and construct the data analysis pipelines easily and quickly on GUI. OptiNiSt's data-saving format follows NWB standards.

OptiNiSt also supports reproducibility of scientific research, standardization of analysis protocols, and developments of novel analysis tools as plug-in.

Support library

ROI detection

Postprocessing

  • Basic Neural Analysis(Event Trigger Average...)
  • Dimenstion Reduction(PCA...)
  • Neural Decoding(LDA...)
  • Neural Population Analysis(Correlation...)

Saving Format

Key Features

:beginner: Easy-To-Create Workflow

  • zero-knowledge of coding: OptiNiSt allows you to create analysis pipelines easily on the GUI.

:zap: Visualizing analysis results

  • quick visualization: OptiNiSt supports you visualize the analysis results by plotly.

:rocket: Managing Workflows

  • recording and reproducing: OptiNiSt records and reproduces the workflow pipelines easily.

Installation

Need anaconda or miniconda environment.

conda create -n optinist python=3.8
conda activate optinist

Install from pip.

pip install optinist

launch.

run_optinist

Open browser. http://localhost:8000

Documentation

https://optinist.readthedocs.io/en/latest/

Using GUI

Workflow

  • OptiNiSt allows you to make your analysis pipelines by graph style using nodes and edges on GUI. Parameters for each analysis are easily changeable.

workflow

Visualize

  • OptiNiSt allows you to visualize the analysis results with one click by plotly. It supports a variety of plotting styles.

visualize

Record

  • OptiNiSt supports you in recording and reproducing workflow pipelines in an organized manner.

record

Contributors

Proposers

Kenji Doya, Yukako Yamane OIST Neural Computation Unit

Main Developers

Shogo Akiyama, Yoshifumi Takeshima

Support Developers

Tatsuya Tanabe, Yosuke Kaneko, Syuya Saeki

References

[Suite2p] Marius Pachitariu, Carsen Stringer, Mario Dipoppa, Sylvia Schröder, L. Federico Rossi, Henry Dalgleish, Matteo Carandini, Kenneth D. Harris. "Suite2p: beyond 10,000 neurons with standard two-photon microscopy". 2017
[CaImAn] Andrea Giovannucci Is a corresponding author, Johannes Friedrich, Pat Gunn, Jérémie Kalfon, Brandon L Brown, Sue Ann Koay, Jiannis Taxidis, Farzaneh Najafi, Jeffrey L Gauthier, Pengcheng Zhou, Baljit S Khakh, David W Tank, Dmitri B Chklovskii, Eftychios A Pnevmatikakis. "CaImAn: An open source tool for scalable Calcium Imaging data Analysis". 2019
[LCCD] Tsubasa Ito, Keisuke Ota, Kanako Ueno, Yasuhiro Oisi, Chie Matsubara, Kenta Kobayashi, Masamichi Ohkura, Junichi Nakai, Masanori Murayama, Toru Aonishi, "Low computational-cost cell detection method for calcium imaging data", 2022 [PyNWB] Oliver Rübel, Andrew Tritt, Ryan Ly, Benjamin K. Dichter, Satrajit Ghosh, Lawrence Niu, Ivan Soltesz, Karel Svoboda, Loren Frank, Kristofer E. Bouchard, "The Neurodata Without Borders ecosystem for neurophysiological data science", bioRxiv 2021.03.13.435173, March 15, 2021

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

optinist-1.0.0.tar.gz (7.2 MB view details)

Uploaded Source

Built Distribution

optinist-1.0.0-py3-none-any.whl (7.3 MB view details)

Uploaded Python 3

File details

Details for the file optinist-1.0.0.tar.gz.

File metadata

  • Download URL: optinist-1.0.0.tar.gz
  • Upload date:
  • Size: 7.2 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.8.18

File hashes

Hashes for optinist-1.0.0.tar.gz
Algorithm Hash digest
SHA256 bb9ee9357b409002ec3d0890a3927e82c53dc8bd555e5eb842bd975a1acd5171
MD5 713d611260c1c026add92c9936412b6e
BLAKE2b-256 d2f6803ca436c23ddfca39ba381e7070c44aabf890fb55c4659a0897c4ea7b1d

See more details on using hashes here.

File details

Details for the file optinist-1.0.0-py3-none-any.whl.

File metadata

  • Download URL: optinist-1.0.0-py3-none-any.whl
  • Upload date:
  • Size: 7.3 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.8.18

File hashes

Hashes for optinist-1.0.0-py3-none-any.whl
Algorithm Hash digest
SHA256 e5ae83bce3bd91e8df4c1d0f51fdea0064fc47af47939226a26e089a1cc46f50
MD5 5f025ef3452cd0f6a5877ef7747b8223
BLAKE2b-256 bc7d58524b629d244ca502e755e2122b6d6ef71b14119f1351cb60b92ca97d84

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page