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Pengcheng Zhou edited this page Sep 26, 2017 · 4 revisions

Download

OPTION 1: download the package using this LINK

OPTION 2: (recommended) clone the git repository https://github.com/zhoupc/CNMF_E.git. In this way, you are able to get the latest updates of the package within 1-line command or 1-button click.

Installation

Run cnmfe_setup.m to add CNMF-E package to the search path of MATLAB

>> cnmfe_setup

CNMF-E requires CVX to denoise the extracted calcium traces. CNMF-E will automatically downloaded it and add it to the searching path.

Other required MATLAB toolboxes are listed below.

  1. /images/images
  2. /shared/optimlib/
  3. /signal/signal/
  4. /stats/stats/
  5. /curvefit/curvefit

Examples

The best way to get started is running a demo script for analyzing an example data. We included three demo scripts for you to try. You can modify these demos to process your own datasets.

  1. demo_endoscope.m : this demo is good for exploratory analysis of your data. It gives you a good sense of different stages of CNMF-E pipeline and how different parameter selections influence your final results.

    >> run demos/demo_endoscope.m

  2. demo_large_data_1p.m : this demo is good for processing large-scale dataset with the minimal manual intervention. It can process small data as well and should be used in most automated analysis.

    >> run demos/demo_large_data_1p.m

  3. demo_large_data_2p.m : this demo is the same as demo_large_data_1p.m. It is optimized for processing 2p data.

    >> run demos/demo_large_data_2p.m

Questions

You can ask questions by sending emails to zhoupc1988@gmail.com or joining our slack channel for discussions.

Reference

Please cite this paper when you use CNMF-E in your research. Thanks!

Zhou, P., Resendez, S.L., Rodriguez-Romaguera, J., Jimenez, J.C, Neufeld, S.Q., Stuber, G.D., Hen, R., Kheirbek, M.A., Sabatini, B.L., Kass, R.E., Paninski, L. (2016). Efficient and accurate extraction of in vivo calcium signals from microendoscopic video data. arXiv Prepr, arXiv1605.07266.

License

Copyright 2016 Pengcheng Zhou

This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with this program. If not, see http://www.gnu.org/licenses/.

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