Sima

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Overview

SIMA (Sequential IMage Analysis) is an Open Source package for analysis of time-series imaging data arising from fluorescence microscopy. The functionality of this package includes:

• correction of motion artifacts
• segmentation of imaging fields into regions of interest (ROIs)
• extraction of dynamic signals from ROIs

The included ROI Buddy software provides a graphical user interface (GUI) supporting the following functionality:

• manual creation of ROIs
• editing of ROIs resulting from automated segmentation
• registration of ROIs across separate imaging sessions

Installation and Use

For complete documentation go to http://www.losonczylab.org/sima

Dependencies

• Python <http://python.org>_ 2.7
• numpy <http://www.scipy.org>_ >= 1.6.2
• scipy <http://www.scipy.org>_ >= 0.13.0
• scikit-image <http://scikit-image.org>_ >= 0.9.3 (0.11.0 recommended)
• scikit-learn <http://scikit-learn.org>_ >= 0.11
• shapely <https://pypi.python.org/pypi/Shapely>_ >= 1.2.14 (Windows users: be sure to install from Christophe Gohlke's built wheels <http://www.lfd.uci.edu/~gohlke/pythonlibs/#shapely>_)
• pillow <https://pypi.python.org/pypi/Pillow>_ >= 2.6.1
• future <https://pypi.python.org/pypi/future>_ >= 0.14

Optional dependencies

• OpenCV <http://opencv.org>_ >= 2.4.8, required for segmentation, registration of ROIs across multiple datasets, and the ROI Buddy GUI
• picos <http://picos.zib.de>_ >= 1.0.2, required for spike inference (>= 1.1 required for Python 3)
• pyfftw <https://pypi.python.org/pypi/pyFFTW>_, allows faster performance of some motion correction methods when installed together with FFTW.
• h5py <http://www.h5py.org>_ >= 2.2.1 (2.3.1 recommended), required for HDF5 file format
• bottleneck <http://pypi.python.org/pypi/Bottleneck>_ >=0.8, for faster calculations
• matplotlib <http://matplotlib.org>_ >= 1.2.1, for saving extraction summary plots
• mdp <http://mdp-toolkit.sourceforge.net>_, required for ICA demixing of channels

If you build the package from source, you may also need:

• Cython <http://cython.org>_

If you are using the spike inference feature, we strongly recommend installing MOSEK <https://www.mosek.com/>_ (free for academic use) which greatly speeds up the inference.

Citing SIMA

If you use SIMA for your research, please cite the following paper in any resulting publications:

Kaifosh P, Zaremba J, Danielson N, and Losonczy A. SIMA: Python software for analysis of dynamic fluorescence imaging data. Frontiers in Neuroinformatics. 2014 Aug 27; 8:77. doi: 10.3389/fninf.2014.00080. <http://dx.doi.org/10.3389/fninf.2014.00080>_

License

Unless otherwise specified in individual files, all code is

Copyright (C) 2014 The Trustees of Columbia University in the City of New York.

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 2 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/.