This ZHENG_STRAINS_CODE_README.txt file was generated on 2022-6-21 by JINGYANG ZHENG (jz848@cornell.edu)


GENERAL INFORMATION

1. Title: Code from: STRAINS: A Big Data Method for Classifying Cellular Response to Stimuli at the Tissue Scale 

2. Author Information
	A. Principal Investigator Contact Information
		Name: Jingyang Zheng
		Institution: Cornell University
		Address: C7 Clark Hall
		Email: jz848@cornell.edu

	B. Associate or Co-investigator Contact Information
		Name: Itai Cohen
		Institution: Cornell University
		Address: 
		Email: itai.cohen@cornell.edu

3. Date of data collection (single date, range, approximate date): 2019-09-26

4. Geographic location of data collection: CCMR 3i Marianas Spinning Disc Confocal Microscope, Cornell University, Ithaca, NY, USA

5. Information about funding sources that supported the collection of the data: The work was supported by the NIH National Institute of Arthritis and Musculoskeletal and Skin Diseases, Contract: 5R01AR071394-04, K08AR068470, R03AR075929, and The Harry M. Zweig Fund for Equine Research. Additionally, this work was supported by the National Science Foundation grants DMR-1807602, DMR-1808026, CBET-1604712, CMMI 1927197, and BMMB-1536463. Lastly, this work made use of the Cornell Center for Materials Research Shared Facilities which are supported through the NSF MRSEC program (DMR-1719875).


SHARING/ACCESS INFORMATION

1. Licenses/restrictions placed on the data: MIT License

Copyright 2022 Jingyang Zheng

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: attribution to the copyright holder (Jingyang Zheng) and citation of the associated publication (https://www.biorxiv.org/content/10.1101/2022.06.12.495830v2), and email the copyright holder (jz848@cornell.edu) so that the copyright holder can share and cite examples of adaptations

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

2. Links to publications that cite or use the data: https://www.biorxiv.org/content/10.1101/2022.06.12.495830v2, and to be submitted to PLOS One

3. Links to other publicly accessible locations of the data: the code is publicly accessible on Github at https://github.com/jingyangzheng/STRAINS

4. Links/relationships to ancillary data sets: 

5. Was data derived from another source? no
	A. If yes, list source(s): 

6. Recommended citation for this code: 
Zheng, Jingyang, Thomas Wyse Jackson, Lisa Fortier, Lawrence Bonassar, Michelle Delco, and Itai Cohen (2022). Code from: STRAINS: A Big Data Method for Classifying Cellular Response to Stimuli at the Tissue Scale [Source Code] Cornell University Library eCommons Digital Repository. https://doi.org/10.7298/ds7s-nc16


DATA & FILE OVERVIEW

STRAINS GUI
	cellGUI_preMATLAB2019: older version of the app that uses a workaround for click detection, not recommended
	STRAINS_GUI: present version of the GUI, requires MATLAB 2019a or newer


Matlab Codes

Dependencies: requires Crocker & Grier particle tracking code found here: 		https://site.physics.georgetown.edu/matlab/
		requires export_fig from the Matlab Fileshare found here: 			https://www.mathworks.com/matlabcentral/fileexchange/23629-export_fig
		requires Matlab Signal Processing Toolbox

	all_tracking_function_calls: demonstration of function call usage, all parameter are input here and example parameters are included. 
	CellAttributes: compiles the attributes of each cell (peaks, changepoints, etc)
	DecisionTree: the actual if-else statements that make up the decision tree
	FeatureExtraction: gets changepoints and peaks from each cell
	ImageReg_EXAMPLE: example code for image registration, useful for connecting pos1 and impact data
	ManualDataCompilation: scrapes category names from folders after manual sorting
	PositionLabels: save labels for each position by order of CellID (number given by Crocker & Grier)
	SetFigureDefaults: sets figure defaults for plotting
	sorting_function_calls_manual and sorting_function_calls_nomanual: function calls for sorting the data, split between whether or not the data was manually sorted
	SplitPeaksDataCompilation and SplitPeaksDataCompilationNoLabels: compiles data information depending on whether or not manual labels exist
	TrackImpact and TrackPostImpact: tracking code for impact or post-impact videos (impact = 1 channel, post-impact = RGB), outputs intensity information

NOTE that a parent folder of the data is necessary as input in several scripts; edit this as needed for your local path (eg. all_tracking_function_calls, sorting_function_calls_manual and sorting_function_calls_nomanual)


Python Classification Codes - written in Python 3.8
	classifier_function_calls: example code for how to use the functions
	classifier_functions: all functions associated with the time series classifications in this publication
	
NOTE that a parent folder of the data is necessary as input in classifier_function_calls; edit these as needed for your local path (eg. os.chdir and parentdir)

METHODOLOGICAL INFORMATION

1. Description of methods used for collection/generation of data: 
A detailed description can be found in the methods section of https://www.biorxiv.org/content/10.1101/2022.06.12.495830v2
and supplementary information document included

2. Methods for processing the data: 
Slidebook images (.sld) were converted into .tiff files and then either 8-bit (impact image) or RGB color (all other images) in ImageJ/Fiji before the MATLAB code is run

3. Instrument- or software-specific information needed to interpret the data: 
The free version of Slidebook will allow conversion from (.sld) to (.tiff), all included images are in .tiff format
Matlab scripts were created in Matlab 2021a.

4. Standards and calibration information, if appropriate: 

5. Environmental/experimental conditions: 

6. Describe any quality-assurance procedures performed on the data: 

7. People involved with sample collection, processing, analysis and/or submission:
Jingyang Zheng, Thomas Wyse Jackson, Lisa A. Fortier, Lawrence J. Bonassar, Michelle L. Delco, Itai Cohen