MATLAB component

The MATLAB analysis codebase consists of three types of files.  It is adapted from code originally written by Carl Hansen's lab at the University of British Columbia. This ancestry is most apparent in functions in the folder RifkinLab_YeastAnalysisScripts:HansenLabModifiedPipeline which are identical or slight modifications of that original code base.  The code also includes utility functions predominantly downloaded from the matlab file exchange in the folder UtilityFunctionsFromOthers. The final set of files are in the RifkinLab_YeastAnalysisScripts folder and consist of functions written in the Rifkin lab to analyze yeast images.  These are covered by the BSD 3-Clause license as indicated in the LICENSE.txt file.

Steps for the analysis
1) Write AnalysisValues.csv file and put in the main directory for an experiment
2) Use maskPopulatedAreaGUI to generate cellRegionMasks.mat file. This is a cell array the length of the number of frames.
Every 25th frame has a image which has a mask that designates where the cells are in that set of frames.  Any objects outside the masked area will be discarded.
3) Run yeastSegmentGUI to choose 3 parameter sets for segmentation.
4) Run analyzeYeastFluorescence_Chunked.  This will:
    a) Setup the directory structure
    b) Bring up an image window to let the user adjust for shifts caused by microscope bumps (e.g. raising and lowering transillumination setup). Not relevant for these galactose experiments, but useful when new media needs to be pipetted in by hand.
    c) Runs segmentation for each parameter set on each frame calling yeastSegment_WValsFromGUI and associated cleanup functions. 
    d) Copies files over to chunk folder (helps things go faster)
    e) Starts tracking using newYeastTracker
    f) Reassembles the chunks into a continuous set of frames using reassembleChunks
    ------ This fluorescence part is irrelevant - preserved for legacy purposes -----------------
        g) Calculates fluorescence values using processFluorescence_SRS_Chunked
        h) Does some fluorescence normalization.  This part, however, is superseded by the R code.
    ----------------------------------------------------------------------------------------------
5) Run yeastMarkControlCellsGUI.  This lets the user curate and train the classifier for distinguishing bad/control/experimental cells. It relies on the MySQL database.
6) Store information in MySQL database using storeInfoInMYSQL which sets up tables cellStatsForRF, cellData, cellLocs and stores this information, doing some data processing as it goes. The RF is commented out because this didn't need to be done over and over.
7) makeAppendixFigure5 does what it says (with some post-processing in Illustrator).

R component

README file for the R components of analyzing this data

The RCode_YeastVectorFieldProject-2016-11-29.tar.gz is a packrat bundle (https://rstudio.github.io/packrat/) containing everything needed to reproduce the analysis including data files and R scripts and the R libraries used at the time the analysis was done.  It should be possible to unbundle the package in R or extract it using standard unarchiving tools and run it.

Inside the .tar.gz archive is an RStudio project that can be opened.  The key document is an R markdown document called completeAnalysisAndPlotting.Rmd.  This walks the user through the analysis with subheadings for the various steps.

Note that the analysis has the option of requesting data from a MySQL database.  This bundle does not contain that database.  However, a dump of that database can be found in another component of this digital collection.
 
The R analysis scripts are covered by the BSD 3-clause license, which can be found below.

Copyright (c) 2016, Scott Alan Rifkin
All rights reserved.

Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:

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