Double FAST

Do you have reams of data? Finding the FAST GUI restrictively slow? If so, try using FAST's batch processing system, Double FAST.

Double FAST loads settings saved during a single run through the FAST GUI and applies them to multiple datasets, allowing rapid processing of very large quantities of data. Automation of the data import, segmentation, feature extraction, tracking and division detection stages of the FAST pipeline are supported, although not all stages need to be included during a single batch processing run.

To use Double FAST, you will need to have the Matlab-based version of FAST on your path and so, by implication, a Matlab license. Batch processing for users without a Matlab license is not currently supported.

The .m files required to run Double FAST are included in the main distribution of FAST, available from the download page. Please ensure that you download option 1, the Matlab-based version of FAST.

Double FAST requires both these files and the main FAST files have been added to your Matlab path.

To run Double FAST, you will need to perform two tasks:

1. Run FAST once on a single dataset, using the standard GUI. This generates files containing the settings used for each stage of the analysis.
2. Directly edit the DoubleFAST.m script.

If you are not used to editing code directly, don't panic! All you need to do is tell the software where your datasets are, and what stages in the analysis you would like to perform. By leaving these stages in your hands, DoubleFAST allows you to flexibly adapt your analysis to many different dataset structures and analytical requirements.

Once you have run FAST on your initial dataset, open the DoubleFAST.m script, available within the DoubleFast directory of your FAST installation. At the top of this script are the key variables that you need to define.

The first set of variables allow you to define the locations of your datasets:

mainRoot = 'C:\path\to\root\'; %Main directory in which all of your datasets is located
branches = {'Branch_1','Branch_2','Branch_3'}; %Names of subdirectories within main directory in which each separate dataset is stored
batchRoots = fullfile(mainRoot,branches);

By default, this is set up assuming a root-branch structure as shown below:

<diagram>

</diagram>

However, this can be flexibly adjusted according to your requirements. The only requirement is that batchRoots is defined as a cell array containing the paths to all of your datasets.

In the second part of the script, you tell Double FAST where it can find the settings files defined during the initial run through FAST:

%Filename of the unprocessed image data (Only need to define this if you are running from raw images)
imgName = 'Dataset 1.czi';
 
%The location of the metadata file output during image import (if the bioformats import system is used)
MetadataLoc = 'C:\original\analysis\root\Metadata.mat';
 
%The location of the segmentParams file saved following image segmentation
SegmentSettingsLoc = 'C:\original\analysis\root\SegmentationSettings.mat';
 
%The location of the featSettings file output following feature extraction
FeatureSettingsLoc = 'C:\original\analysis\root\CellFeatures.mat';
 
%The location of the track data generated following the object tracking stages
TrackSettingsLoc = 'C:\original\analysis\root\Tracks.mat';
 
%The location of the track data with divisions detected
DivisionSettingsLoc = 'C:\original\analysis\root\Tracks.mat';

If you wish to leave out some part of the main pipeline (for example, because you have already segmented your images using a separate program, or because you don't need to perform division detection), simply comment out the corresponding variables by placing a '%' symbol at the start of the line. To terminate processing at the feature detection stage for example, we would write:

%Filename of the unprocessed image data (Only need to define this if you are running from raw images)
imgName = 'Dataset 1.czi';
 
%The location of the metadata file output during image import (if the bioformats import system is used)
MetadataLoc = 'C:\original\analysis\root\Metadata.mat';
 
%The location of the segmentParams file saved following image segmentation
SegmentSettingsLoc = 'C:\original\analysis\root\SegmentationSettings.mat';
 
%The location of the featSettings file output following feature extraction
FeatureSettingsLoc = 'C:\original\analysis\root\CellFeatures.mat';
 
%The location of the track data generated following the object tracking stages
%TrackSettingsLoc = 'C:\original\analysis\root\Tracks.mat';
 
%The location of the track data with divisions detected
%DivisionSettingsLoc = 'C:\original\analysis\root\Tracks.mat';