genCorrelationMatrix

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Generate correlation matrix from image time series.

Description

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This function creates a Pearson's correlation matrix from ROIs of image time series data. Here, one can create the correlation matrix using either the centroid pixels and/or all the pixels from the ROIs (see parameters for details).

Input

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This function accepts only image time series with dimensions Y, X and T as input.

Output

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The output of this function is a .mat file containing the correlation matrix with dimensions N x N where N is the number of ROIs.

Note
The output of this function is used in the Analysis tab of the umIToolboxapp to visualize and compare grouped datasets.

For more information on the data structure of the output file, click here.

Note regarding the centroid calculation
In the case that there is more than a single region under the same ROI name, this function will calculate the centroid of the first region on the ROI list. This is applied only if the CorrAlgorithm parameter is set to centroid_vs_centroid or centroid_vs_agg and for the calculation of Seed-pixels correlation maps.

Parameters

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This parameter contains the name of the .mat file starting with ROImasks_ generated by the ROImanager app. This file contains the ROIs logical masks that will be used by this function to extract the ROI data.

This parameter sets the correlation algorithm to be used by the function. There are three options:

• centroid_vs_centroid: calculates the Pearson's correlation between the centroid pixels of all ROIs
• centroid_vs_agg: calculates the Pearson's correlation between the centroid pixel of the source ROI and the aggregated value (calculated using the function set in the SpatialAggFcn parameter) of the target ROI
• avg_vs_avg: calculates the Pearson's correlation between the spatial pixel average of both the source and the target ROIs

This parameter states the function that will be used to aggregate the ROI data. The selected function will be applied to all pixels inside the ROI.

Note
This parameter is used only when the parameter CorrAlgorithm is set to centroid_vs_agg. Otherwise, it will be ignored.

Set this parameter to True to apply a Fisher Z transformation of the Pearson's correlation values.

Set this parameter to True to create a file containing the Seed Pixel Correlation Maps for each ROI. The maps are created using the centroid pixel of the source ROI as seed. The maps are stored in a file named SPCMaps.mat and it can be accessed through the Analysis tab of umIToolbox app.

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