Photometry analysis - KravitzLab/KreedLabWiki GitHub Wiki

A python notebook containing code for processing and analyzing data captured with the RWD system is here!

Photometry pre-processing is a multi-step process that aims to remove motion artifacts from the fluorescent signal. The steps include:

Importing a .csv file containing your raw data

Fit an exponential curve to the isosbestic and fluorescence signals, to be used for subtracting out the bleaching trend

Subtract this fitted curve from the fluorescent and UV traces

Scaling the isosbestic and fluorescent signals to the same range, using a linear regression. Note how the values close to zero drive this scaling operation.

Subtract the scaled isosbestic from the fluorescence trace

Bandpass filter the signal to remove high and low frequency fluctuations (depending on your experimental goals this may not be desired)

After this, events of interest can be identified and peri-event traces can be made. Depending on the experimental design different approaches will be needed to define events.