Bio-Rad EXQuest Spot Cutter - Manual (Page 18)

Introduction
1-5
Spot Identification
Now you are ready to identify the spots in the gel. The Spot Detection Wizard
automates the process of selecting the proper spot detection parameters for your gels.
Using the Wizard, you select the parameters, study the results of spot detection, then
adjust the parameters until you have identified all spots of interest in your gels.
When spots are detected in PDQuest, the original gel image is filtered and smoothed
to clarify the spots, then three-dimensional Gaussian spots are created from the
clarified spots. The end result is three separate images: the original unaltered scan (2-
D Scan), the filtered and processed scan (Filtered image), and a synthetic image
containing the Gaussian spots (Gaussian image).
Fig. 1-3. Images created during spot detection.
All spot matching and analysis in PDQuest are performed on Gaussian spots.
What Are Gaussian Spots?
Fuzzy, streaked, or overlapping spots in a 2-D gel can be difficult to accurately
distinguish and quantify. Because the image profile of an ideal spot confirms to a
Gaussian curve, PDQuest uses Gaussian modeling to generate spots that can be
precisely identified and quantitated.
A Gaussian spot is a three-dimensional representation of an original scanned spot.
Gaussian curves are fitted to the scanned spot in the X and Y dimensions, and then
additional modeling is performed to create the final Gaussian spot.
Using Gaussian modeling, you can accurately quantitate overlapping spots, spots in
gel streaks, and multiple spots in dense clusters.
2-D Scan Filtered Image Gaussian Image