Aug 04, 2023
DQ-BSA quantification
- Narayana Yadavalli1,2,3,4,5,
- Shawn M. Ferguson1,2,3,4,6,5
- 1Department of Cell Biology, Yale University School of Medicine, New Haven, Connecticut 06510, USA;
- 2Neuroscience, Yale University School of Medicine, New Haven, Connecticut 06510, USA;
- 3Program in Cellular Neuroscience, Neurodegeneration and Repair;
- 4Wu Tsai Institute Yale University School of Medicine, New Haven, Connecticut 06510, USA;
- 5Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network, Chevy Chase, MD, 20815, USA;
- 6Kavli Institute for Neuroscience, Yale University School of Medicine, New Haven, Connecticut 06510, USA
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Abstract
This protocol describes DQ-BSA quantification.
Attachments
DQ-BSA quantification
DQ-BSA quantification
Segment maximal projection images from z-stacks spanning complete cells by using the find maxima function.
Threshold the duplicated images by default algorithm.
Combine the segmented and thresholder images by AND function to create a mask.
Obtain the mean gray values by applying analyze particle function to the mask and redirecting this whole analysis to the original images.