Matt:LabNotes/2014-8-20

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Decoding PGP1F with Agi26k0gap Rolonies Using PISA Mask[edit]

  • Images saved in: Dropbox\GradZhangLab\FullDecoding_v1
  1. First did Max Intensity Projection of the 21 images
    • 7 cycles each with 3 color channels (Cycle1-488, Cycle1-Cy3, Cycle1-Cy5, Cycle2-488,...)
  2. Then used PISA on MIP image to identify all secondary rolonies
 Use: PISA Gui
 v1:			6870 rolonies
               DataFileFilter = '*_20x_4k_*.tif';
               PISAParam.log_radius = 2;
               PISAParam.log_upper = -5e-4;            
               PISAParam.area_upper = 50;            
               PISAParam.area_lower = 9;
               PISAParam.axratio_lower = 0.5;            
               PISAParam.circ_upper = 1.6;            
               PISAParam.circ_lower = 0.8;            
               PISAParam.pconn = 8;            
               PISAParam.bkgmult_lower = 3; 
 v2:			4030 rolonies	
               DataFileFilter = '*_20x_4k_*.tif';
               PISAParam.log_radius = 3;
               PISAParam.log_upper = -2e-4;            
               PISAParam.area_upper = 100;            
               PISAParam.area_lower = 4;
               PISAParam.axratio_lower = 0.6;            
               PISAParam.circ_upper = 1.6;            
               PISAParam.circ_lower = 0.8;            
               PISAParam.pconn = 8;            
               PISAParam.bkgmult_lower = 7; 
 v3:			 4658 rolonies	
               DataFileFilter = '*_20x_4k_*.tif';
               PISAParam.log_radius = 3;
               PISAParam.log_upper = -2e-5;            
               PISAParam.area_upper = 144;            
               PISAParam.area_lower = 16;
               PISAParam.axratio_lower = 0.6;            
               PISAParam.circ_upper = 1.6;            
               PISAParam.circ_lower = 0.8;            
               PISAParam.pconn = 8;            
               PISAParam.bkgmult_lower = 4; 
 Use: Rolony_Counting_Batch_8a.m				
 v4:			  4382 rolonies	
               DataFileFilter = '*_20x_4k_*.tif';
               PISAParam.log_radius = 3;
               PISAParam.log_upper = -2e-5;            
               PISAParam.area_upper = 144;            
               PISAParam.area_lower = 16;
               PISAParam.axratio_lower = 0.6;            
               PISAParam.circ_upper = 1.6;            
               PISAParam.circ_lower = 0.8;            
               PISAParam.pconn = 8;            
               PISAParam.bkgmult_lower = 4; 	
 v5:			  4382 rolonies	 (same as v4 so deleted)
               DataFileFilter = '*_20x_4k_*.tif';
               PISAParam.log_radius = 3;
               PISAParam.log_upper = -2e-4;            
               PISAParam.area_upper = 144;            
               PISAParam.area_lower = 16;
               PISAParam.axratio_lower = 0.6;            
               PISAParam.circ_upper = 1.6;            
               PISAParam.circ_lower = 0.8;            
               PISAParam.pconn = 8;            
               PISAParam.bkgmult_lower = 3;
  1. Used bwimage from PISA to mask each of the 21 images and then regionprops to obtain MeanIntensity, Area, and Centroid values for each feature