CellProfiler Pipeline: http://www.cellprofiler.org Version:1 SVNRevision:10415 LoadImages:[module_num:1|svn_version:\'10372\'|variable_revision_number:7|show_window:False|notes:\x5B\x5D] File type to be loaded:individual images File selection method:Text-Exact match Number of images in each group?:3 Type the text that the excluded images have in common:Do not use Analyze all subfolders within the selected folder?:No Input image file location:Default Input Folder\x7CNone Check image sets for missing or duplicate files?:Yes Group images by metadata?:No Exclude certain files?:No Specify metadata fields to group by: Image count:1 Text that these images have in common (case-sensitive):.tif Position of this image in each group:1 Extract metadata from where?:None Regular expression that finds metadata in the file name:^(?P.*)_(?P\x5BA-P\x5D\x5B0-9\x5D{2})_s(?P\x5B0-9\x5D) Type the regular expression that finds metadata in the subfolder path:.*\x5B\\\\/\x5D(?P.*)\x5B\\\\/\x5D(?P.*)$ Channel count:1 Group the movie frames?:No Grouping method:Interleaved Number of channels per group:3 Name this loaded image:OrigDAPI Channel number:1 Smooth:[module_num:2|svn_version:\'10300\'|variable_revision_number:1|show_window:True|notes:\x5B\x5D] Select the input image:OrigDAPI Name the output image:FilteredImage Select smoothing method:Median Filter Calculate artifact diameter automatically?:Yes Typical artifact diameter, in pixels:16.0 Edge intensity difference:0.1 CorrectIlluminationCalculate:[module_num:3|svn_version:\'10300\'|variable_revision_number:2|show_window:True|notes:\x5B\x5D] Select the input image:FilteredImage Name the output image:IllumBlue Select how the illumination function is calculated:Regular Dilate objects in the final averaged image?:No Dilation radius:1 Block size:60 Rescale the illumination function?:Yes Calculate function for each image individually, or based on all images?:Each Smoothing method:Median Filter Method to calculate smoothing filter size:Object size Approximate object size:42 Smoothing filter size:10 Retain the averaged image for use later in the pipeline (for example, in SaveImages)?:No Name the averaged image:IllumBlueAvg Retain the dilated image for use later in the pipeline (for example, in SaveImages)?:No Name the dilated image:IllumBlueDilated Automatically calculate spline parameters?:Yes Background mode:auto Number of spline points:5 Background threshold:2 Image resampling factor:2 Maximum number of iterations:40 Residual value for convergence:0.001 CorrectIlluminationApply:[module_num:4|svn_version:\'10300\'|variable_revision_number:3|show_window:True|notes:\x5B\x5D] Select the input image:FilteredImage Name the output image:CorrBlue Select the illumination function:IllumBlue Select how the illumination function is applied:Subtract EnhanceOrSuppressFeatures:[module_num:5|svn_version:\'10300\'|variable_revision_number:2|show_window:False|notes:\x5B\x5D] Select the input image:OrigDAPI Name the output image:FilteredBlue Select the operation:Suppress Feature size:10 Feature type:Neurites Range of hole sizes:1,10 IdentifyPrimaryObjects:[module_num:6|svn_version:\'10372\'|variable_revision_number:7|show_window:False|notes:\x5B\'Identify nuclei via segmentation.\'\x5D] Select the input image:OrigDAPI Name the primary objects to be identified:SegmentedNuclei Typical diameter of objects, in pixel units (Min,Max):20,60 Discard objects outside the diameter range?:Yes Try to merge too small objects with nearby larger objects?:No Discard objects touching the border of the image?:Yes Select the thresholding method:Otsu Global Threshold correction factor:2.5 Lower and upper bounds on threshold:0.000000,1.000000 Approximate fraction of image covered by objects?:0.01 Method to distinguish clumped objects:Shape Method to draw dividing lines between clumped objects:Intensity Size of smoothing filter:10 Suppress local maxima that are closer than this minimum allowed distance:7 Speed up by using lower-resolution image to find local maxima?:Yes Name the outline image:PrimaryOutlines Fill holes in identified objects?:Yes Automatically calculate size of smoothing filter?:Yes Automatically calculate minimum allowed distance between local maxima?:Yes Manual threshold:0.0 Select binary image:None Retain outlines of the identified objects?:No Automatically calculate the threshold using the Otsu method?:Yes Enter Laplacian of Gaussian threshold:0.5 Two-class or three-class thresholding?:Three classes Minimize the weighted variance or the entropy?:Weighted variance Assign pixels in the middle intensity class to the foreground or the background?:Background Automatically calculate the size of objects for the Laplacian of Gaussian filter?:Yes Enter LoG filter diameter:5 Handling of objects if excessive number of objects identified:Continue Maximum number of objects:500 Select the measurement to threshold with:None IdentifyPrimaryObjects:[module_num:7|svn_version:\'10372\'|variable_revision_number:7|show_window:False|notes:\x5B\'Identify nuclei but do not declump.\'\x5D] Select the input image:OrigDAPI Name the primary objects to be identified:UnifiedNuclei Typical diameter of objects, in pixel units (Min,Max):20,60 Discard objects outside the diameter range?:Yes Try to merge too small objects with nearby larger objects?:No Discard objects touching the border of the image?:Yes Select the thresholding method:Otsu Global Threshold correction factor:2.5 Lower and upper bounds on threshold:0.000000,1.000000 Approximate fraction of image covered by objects?:0.01 Method to distinguish clumped objects:None Method to draw dividing lines between clumped objects:Intensity Size of smoothing filter:10 Suppress local maxima that are closer than this minimum allowed distance:7 Speed up by using lower-resolution image to find local maxima?:Yes Name the outline image:PrimaryOutlines Fill holes in identified objects?:Yes Automatically calculate size of smoothing filter?:Yes Automatically calculate minimum allowed distance between local maxima?:Yes Manual threshold:0.0 Select binary image:None Retain outlines of the identified objects?:No Automatically calculate the threshold using the Otsu method?:Yes Enter Laplacian of Gaussian threshold:0.5 Two-class or three-class thresholding?:Three classes Minimize the weighted variance or the entropy?:Weighted variance Assign pixels in the middle intensity class to the foreground or the background?:Background Automatically calculate the size of objects for the Laplacian of Gaussian filter?:Yes Enter LoG filter diameter:5 Handling of objects if excessive number of objects identified:Continue Maximum number of objects:500 Select the measurement to threshold with:None IdentifySecondaryObjects:[module_num:8|svn_version:\'10300\'|variable_revision_number:7|show_window:False|notes:\x5B\'Identify cells on basis of unified nuclei.\'\x5D] Select the input objects:UnifiedNuclei Name the objects to be identified:Cells Select the method to identify the secondary objects:Propagation Select the input image:OrigDAPI Select the thresholding method:Otsu Global Threshold correction factor:1 Lower and upper bounds on threshold:0.000000,1.000000 Approximate fraction of image covered by objects?:0.01 Number of pixels by which to expand the primary objects:10 Regularization factor:0.05 Name the outline image:SecondaryOutlines Manual threshold:0.0 Select binary image:None Retain outlines of the identified secondary objects?:No Two-class or three-class thresholding?:Three classes Minimize the weighted variance or the entropy?:Weighted variance Assign pixels in the middle intensity class to the foreground or the background?:Foreground Discard secondary objects that touch the edge of the image?:No Discard the associated primary objects?:No Name the new primary objects:FilteredNuclei Retain outlines of the new primary objects?:No Name the new primary object outlines:FilteredNucleiOutlines Select the measurement to threshold with:None Fill holes in identified objects?:Yes RelateObjects:[module_num:9|svn_version:\'10300\'|variable_revision_number:2|show_window:False|notes:\x5B\x5D] Select the input child objects:SegmentedNuclei Select the input parent objects:Cells Calculate distances?:None Calculate per-parent means for all child measurements?:No Calculate distances to other parents?:No Parent name:None ClassifyObjects:[module_num:10|svn_version:\'10300\'|variable_revision_number:2|show_window:False|notes:\x5B\'Cells with more than one nuclei are binucleated.\'\x5D] Should each classification decision be based on a single measurement or on the combination of a pair of measurements?:Single measurement Hidden:1 Select the object to be classified:Cells Select the measurement to classify by:Children_SegmentedNuclei_Count Select bin spacing:Custom-defined bins Number of bins:2 Lower threshold:0 Use a bin for objects below the threshold?:Yes Upper threshold:1 Use a bin for objects above the threshold?:Yes Enter the custom thresholds separating the values between bins:1.5 Give each bin a name?:Yes Enter the bin names separated by commas:Mono, Bi Retain an image of the objects classified by their measurements, for use later in the pipeline (for example, in SaveImages)?:No Name the output image:ClassifiedNuclei Enter the object name:AllNuclei Select the first measurement:AreaShape_Area Method to select the cutoff:Custom Enter the cutoff value:0.5 Select the second measurement:None Method to select the cutoff:Mean Enter the cutoff value:0.5 Use custom names for the bins?:No Enter the low-low bin name:low_low Enter the low-high bin name:low_high Enter the high-low bin name:high_low Enter the high-high bin name:high_high Retain an image of the objects classified by their measurements, for use later in the pipeline (for example, in SaveImages)?:No Enter the image name:None FilterObjects:[module_num:11|svn_version:\'10300\'|variable_revision_number:5|show_window:False|notes:\x5B\'Filter cells on basis of same criteria\'\x5D] Name the output objects:BinucleatedCells Select the object to filter:Cells Filter using classifier rules or measurements?:Measurements Select the filtering method:Limits Select the objects that contain the filtered objects:None Retain outlines of the identified objects?:No Name the outline image:FilteredObjects Rules file location:Default Input Folder\x7CNone Rules file name:rules.txt Measurement count:1 Additional object count:0 Select the measurement to filter by:Children_SegmentedNuclei_Count Filter using a minimum measurement value?:Yes Minimum value:1.5 Filter using a maximum measurement value?:No Maximum value:1 ExportToSpreadsheet:[module_num:12|svn_version:\'10251\'|variable_revision_number:7|show_window:False|notes:\x5B\x5D] Select or enter the column delimiter:Comma (",") Prepend the output file name to the data file names?:Yes Add image metadata columns to your object data file?:No Limit output to a size that is allowed in Excel?:No Select the columns of measurements to export?:No Calculate the per-image mean values for object measurements?:No Calculate the per-image median values for object measurements?:No Calculate the per-image standard deviation values for object measurements?:No Output file location:Default Output Folder\x7CNone Create a GenePattern GCT file?:No Select source of sample row name:Metadata Select the image to use as the identifier:None Select the metadata to use as the identifier:None Export all measurements?:Yes Press button to select measurements to export: Data to export:Do not use Combine these object measurements with those of the previous object?:No File name:DATA.csv Use the object name for the file name?:Yes Crop:[module_num:13|svn_version:\'10300\'|variable_revision_number:2|show_window:True|notes:\x5B\x5D] Select the input image:OrigDAPI Name the output image:CropBlue Select the cropping shape:Objects Select the cropping method:Coordinates Apply which cycle\'s cropping pattern?:Every Left and right rectangle positions:0,end Top and bottom rectangle positions:0,end Coordinates of ellipse center:500,500 Ellipse radius, X direction:400 Ellipse radius, Y direction:200 Use Plate Fix?:No Remove empty rows and columns?:No Select the masking image:None Select the image with a cropping mask:None Select the objects:Cells MaskImage:[module_num:14|svn_version:\'10300\'|variable_revision_number:3|show_window:True|notes:\x5B\x5D] Select the input image:OrigDAPI Name the output image:MaskBlue Use objects or an image as a mask?:Objects Select object for mask:BinucleatedCells Select image for mask:None Invert the mask?:No