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110803TemplatePipelineCountInfectedCells3Chan_parallel_cols01-06.cp
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CellProfiler Pipeline: http://www.cellprofiler.org
Version:1
SVNRevision:11000
LoadImages:[module_num:1|svn_version:\'10951\'|variable_revision_number:11|show_window:False|notes:\x5B\x5D]
File type to be loaded:individual images
File selection method:Text-Regular expressions
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?:All
Input image file location:Default Input Folder\x7CNone
Check image sets for missing or duplicate files?:Yes
Group images by metadata?:Yes
Exclude certain files?:No
Specify metadata fields to group by:Well
Select subfolders to analyze:
Image count:3
Text that these images have in common (case-sensitive):\\w*1\x5B0-2\x5D\\w*w1.TIF
Position of this image in each group:1
Extract metadata from where?:File name
Regular expression that finds metadata in the file name:^(?P<Plate>.*)_(?P<Well>\x5BA-P\x5D\x5B0-9\x5D{2})_s(?P<Site>\x5B0-9\x5D*)
Type the regular expression that finds metadata in the subfolder path:.*\x5B\\\\/\x5D(?P<Date>.*)\x5B\\\\/\x5D(?P<Run>.*)$
Channel count:1
Group the movie frames?:No
Grouping method:Interleaved
Number of channels per group:2
Load the input as images or objects?:Images
Name this loaded image:Nuclei
Name this loaded object:Nuclei
Retain outlines of loaded objects?:No
Name the outline image:NucleiOutlines
Channel number:1
Rescale intensities?:Yes
Text that these images have in common (case-sensitive):\\w*1\x5B0-2\x5D\\w*w2.TIF
Position of this image in each group:2
Extract metadata from where?:File name
Regular expression that finds metadata in the file name:^(?P<Plate>.*)_(?P<Well>\x5BA-P\x5D\x5B0-9\x5D{2})_s(?P<Site>\x5B0-9\x5D*)
Type the regular expression that finds metadata in the subfolder path:.*\x5B\\\\/\x5D(?P<Date>.*)\x5B\\\\/\x5D(?P<Run>.*)$
Channel count:1
Group the movie frames?:No
Grouping method:Interleaved
Number of channels per group:2
Load the input as images or objects?:Images
Name this loaded image:VirusSignal
Name this loaded object:Nuclei
Retain outlines of loaded objects?:No
Name the outline image:NucleiOutlines
Channel number:1
Rescale intensities?:Yes
Text that these images have in common (case-sensitive):\\w*1\x5B0-2\x5D\\w*w3.TIF
Position of this image in each group:3
Extract metadata from where?:File name
Regular expression that finds metadata in the file name:^(?P<Plate>.*)_(?P<Well>\x5BA-P\x5D\x5B0-9\x5D{2})_s(?P<Site>\x5B0-9\x5D*)
Type the regular expression that finds metadata in the subfolder path:.*\x5B\\\\/\x5D(?P<Date>.*)\x5B\\\\/\x5D(?P<Run>.*)$
Channel count:1
Group the movie frames?:No
Grouping method:Interleaved
Number of channels per group:3
Load the input as images or objects?:Images
Name this loaded image:RedChan
Name this loaded object:Nuclei
Retain outlines of loaded objects?:No
Name the outline image:LoadedImageOutlines
Channel number:1
Rescale intensities?:Yes
IdentifyPrimaryObjects:[module_num:2|svn_version:\'10826\'|variable_revision_number:8|show_window:False|notes:\x5B\x5D]
Select the input image:Nuclei
Name the primary objects to be identified:DetectedNuclei
Typical diameter of objects, in pixel units (Min,Max):10,45
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:1
Lower and upper bounds on threshold:0.000000,1.000000
Approximate fraction of image covered by objects?:0.01
Method to distinguish clumped objects:Intensity
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?:No
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?:Two classes
Minimize the weighted variance or the entropy?:Weighted variance
Assign pixels in the middle intensity class to the foreground or the background?:Foreground
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:3|svn_version:\'10826\'|variable_revision_number:7|show_window:False|notes:\x5B\x5D]
Select the input objects:DetectedNuclei
Name the objects to be identified:Cells
Select the method to identify the secondary objects:Distance - N
Select the input image:VirusSignal
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:5
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?:Two 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?:No
IdentifyTertiaryObjects:[module_num:4|svn_version:\'10300\'|variable_revision_number:1|show_window:False|notes:\x5B\x5D]
Select the larger identified objects:Cells
Select the smaller identified objects:DetectedNuclei
Name the tertiary objects to be identified:Cytoplasm
Name the outline image:CytoplasmOutlines
Retain outlines of the tertiary objects?:No
MeasureObjectIntensity:[module_num:5|svn_version:\'10816\'|variable_revision_number:3|show_window:False|notes:\x5B\x5D]
Hidden:1
Select an image to measure:VirusSignal
Select objects to measure:Cells
Select objects to measure:DetectedNuclei
Select objects to measure:Cytoplasm
MeasureObjectIntensity:[module_num:6|svn_version:\'10816\'|variable_revision_number:3|show_window:True|notes:\x5B\x5D]
Hidden:1
Select an image to measure:RedChan
Select objects to measure:Cells
Select objects to measure:DetectedNuclei
Select objects to measure:Cytoplasm
ExportToSpreadsheet:[module_num:7|svn_version:\'10880\'|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?:Yes
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, using default file names?: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