ExampleFly.cppipe

CellProfiler Pipeline: http://www.cellprofiler.org
Version:5
DateRevision:500
GitHash:
ModuleCount:14
HasImagePlaneDetails:False

LoadData:[module_num:1|svn_version:'Unknown'|variable_revision_number:6|show_window:True|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Input data file location:Default Input Folder|workspace
    Name of the file:load_data.csv
    Load images based on this data?:Yes
    Base image location:Default Input Folder|
    Process just a range of rows?:No
    Rows to process:1,100000
    Group images by metadata?:Yes
    Select metadata tags for grouping:Position
    Rescale intensities?:Yes

IdentifyPrimaryObjects:[module_num:2|svn_version:'Unknown'|variable_revision_number:15|show_window:True|notes:['Identify the nuclei from the DAPI image. Three-class thresholding performs better than the default two-class thresholding in this case.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Select the input image:OrigBlue
    Name the primary objects to be identified:Nuclei
    Typical diameter of objects, in pixel units (Min,Max):10,40
    Discard objects outside the diameter range?:Yes
    Discard objects touching the border of the image?:Yes
    Method to distinguish clumped objects:Shape
    Method to draw dividing lines between clumped objects:Shape
    Size of smoothing filter:10
    Suppress local maxima that are closer than this minimum allowed distance:5
    Speed up by using lower-resolution image to find local maxima?:Yes
    Fill holes in identified objects?:After both thresholding and declumping
    Automatically calculate size of smoothing filter for declumping?:Yes
    Automatically calculate minimum allowed distance between local maxima?:Yes
    Handling of objects if excessive number of objects identified:Continue
    Maximum number of objects:500
    Use advanced settings?:Yes
    Threshold setting version:12
    Threshold strategy:Global
    Thresholding method:Minimum Cross-Entropy
    Threshold smoothing scale:1.3488
    Threshold correction factor:1.0
    Lower and upper bounds on threshold:0,1
    Manual threshold:0.0
    Select the measurement to threshold with:None
    Two-class or three-class thresholding?:Three classes
    Log transform before thresholding?:No
    Assign pixels in the middle intensity class to the foreground or the background?:Background
    Size of adaptive window:10
    Lower outlier fraction:0.05
    Upper outlier fraction:0.05
    Averaging method:Mean
    Variance method:Standard deviation
    # of deviations:2
    Thresholding method:Otsu

IdentifySecondaryObjects:[module_num:3|svn_version:'Unknown'|variable_revision_number:10|show_window:True|notes:['Identify the cells by using the nuclei as a "seed" region, then growing outwards until stopped by the image threshold or by a neighbor. The Propagation method is used to delineate the boundary between neighboring cells.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Select the input objects:Nuclei
    Name the objects to be identified:Cells
    Select the method to identify the secondary objects:Propagation
    Select the input image:OrigGreen
    Number of pixels by which to expand the primary objects:10
    Regularization factor:0.05
    Discard secondary objects touching the border of the image?:No
    Discard the associated primary objects?:No
    Name the new primary objects:FilteredNuclei
    Fill holes in identified objects?:Yes
    Threshold setting version:12
    Threshold strategy:Global
    Thresholding method:Minimum Cross-Entropy
    Threshold smoothing scale:0
    Threshold correction factor:1
    Lower and upper bounds on threshold:0,1
    Manual threshold:0
    Select the measurement to threshold with:None
    Two-class or three-class thresholding?:Two classes
    Log transform before thresholding?:No
    Assign pixels in the middle intensity class to the foreground or the background?:Foreground
    Size of adaptive window:10
    Lower outlier fraction:0.05
    Upper outlier fraction:0.05
    Averaging method:Mean
    Variance method:Standard deviation
    # of deviations:2
    Thresholding method:Otsu

IdentifyTertiaryObjects:[module_num:4|svn_version:'Unknown'|variable_revision_number:3|show_window:True|notes:['Identify the cytoplasm by "subtracting" the nuclei objects from the cell objects.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Select the larger identified objects:Cells
    Select the smaller identified objects:Nuclei
    Name the tertiary objects to be identified:Cytoplasm
    Shrink smaller object prior to subtraction?:Yes

MeasureObjectSizeShape:[module_num:5|svn_version:'Unknown'|variable_revision_number:3|show_window:True|notes:['Measure morphological features from the cell, nuclei and cytoplasm objects.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Select object sets to measure:Cells, Nuclei, Cytoplasm
    Calculate the Zernike features?:Yes
    Calculate the advanced features?:No

MeasureObjectIntensity:[module_num:6|svn_version:'Unknown'|variable_revision_number:4|show_window:True|notes:['Measure intensity features from nuclei and cell objects against the DAPI image.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Select images to measure:OrigBlue
    Select objects to measure:Nuclei, Cells, Cytoplasm

MeasureTexture:[module_num:7|svn_version:'Unknown'|variable_revision_number:7|show_window:True|notes:['Measure texture features of the nuclei, cells and cytoplasm from the DAPI image.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Select images to measure:OrigBlue
    Select objects to measure:Nuclei, Cytoplasm, Cells
    Enter how many gray levels to measure the texture at:256
    Hidden:1
    Measure whole images or objects?:Both
    Texture scale to measure:3

MeasureObjectNeighbors:[module_num:8|svn_version:'Unknown'|variable_revision_number:3|show_window:True|notes:['Obtain the nuclei neighborhood measures, considering nuclei within 4 pixels in any direction as a neighbor.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Select objects to measure:Nuclei
    Select neighboring objects to measure:Nuclei
    Method to determine neighbors:Within a specified distance
    Neighbor distance:4
    Consider objects discarded for touching image border?:Yes
    Retain the image of objects colored by numbers of neighbors?:No
    Name the output image:Do not use
    Select colormap:Default
    Retain the image of objects colored by percent of touching pixels?:No
    Name the output image:PercentTouching
    Select colormap:Default

MeasureColocalization:[module_num:9|svn_version:'Unknown'|variable_revision_number:5|show_window:True|notes:['Measure the pixel intensity correlation between the pixels in the nuclei objects in the DAPI and FITC images, as well as the entire image.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Select images to measure:OrigBlue, OrigGreen
    Set threshold as percentage of maximum intensity for the images:15.0
    Select where to measure correlation:Both
    Select objects to measure:Nuclei
    Run all metrics?:Accurate
    Calculate correlation and slope metrics?:Yes
    Calculate the Manders coefficients?:Yes
    Calculate the Rank Weighted Colocalization coefficients?:Yes
    Calculate the Overlap coefficients?:Yes
    Calculate the Manders coefficients using Costes auto threshold?:Yes
    Method for Costes thresholding:Fast

MeasureImageIntensity:[module_num:10|svn_version:'Unknown'|variable_revision_number:4|show_window:True|notes:['Measure the image intensity from the DAPI image.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Select images to measure:OrigBlue
    Measure the intensity only from areas enclosed by objects?:No
    Select input object sets:
    Calculate custom percentiles:No
    Specify percentiles to measure:10,90

MeasureImageQuality:[module_num:11|svn_version:'Unknown'|variable_revision_number:6|show_window:True|notes:['Obtain some measurements for quality control purposes.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Calculate metrics for which images?:Select...
    Image count:3
    Scale count:1
    Threshold count:1
    Scale count:1
    Threshold count:1
    Scale count:1
    Threshold count:1
    Select the images to measure:OrigBlue
    Include the image rescaling value?:Yes
    Calculate blur metrics?:Yes
    Spatial scale for blur measurements:20
    Calculate saturation metrics?:Yes
    Calculate intensity metrics?:Yes
    Calculate thresholds?:Yes
    Use all thresholding methods?:No
    Select a thresholding method:Otsu
    Typical fraction of the image covered by objects:0.1
    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
    Select the images to measure:OrigGreen
    Include the image rescaling value?:Yes
    Calculate blur metrics?:Yes
    Spatial scale for blur measurements:20
    Calculate saturation metrics?:Yes
    Calculate intensity metrics?:Yes
    Calculate thresholds?:Yes
    Use all thresholding methods?:No
    Select a thresholding method:Otsu
    Typical fraction of the image covered by objects:0.1
    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
    Select the images to measure:OrigRed
    Include the image rescaling value?:Yes
    Calculate blur metrics?:Yes
    Spatial scale for blur measurements:20
    Calculate saturation metrics?:Yes
    Calculate intensity metrics?:Yes
    Calculate thresholds?:Yes
    Use all thresholding methods?:No
    Select a thresholding method:Otsu
    Typical fraction of the image covered by objects:0.1
    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

CalculateMath:[module_num:12|svn_version:'Unknown'|variable_revision_number:3|show_window:True|notes:['Compute a ratio of nuclei mean intensity to nuclear area for each nucleus.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Name the output measurement:Ratio
    Operation:Divide
    Select the numerator measurement type:Object
    Select the numerator objects:Nuclei
    Select the numerator measurement:Intensity_MeanIntensity_OrigBlue
    Multiply the above operand by:1.0
    Raise the power of above operand by:1.0
    Select the denominator measurement type:Object
    Select the denominator objects:Nuclei
    Select the denominator measurement:AreaShape_Area
    Multiply the above operand by:1.0
    Raise the power of above operand by:1.0
    Take log10 of result?:No
    Multiply the result by:1.0
    Raise the power of result by:1.0
    Add to the result:0
    How should the output value be rounded?:Not rounded
    Enter how many decimal places the value should be rounded to:0
    Constrain the result to a lower bound?:No
    Enter the lower bound:0
    Constrain the result to an upper bound?:No
    Enter the upper bound:1

ClassifyObjects:[module_num:13|svn_version:'Unknown'|variable_revision_number:4|show_window:True|notes:['Classify the nuclei on the basis of area. Divide the areas into 3 bins and give each bin a name.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Make classification decision based on:Single measurement
    Hidden:1
    Hidden:1
    Select the object to be classified:Nuclei
    Select the measurement to classify by:AreaShape_Area
    Select bin spacing:Evenly spaced bins
    Number of bins:3
    Lower threshold:350
    Use a bin for objects below the threshold?:No
    Upper threshold:700
    Use a bin for objects above the threshold?:No
    Enter the custom thresholds separating the values between bins:0,1
    Give each bin a name?:Yes
    Enter the bin names separated by commas:Small,Medium,Large
    Retain an image of the classified objects?:No
    Name the output image:Do not use
    Select a class:None
    Name the output objects:ClassifiedObjects
    Select the object name:Nuclei
    Select the first measurement:None
    Method to select the cutoff:Mean
    Enter the cutoff value:.5
    Select the second measurement:None
    Method to select the cutoff:Mean
    Enter the cutoff value:.5
    Use custom names for the bins?:No
    Enter the low-low bin name:LowLow
    Enter the low-high bin name:HighLow
    Enter the high-low bin name:LowHigh
    Enter the high-high bin name:HighHigh
    Retain an image of the classified objects?:No
    Enter the image name:ClassifiedNuclei
    Save classes as new object sets?:No
    Select the location of the classifier model file:Default Output Folder|None
    Rules or classifier file name:None
    Allow fuzzy feature matching?:No

ExportToSpreadsheet:[module_num:14|svn_version:'Unknown'|variable_revision_number:13|show_window:True|notes:['Export any measurements to a comma-delimited file (.csv). The measurements made for the nuclei, cell and cytoplasm objects will be saved to separate .csv files, in addition to the per-image .csv’s.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Select the column delimiter:Comma (",")
    Add image metadata columns to your object data file?:No
    Add image file and folder names to your object data file?:No
    Select the measurements to export:No
    Calculate the per-image mean values for object measurements?:Yes
    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|.
    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 measurement types?:No
    Press button to select measurements:None|None
    Representation of Nan/Inf:NaN
    Add a prefix to file names?:No
    Filename prefix:MyExpt_
    Overwrite existing files without warning?:Yes
    Data to export:Image
    Combine these object measurements with those of the previous object?:No
    File name:Image.csv
    Use the object name for the file name?:No
    Data to export:Nuclei
    Combine these object measurements with those of the previous object?:No
    File name:Nuclei.csv
    Use the object name for the file name?:No
    Data to export:Cells
    Combine these object measurements with those of the previous object?:No
    File name:Cells.csv
    Use the object name for the file name?:No
    Data to export:Cytoplasm
    Combine these object measurements with those of the previous object?:No
    File name:Cytoplasm.csv
    Use the object name for the file name?:No