TGlow_40X_farm_V2.cppipe

CellProfiler Pipeline: http://www.cellprofiler.org
Version:5
DateRevision:425
GitHash:
ModuleCount:28
HasImagePlaneDetails:False

Images:[module_num:1|svn_version:'Unknown'|variable_revision_number:2|show_window:False|notes:['To begin creating your project, use the Images module to compile a list of files and/or folders that you want to analyze. You can also specify a set of rules to include only the desired files in your selected folders.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    :
    Filter images?:Images only
    Select the rule criteria:and (extension does isimage) (directory doesnot containregexp "[\\\\/]\\.")

Metadata:[module_num:2|svn_version:'Unknown'|variable_revision_number:6|show_window:False|notes:['The Metadata module optionally allows you to extract information describing your images (i.e, metadata) which will be stored along with your measurements. This information can be contained in the file name and/or location, or in an external file.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Extract metadata?:Yes
    Metadata data type:Text
    Metadata types:{}
    Extraction method count:1
    Metadata extraction method:Extract from image file headers
    Metadata source:File name
    Regular expression to extract from file name:^(?P<Plate>.*)_(?P<Well>[A-P][0-9]{2})_s(?P<Site>[0-9])_w(?P<ChannelNumber>[0-9])
    Regular expression to extract from folder name:(?P<Date>[0-9]{4}_[0-9]{2}_[0-9]{2})$
    Extract metadata from:All images
    Select the filtering criteria:and (file does contain "")
    Metadata file location:Elsewhere...|
    Match file and image metadata:[]
    Use case insensitive matching?:No
    Metadata file name:None
    Does cached metadata exist?:Yes

NamesAndTypes:[module_num:3|svn_version:'Unknown'|variable_revision_number:8|show_window:False|notes:['The NamesAndTypes module allows you to assign a meaningful name to each image by which other modules will refer to it.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Assign a name to:Images matching rules
    Select the image type:Grayscale image
    Name to assign these images:DNA
    Match metadata:[]
    Image set matching method:Order
    Set intensity range from:Image metadata
    Assignments count:4
    Single images count:0
    Maximum intensity:255.0
    Process as 3D?:No
    Relative pixel spacing in X:1.0
    Relative pixel spacing in Y:1.0
    Relative pixel spacing in Z:1.0
    Select the rule criteria:and (metadata does T "3")
    Name to assign these images:DNA
    Name to assign these objects:Cell
    Select the image type:Grayscale image
    Set intensity range from:Image metadata
    Maximum intensity:255.0
    Select the rule criteria:and (metadata does T "0")
    Name to assign these images:CD25_Ki67
    Name to assign these objects:Cell
    Select the image type:Grayscale image
    Set intensity range from:Image metadata
    Maximum intensity:255.0
    Select the rule criteria:and (metadata does T "1")
    Name to assign these images:Actin
    Name to assign these objects:Cell
    Select the image type:Grayscale image
    Set intensity range from:Image metadata
    Maximum intensity:255.0
    Select the rule criteria:and (metadata does T "2")
    Name to assign these images:Mitochondria
    Name to assign these objects:Cell
    Select the image type:Grayscale image
    Set intensity range from:Image metadata
    Maximum intensity:255.0

Groups:[module_num:4|svn_version:'Unknown'|variable_revision_number:2|show_window:False|notes:['The Groups module optionally allows you to split your list of images into image subsets (groups) which will be processed independently of each other. Examples of groupings include screening batches, microtiter plates, time-lapse movies, etc.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Do you want to group your images?:No
    grouping metadata count:1
    Metadata category:None

MeasureImageQuality:[module_num:5|svn_version:'Unknown'|variable_revision_number:6|show_window:False|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Calculate metrics for which images?:All loaded images
    Image count:1
    Scale count:1
    Threshold count:1
    Select the images to measure:Actin, CD25_Ki67, DNA, Mitochondria
    Include the image rescaling value?:Yes
    Calculate blur metrics?:No
    Spatial scale for blur measurements:20
    Calculate saturation metrics?:Yes
    Calculate intensity metrics?:Yes
    Calculate thresholds?:No
    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

ImageMath:[module_num:6|svn_version:'Unknown'|variable_revision_number:5|show_window:False|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Operation:Add
    Raise the power of the result by:1.0
    Multiply the result by:1.0
    Add to result:0.0
    Set values less than 0 equal to 0?:Yes
    Set values greater than 1 equal to 1?:Yes
    Replace invalid values with 0?:Yes
    Ignore the image masks?:Yes
    Name the output image:Ki67_plus_MC
    Image or measurement?:Image
    Select the first image:Mitochondria
    Multiply the first image by:5
    Measurement:
    Image or measurement?:Image
    Select the second image:CD25_Ki67
    Multiply the second image by:10
    Measurement:
    Image or measurement?:Image
    Select the third image:Actin
    Multiply the third image by:20
    Measurement:
    Image or measurement?:Image
    Select the fourth image:DNA
    Multiply the fourth image by:1.0
    Measurement:

IdentifyPrimaryObjects:[module_num:7|svn_version:'Unknown'|variable_revision_number:15|show_window:False|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Select the input image:DNA
    Name the primary objects to be identified:Nuclei
    Typical diameter of objects, in pixel units (Min,Max):10,80
    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:20
    Suppress local maxima that are closer than this minimum allowed distance:20
    Speed up by using lower-resolution image to find local maxima?:No
    Fill holes in identified objects?:Never
    Automatically calculate size of smoothing filter for declumping?:No
    Automatically calculate minimum allowed distance between local maxima?:No
    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:Otsu
    Threshold smoothing scale:0
    Threshold correction factor:1.0
    Lower and upper bounds on threshold:0.0,1.0
    Manual threshold:0.0
    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:50
    Lower outlier fraction:0.05
    Upper outlier fraction:0.05
    Averaging method:Mean
    Variance method:Standard deviation
    # of deviations:2.0
    Thresholding method:Minimum Cross-Entropy

IdentifyPrimaryObjects:[module_num:8|svn_version:'Unknown'|variable_revision_number:15|show_window:False|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Select the input image:CD25_Ki67
    Name the primary objects to be identified:Ki67
    Typical diameter of objects, in pixel units (Min,Max):5,100
    Discard objects outside the diameter range?:Yes
    Discard objects touching the border of the image?:Yes
    Method to distinguish clumped objects:None
    Method to draw dividing lines between clumped objects:Intensity
    Size of smoothing filter:20
    Suppress local maxima that are closer than this minimum allowed distance:20
    Speed up by using lower-resolution image to find local maxima?:No
    Fill holes in identified objects?:Never
    Automatically calculate size of smoothing filter for declumping?:No
    Automatically calculate minimum allowed distance between local maxima?:No
    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:Robust Background
    Threshold smoothing scale:1.3488
    Threshold correction factor:1.0
    Lower and upper bounds on threshold:0.001,1.0
    Manual threshold:0.0
    Select the measurement to threshold with:None
    Two-class or three-class thresholding?:Two classes
    Log transform before thresholding?:Yes
    Assign pixels in the middle intensity class to the foreground or the background?:Foreground
    Size of adaptive window:50
    Lower outlier fraction:0.05
    Upper outlier fraction:0.05
    Averaging method:Mean
    Variance method:Standard deviation
    # of deviations:2.0
    Thresholding method:Minimum Cross-Entropy

IdentifyPrimaryObjects:[module_num:9|svn_version:'Unknown'|variable_revision_number:15|show_window:False|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Select the input image:Actin
    Name the primary objects to be identified:actin
    Typical diameter of objects, in pixel units (Min,Max):10,100
    Discard objects outside the diameter range?:No
    Discard objects touching the border of the image?:Yes
    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:7.0
    Speed up by using lower-resolution image to find local maxima?:Yes
    Fill holes in identified objects?:Never
    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:Adaptive
    Thresholding method:Minimum Cross-Entropy
    Threshold smoothing scale:1.3488
    Threshold correction factor:1.0
    Lower and upper bounds on threshold:0.004,1.0
    Manual threshold:0.0
    Select the measurement to threshold with:None
    Two-class or three-class thresholding?:Two classes
    Log transform before thresholding?:Yes
    Assign pixels in the middle intensity class to the foreground or the background?:Foreground
    Size of adaptive window:100
    Lower outlier fraction:0.05
    Upper outlier fraction:0.05
    Averaging method:Mean
    Variance method:Standard deviation
    # of deviations:2.0
    Thresholding method:Robust Background

IdentifyPrimaryObjects:[module_num:10|svn_version:'Unknown'|variable_revision_number:15|show_window:False|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Select the input image:Mitochondria
    Name the primary objects to be identified:MC
    Typical diameter of objects, in pixel units (Min,Max):20,100
    Discard objects outside the diameter range?:No
    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:7.0
    Speed up by using lower-resolution image to find local maxima?:Yes
    Fill holes in identified objects?:Never
    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:Otsu
    Threshold smoothing scale:1.3488
    Threshold correction factor:1.0
    Lower and upper bounds on threshold:0,1.0
    Manual threshold:0.0
    Select the measurement to threshold with:None
    Two-class or three-class thresholding?:Two classes
    Log transform before thresholding?:Yes
    Assign pixels in the middle intensity class to the foreground or the background?:Foreground
    Size of adaptive window:50
    Lower outlier fraction:0.05
    Upper outlier fraction:0.05
    Averaging method:Mean
    Variance method:Standard deviation
    # of deviations:2.0
    Thresholding method:Minimum Cross-Entropy

IdentifySecondaryObjects:[module_num:11|svn_version:'Unknown'|variable_revision_number:10|show_window:False|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Select the input objects:Nuclei
    Name the objects to be identified:cell
    Select the method to identify the secondary objects:Propagation
    Select the input image:Ki67_plus_MC
    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:Adaptive
    Thresholding method:Minimum Cross-Entropy
    Threshold smoothing scale:0.0
    Threshold correction factor:1.0
    Lower and upper bounds on threshold:0.0,1.0
    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?:Foreground
    Size of adaptive window:50
    Lower outlier fraction:0.05
    Upper outlier fraction:0.05
    Averaging method:Mean
    Variance method:Standard deviation
    # of deviations:2.0
    Thresholding method:Otsu

RelateObjects:[module_num:12|svn_version:'Unknown'|variable_revision_number:5|show_window:False|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Parent objects:cell
    Child objects:Ki67
    Calculate child-parent distances?:None
    Calculate per-parent means for all child measurements?:Yes
    Calculate distances to other parents?:No
    Do you want to save the children with parents as a new object set?:No
    Name the output object:CellwithMC
    Parent name:None

RelateObjects:[module_num:13|svn_version:'Unknown'|variable_revision_number:5|show_window:False|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Parent objects:cell
    Child objects:MC
    Calculate child-parent distances?:None
    Calculate per-parent means for all child measurements?:Yes
    Calculate distances to other parents?:No
    Do you want to save the children with parents as a new object set?:No
    Name the output object:CellwithMCwithKi67
    Parent name:None

RelateObjects:[module_num:14|svn_version:'Unknown'|variable_revision_number:5|show_window:False|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Parent objects:cell
    Child objects:actin
    Calculate child-parent distances?:None
    Calculate per-parent means for all child measurements?:Yes
    Calculate distances to other parents?:No
    Do you want to save the children with parents as a new object set?:No
    Name the output object:CellwithMCwithKi67
    Parent name:None

RelateObjects:[module_num:15|svn_version:'Unknown'|variable_revision_number:5|show_window:False|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Parent objects:cell
    Child objects:Nuclei
    Calculate child-parent distances?:None
    Calculate per-parent means for all child measurements?:Yes
    Calculate distances to other parents?:No
    Do you want to save the children with parents as a new object set?:No
    Name the output object:CellwithMCwithKi67
    Parent name:None

MeasureImageIntensity:[module_num:16|svn_version:'Unknown'|variable_revision_number:4|show_window:False|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Select images to measure:DNA
    Measure the intensity only from areas enclosed by objects?:Yes
    Select input object sets:cell
    Calculate custom percentiles:Yes
    Specify percentiles to measure:10,90

MeasureImageIntensity:[module_num:17|svn_version:'Unknown'|variable_revision_number:4|show_window:False|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Select images to measure:Mitochondria
    Measure the intensity only from areas enclosed by objects?:Yes
    Select input object sets:cell
    Calculate custom percentiles:Yes
    Specify percentiles to measure:10,90

MeasureImageIntensity:[module_num:18|svn_version:'Unknown'|variable_revision_number:4|show_window:False|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Select images to measure:CD25_Ki67
    Measure the intensity only from areas enclosed by objects?:Yes
    Select input object sets:cell
    Calculate custom percentiles:Yes
    Specify percentiles to measure:10,90

MeasureObjectIntensity:[module_num:19|svn_version:'Unknown'|variable_revision_number:4|show_window:False|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Select images to measure:Mitochondria
    Select objects to measure:cell

MeasureObjectIntensity:[module_num:20|svn_version:'Unknown'|variable_revision_number:4|show_window:False|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Select images to measure:CD25_Ki67
    Select objects to measure:cell

MeasureObjectIntensity:[module_num:21|svn_version:'Unknown'|variable_revision_number:4|show_window:False|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Select images to measure:Actin
    Select objects to measure:cell

MeasureObjectIntensity:[module_num:22|svn_version:'Unknown'|variable_revision_number:4|show_window:False|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Select images to measure:DNA
    Select objects to measure:cell

MeasureObjectSizeShape:[module_num:23|svn_version:'Unknown'|variable_revision_number:3|show_window:False|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Select object sets to measure:MC, cell
    Calculate the Zernike features?:Yes
    Calculate the advanced features?:Yes

MeasureColocalization:[module_num:24|svn_version:'Unknown'|variable_revision_number:5|show_window:False|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Select images to measure:DNA, Mitochondria
    Set threshold as percentage of maximum intensity for the images:15.0
    Select where to measure correlation:Within objects
    Select objects to measure:MC, Nuclei
    Run all metrics?:No
    Calculate correlation and slope metrics?:No
    Calculate the Manders coefficients?:No
    Calculate the Rank Weighted Colocalization coefficients?:No
    Calculate the Overlap coefficients?:Yes
    Calculate the Manders coefficients using Costes auto threshold?:No
    Method for Costes thresholding:Faster

MeasureTexture:[module_num:25|svn_version:'Unknown'|variable_revision_number:7|show_window:False|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Select images to measure:DNA
    Select objects to measure:Nuclei
    Enter how many gray levels to measure the texture at:256
    Hidden:1
    Measure whole images or objects?:Objects
    Texture scale to measure:2

MeasureTexture:[module_num:26|svn_version:'Unknown'|variable_revision_number:7|show_window:False|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Select images to measure:Mitochondria
    Select objects to measure:MC
    Enter how many gray levels to measure the texture at:256
    Hidden:1
    Measure whole images or objects?:Objects
    Texture scale to measure:2

MeasureGranularity:[module_num:27|svn_version:'Unknown'|variable_revision_number:4|show_window:False|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Select images to measure:Mitochondria
    Measure within objects?:Yes
    Select objects to measure:cell
    Subsampling factor for granularity measurements:0.25
    Subsampling factor for background reduction:0.25
    Radius of structuring element:1
    Range of the granular spectrum:6

ExportToSpreadsheet:[module_num:28|svn_version:'Unknown'|variable_revision_number:13|show_window:False|notes:[]|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?:Yes
    Select the 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|Desktop/Julie/20230728_TCA/results_test_farm
    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?:Yes
    Press button to select measurements:Image|Granularity_3_Mitochondria,Image|Granularity_9_Mitochondria,Image|Granularity_5_Mitochondria,Image|Granularity_8_Mitochondria,Image|Granularity_2_Mitochondria,Image|Granularity_14_Mitochondria,Image|Granularity_12_Mitochondria,Image|Granularity_1_Mitochondria,Image|Granularity_7_Mitochondria,Image|Granularity_6_Mitochondria,Image|Granularity_10_Mitochondria,Image|Granularity_4_Mitochondria,Image|Granularity_16_Mitochondria,Image|Granularity_13_Mitochondria,Image|Granularity_11_Mitochondria,Image|Granularity_15_Mitochondria,Image|Intensity_Percentile_10_Mitochondria_MC,Image|Intensity_Percentile_10_DNA_Nuclei,Image|Intensity_Percentile_10_CD25_Ki67_Ki67,Image|Intensity_Percentile_90_DNA_Nuclei,Image|Intensity_Percentile_90_Mitochondria_MC,Image|Intensity_Percentile_90_CD25_Ki67_Ki67,Image|Intensity_TotalIntensity_DNA_Nuclei,Image|Intensity_TotalIntensity_Mitochondria_MC,Image|Intensity_TotalIntensity_CD25_Ki67_Ki67,Image|Intensity_UpperQuartileIntensity_DNA_Nuclei,Image|Intensity_UpperQuartileIntensity_Mitochondria_MC,Image|Intensity_UpperQuartileIntensity_CD25_Ki67_Ki67,Image|Intensity_MeanIntensity_Mitochondria_MC,Image|Intensity_MeanIntensity_DNA_Nuclei,Image|Intensity_MeanIntensity_CD25_Ki67_Ki67,Image|Intensity_TotalArea_DNA_Nuclei,Image|Intensity_TotalArea_CD25_Ki67_Ki67,Image|Intensity_TotalArea_Mitochondria_MC,Image|Intensity_LowerQuartileIntensity_Mitochondria_MC,Image|Intensity_LowerQuartileIntensity_CD25_Ki67_Ki67,Image|Intensity_LowerQuartileIntensity_DNA_Nuclei,Image|Intensity_MedianIntensity_DNA_Nuclei,Image|Intensity_MedianIntensity_Mitochondria_MC,Image|Intensity_MedianIntensity_CD25_Ki67_Ki67,Image|Intensity_MADIntensity_DNA_Nuclei,Image|Intensity_MADIntensity_CD25_Ki67_Ki67,Image|Intensity_MADIntensity_Mitochondria_MC,Image|Intensity_StdIntensity_DNA_Nuclei,Image|Intensity_StdIntensity_Mitochondria_MC,Image|Intensity_StdIntensity_CD25_Ki67_Ki67,Image|Intensity_MinIntensity_CD25_Ki67_Ki67,Image|Intensity_MinIntensity_DNA_Nuclei,Image|Intensity_MinIntensity_Mitochondria_MC,Image|Intensity_MaxIntensity_CD25_Ki67_Ki67,Image|Intensity_MaxIntensity_Mitochondria_MC,Image|Intensity_MaxIntensity_DNA_Nuclei,Image|Intensity_PercentMaximal_DNA_Nuclei,Image|Intensity_PercentMaximal_Mitochondria_MC,Image|Intensity_PercentMaximal_CD25_Ki67_Ki67,Image|Metadata_SizeX,Image|Metadata_FileLocation,Image|Metadata_SizeC,Image|Metadata_Series,Image|Metadata_SizeT,Image|Metadata_Plate,Image|Metadata_T,Image|Metadata_ColorFormat,Image|Metadata_Z,Image|Metadata_SizeZ,Image|Metadata_Well,Image|Metadata_ChannelName,Image|Metadata_Frame,Image|Metadata_Site,Image|Metadata_C,Image|Metadata_SizeY,Image|ModuleError_02Metadata,Image|ModuleError_15RelateObjects,Image|ModuleError_10IdentifyPrimaryObjects,Image|ModuleError_08IdentifyPrimaryObjects,Image|ModuleError_04Groups,Image|ModuleError_24MeasureObjectNeighbors,Image|ModuleError_32MeasureTexture,Image|ModuleError_19MeasureImageIntensity,Image|ModuleError_17RelateObjects,Image|ModuleError_21MeasureObjectIntensity,Image|ModuleError_03NamesAndTypes,Image|ModuleError_30MeasureObjectSizeShape,Image|ModuleError_01Images,Image|ModuleError_29MeasureGranularity,Image|ModuleError_13IdentifySecondaryObjects,Image|ModuleError_31MeasureObjectSizeShape,Image|ModuleError_23MeasureColocalization,Image|ModuleError_18MeasureImageIntensity,Image|ModuleError_09IdentifyPrimaryObjects,Image|ModuleError_16RelateObjects,Image|ModuleError_22MeasureObjectIntensity,Image|ModuleError_06ImageMath,Image|ModuleError_20MeasureImageIntensity,Image|ModuleError_14RelateObjects,Image|ModuleError_07IdentifyPrimaryObjects,Image|MD5Digest_CD25_Ki67,Image|MD5Digest_DNA,Image|MD5Digest_Actin,Image|MD5Digest_Mitochondria,Image|ExecutionTime_32MeasureTexture,Image|ExecutionTime_24MeasureObjectNeighbors,Image|ExecutionTime_15RelateObjects,Image|ExecutionTime_09IdentifyPrimaryObjects,Image|ExecutionTime_08IdentifyPrimaryObjects,Image|ExecutionTime_10IdentifyPrimaryObjects,Image|ExecutionTime_02Metadata,Image|ExecutionTime_19MeasureImageIntensity,Image|ExecutionTime_13IdentifySecondaryObjects,Image|ExecutionTime_20MeasureImageIntensity,Image|ExecutionTime_30MeasureObjectSizeShape,Image|ExecutionTime_04Groups,Image|ExecutionTime_03NamesAndTypes,Image|ExecutionTime_23MeasureColocalization,Image|ExecutionTime_18MeasureImageIntensity,Image|ExecutionTime_22MeasureObjectIntensity,Image|ExecutionTime_16RelateObjects,Image|ExecutionTime_07IdentifyPrimaryObjects,Image|ExecutionTime_29MeasureGranularity,Image|ExecutionTime_01Images,Image|ExecutionTime_06ImageMath,Image|ExecutionTime_31MeasureObjectSizeShape,Image|ExecutionTime_14RelateObjects,Image|ExecutionTime_21MeasureObjectIntensity,Image|ExecutionTime_17RelateObjects,Image|Threshold_OrigThreshold_Ki67,Image|Threshold_OrigThreshold_Nuclei,Image|Threshold_OrigThreshold_cell2,Image|Threshold_OrigThreshold_MC,Image|Threshold_OrigThreshold_actin,Image|Threshold_FinalThreshold_Nuclei,Image|Threshold_FinalThreshold_MC,Image|Threshold_FinalThreshold_cell2,Image|Threshold_FinalThreshold_Ki67,Image|Threshold_FinalThreshold_actin,Image|Threshold_WeightedVariance_Ki67,Image|Threshold_WeightedVariance_MC,Image|Threshold_WeightedVariance_Nuclei,Image|Threshold_WeightedVariance_actin,Image|Threshold_WeightedVariance_cell2,Image|Threshold_SumOfEntropies_actin,Image|Threshold_SumOfEntropies_Ki67,Image|Threshold_SumOfEntropies_MC,Image|Threshold_SumOfEntropies_Nuclei,Image|Threshold_SumOfEntropies_cell2,Image|Threshold_GuideThreshold_actin,Image|PathName_Mitochondria,Image|PathName_CD25_Ki67,Image|PathName_Actin,Image|PathName_DNA,Image|FileName_Mitochondria,Image|FileName_DNA,Image|FileName_CD25_Ki67,Image|FileName_Actin,Image|URL_Mitochondria,Image|URL_DNA,Image|URL_Actin,Image|URL_CD25_Ki67,Image|Series_DNA,Image|Series_CD25_Ki67,Image|Series_Mitochondria,Image|Series_Actin,Image|Scaling_DNA,Image|Scaling_Mitochondria,Image|Scaling_Actin,Image|Scaling_CD25_Ki67,Image|Width_Mitochondria,Image|Width_Actin,Image|Width_DNA,Image|Width_CD25_Ki67,Image|Frame_Mitochondria,Image|Frame_DNA,Image|Frame_CD25_Ki67,Image|Frame_Actin,Image|Group_Index,Image|Group_Number,Image|Group_Length,Image|Count_MC,Image|Count_actin,Image|Count_cell2,Image|Count_Nuclei,Image|Count_Ki67,Image|Height_Actin,Image|Height_DNA,Image|Height_CD25_Ki67,Image|Height_Mitochondria,cell2|Location_Center_Z,cell2|Location_Center_Y,cell2|Location_Center_X,cell2|Location_MaxIntensity_Y_Mitochondria,cell2|Location_MaxIntensity_Y_CD25_Ki67,cell2|Location_MaxIntensity_Z_CD25_Ki67,cell2|Location_MaxIntensity_Z_Mitochondria,cell2|Location_MaxIntensity_X_CD25_Ki67,cell2|Location_MaxIntensity_X_Mitochondria,cell2|Location_CenterMassIntensity_Y_CD25_Ki67,cell2|Location_CenterMassIntensity_Y_Mitochondria,cell2|Location_CenterMassIntensity_Z_CD25_Ki67,cell2|Location_CenterMassIntensity_Z_Mitochondria,cell2|Location_CenterMassIntensity_X_Mitochondria,cell2|Location_CenterMassIntensity_X_CD25_Ki67,cell2|Intensity_StdIntensityEdge_CD25_Ki67,cell2|Intensity_StdIntensityEdge_Mitochondria,cell2|Intensity_MinIntensityEdge_CD25_Ki67,cell2|Intensity_MinIntensityEdge_Mitochondria,cell2|Intensity_MADIntensity_Mitochondria,cell2|Intensity_MADIntensity_CD25_Ki67,cell2|Intensity_MedianIntensity_CD25_Ki67,cell2|Intensity_MedianIntensity_Mitochondria,cell2|Intensity_IntegratedIntensity_Mitochondria,cell2|Intensity_IntegratedIntensity_CD25_Ki67,cell2|Intensity_MassDisplacement_CD25_Ki67,cell2|Intensity_MassDisplacement_Mitochondria,cell2|Intensity_LowerQuartileIntensity_Mitochondria,cell2|Intensity_LowerQuartileIntensity_CD25_Ki67,cell2|Intensity_MeanIntensityEdge_CD25_Ki67,cell2|Intensity_MeanIntensityEdge_Mitochondria,cell2|Intensity_UpperQuartileIntensity_CD25_Ki67,cell2|Intensity_UpperQuartileIntensity_Mitochondria,cell2|Intensity_MinIntensity_CD25_Ki67,cell2|Intensity_MinIntensity_Mitochondria,cell2|Intensity_MaxIntensityEdge_Mitochondria,cell2|Intensity_MaxIntensityEdge_CD25_Ki67,cell2|Intensity_StdIntensity_Mitochondria,cell2|Intensity_StdIntensity_CD25_Ki67,cell2|Intensity_MaxIntensity_Mitochondria,cell2|Intensity_MaxIntensity_CD25_Ki67,cell2|Intensity_IntegratedIntensityEdge_Mitochondria,cell2|Intensity_IntegratedIntensityEdge_CD25_Ki67,cell2|Intensity_MeanIntensity_CD25_Ki67,cell2|Intensity_MeanIntensity_Mitochondria,cell2|Mean_actin_Number_Object_Number,cell2|Mean_actin_Location_Center_Y,cell2|Mean_actin_Location_Center_Z,cell2|Mean_actin_Location_Center_X,cell2|Mean_Ki67_Number_Object_Number,cell2|Mean_Ki67_Location_Center_Z,cell2|Mean_Ki67_Location_Center_Y,cell2|Mean_Ki67_Location_Center_X,cell2|Mean_Nuclei_Children_cell2_Count,cell2|Mean_Nuclei_Location_Center_Z,cell2|Mean_Nuclei_Location_Center_Y,cell2|Mean_Nuclei_Location_Center_X,cell2|Mean_Nuclei_Number_Object_Number,cell2|Mean_MC_Location_Center_X,cell2|Mean_MC_Location_Center_Z,cell2|Mean_MC_Location_Center_Y,cell2|Mean_MC_Number_Object_Number,cell2|Children_Ki67_Count,cell2|Children_Nuclei_Count,cell2|Children_actin_Count,cell2|Children_MC_Count,cell2|Parent_Nuclei,cell2|Number_Object_Number,MC|Correlation_K_CD25_Ki67_Mitochondria,MC|Correlation_K_Mitochondria_CD25_Ki67,MC|Correlation_Overlap_CD25_Ki67_Mitochondria,MC|Parent_cell2,MC|Location_Center_Y,MC|Location_Center_X,MC|Location_Center_Z,MC|Number_Object_Number,Ki67|Correlation_K_Mitochondria_CD25_Ki67,Ki67|Correlation_K_CD25_Ki67_Mitochondria,Ki67|Correlation_Overlap_CD25_Ki67_Mitochondria,Ki67|Location_Center_X,Ki67|Location_Center_Z,Ki67|Location_Center_Y,Ki67|Number_Object_Number,Ki67|Parent_cell2,actin|Location_Center_Y,actin|Location_Center_X,actin|Location_Center_Z,actin|Parent_cell2,actin|Number_Object_Number,Nuclei|Location_Center_Z,Nuclei|Location_Center_X,Nuclei|Location_Center_Y,Nuclei|Neighbors_FirstClosestDistance_5,Nuclei|Neighbors_PercentTouching_5,Nuclei|Neighbors_FirstClosestObjectNumber_5,Nuclei|Neighbors_SecondClosestObjectNumber_5,Nuclei|Neighbors_NumberOfNeighbors_5,Nuclei|Neighbors_AngleBetweenNeighbors_5,Nuclei|Neighbors_SecondClosestDistance_5,Nuclei|Parent_cell2,Nuclei|Number_Object_Number,Nuclei|Children_cell2_Count,Experiment|CellProfiler_Version,Experiment|Modification_Timestamp,Experiment|Run_Timestamp,Experiment|Metadata_GroupingTags,Experiment|Pipeline_Pipeline
    Representation of Nan/Inf:NaN
    Add a prefix to file names?:Yes
    Filename prefix:MyExpt_
    Overwrite existing files without warning?:No
    Data to export:Image
    Combine these object measurements with those of the previous object?:No
    File name:DATA.csv
    Use the object name for the file name?:Yes
    Data to export:Experiment
    Combine these object measurements with those of the previous object?:No
    File name:DATA.csv
    Use the object name for the file name?:Yes
    Data to export:Object relationships
    Combine these object measurements with those of the previous object?:No
    File name:DATA.csv
    Use the object name for the file name?:Yes
    Data to export:Nuclei
    Combine these object measurements with those of the previous object?:No
    File name:DATA.csv
    Use the object name for the file name?:Yes
    Data to export:cell2
    Combine these object measurements with those of the previous object?:No
    File name:DATA.csv
    Use the object name for the file name?:Yes