analysis.cppipe

CellProfiler Pipeline: http://www.cellprofiler.org
Version:5
DateRevision:428
GitHash:
ModuleCount:21
HasImagePlaneDetails:False

LoadData:[module_num:1|svn_version:'Unknown'|variable_revision_number:6|show_window:False|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Input data file location:Default Input Folder|pediatric_cancer_atlas_profiling/2.feature_extraction/loaddata_csvs
    Name of the file:
    Load images based on this data?:Yes
    Base image location:None|
    Process just a range of rows?:No
    Rows to process:1,100000
    Group images by metadata?:Yes
    Select metadata tags for grouping:Plate
    Rescale intensities?:Yes

MeasureImageQuality:[module_num:2|svn_version:'Unknown'|variable_revision_number:6|show_window:False|notes:['Calculate image quality metrics to then flag and not process images with IC and further.']|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:
    Include the image rescaling value?:No
    Calculate blur metrics?:Yes
    Spatial scale for blur measurements:20
    Calculate saturation metrics?:Yes
    Calculate intensity metrics?:No
    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

FlagImage:[module_num:3|svn_version:'Unknown'|variable_revision_number:5|show_window:False|notes:["Flag and prevent any image set from being processes if it doesn't pass any of the poor quality QC thresholds for either blur or saturation."]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Hidden:1
    Hidden:10
    Name the flag's category:Blur_and_Saturation
    Name the flag:QCFlag
    How should measurements be linked?:Flag if any fail
    Skip image set if flagged?:Yes
    Flag is based on:Whole-image measurement
    Select the object to be used for flagging:None
    Which measurement?:ImageQuality_PowerLogLogSlope_OrigDNA
    Flag images based on low values?:Yes
    Minimum value:-2.7976730166487322
    Flag images based on high values?:Yes
    Maximum value:-1.1262448982947686
    Rules file location:Elsewhere...|
    Rules file name:rules.txt
    Class number:
    Allow fuzzy feature matching?:No
    Flag is based on:Whole-image measurement
    Select the object to be used for flagging:None
    Which measurement?:ImageQuality_PowerLogLogSlope_OrigAGP
    Flag images based on low values?:Yes
    Minimum value:-2.7976730166487322
    Flag images based on high values?:Yes
    Maximum value:-1.1262448982947686
    Rules file location:Elsewhere...|
    Rules file name:rules.txt
    Class number:
    Allow fuzzy feature matching?:No
    Flag is based on:Whole-image measurement
    Select the object to be used for flagging:None
    Which measurement?:ImageQuality_PowerLogLogSlope_OrigER
    Flag images based on low values?:Yes
    Minimum value:-2.7976730166487322
    Flag images based on high values?:Yes
    Maximum value:-1.1262448982947686
    Rules file location:Elsewhere...|
    Rules file name:rules.txt
    Class number:
    Allow fuzzy feature matching?:No
    Flag is based on:Whole-image measurement
    Select the object to be used for flagging:None
    Which measurement?:ImageQuality_PowerLogLogSlope_OrigMito
    Flag images based on low values?:Yes
    Minimum value:-2.7976730166487322
    Flag images based on high values?:Yes
    Maximum value:-1.1262448982947686
    Rules file location:Elsewhere...|
    Rules file name:rules.txt
    Class number:
    Allow fuzzy feature matching?:No
    Flag is based on:Whole-image measurement
    Select the object to be used for flagging:None
    Which measurement?:ImageQuality_PowerLogLogSlope_OrigRNA
    Flag images based on low values?:Yes
    Minimum value:-2.7976730166487322
    Flag images based on high values?:Yes
    Maximum value:-1.1262448982947686
    Rules file location:Elsewhere...|
    Rules file name:rules.txt
    Class number:
    Allow fuzzy feature matching?:No
    Flag is based on:Whole-image measurement
    Select the object to be used for flagging:None
    Which measurement?:ImageQuality_PercentMaximal_OrigDNA
    Flag images based on low values?:No
    Minimum value:0.0
    Flag images based on high values?:Yes
    Maximum value:4.275261792593619
    Rules file location:Elsewhere...|
    Rules file name:rules.txt
    Class number:
    Allow fuzzy feature matching?:No
    Flag is based on:Whole-image measurement
    Select the object to be used for flagging:None
    Which measurement?:ImageQuality_PercentMaximal_OrigAGP
    Flag images based on low values?:No
    Minimum value:0.0
    Flag images based on high values?:Yes
    Maximum value:4.275261792593619
    Rules file location:Elsewhere...|
    Rules file name:rules.txt
    Class number:
    Allow fuzzy feature matching?:No
    Flag is based on:Whole-image measurement
    Select the object to be used for flagging:None
    Which measurement?:ImageQuality_PercentMaximal_OrigER
    Flag images based on low values?:No
    Minimum value:0.0
    Flag images based on high values?:Yes
    Maximum value:4.275261792593619
    Rules file location:Elsewhere...|
    Rules file name:rules.txt
    Class number:
    Allow fuzzy feature matching?:No
    Flag is based on:Whole-image measurement
    Select the object to be used for flagging:None
    Which measurement?:ImageQuality_PercentMaximal_OrigMito
    Flag images based on low values?:No
    Minimum value:0.0
    Flag images based on high values?:Yes
    Maximum value:4.275261792593619
    Rules file location:Elsewhere...|
    Rules file name:rules.txt
    Class number:
    Allow fuzzy feature matching?:No
    Flag is based on:Whole-image measurement
    Select the object to be used for flagging:None
    Which measurement?:ImageQuality_PercentMaximal_OrigRNA
    Flag images based on low values?:No
    Minimum value:0.0
    Flag images based on high values?:Yes
    Maximum value:4.275261792593619
    Rules file location:Elsewhere...|
    Rules file name:rules.txt
    Class number:
    Allow fuzzy feature matching?:No
    Ignore flag skips on last cycle?:No

CorrectIlluminationApply:[module_num:4|svn_version:'Unknown'|variable_revision_number:5|show_window:False|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Select the input image:OrigDNA
    Name the output image:CorrDNA
    Select the illumination function:IllumDNA
    Select how the illumination function is applied:Subtract
    Select the input image:OrigAGP
    Name the output image:CorrAGP
    Select the illumination function:IllumAGP
    Select how the illumination function is applied:Subtract
    Select the input image:OrigER
    Name the output image:CorrER
    Select the illumination function:IllumAGP
    Select how the illumination function is applied:Subtract
    Select the input image:OrigMito
    Name the output image:CorrMito
    Select the illumination function:IllumMito
    Select how the illumination function is applied:Subtract
    Select the input image:OrigRNA
    Name the output image:CorrRNA
    Select the illumination function:IllumRNA
    Select how the illumination function is applied:Subtract
    Select the input image:OrigBrightfield
    Name the output image:CorrBrightfield
    Select the illumination function:IllumBrightfield
    Select how the illumination function is applied:Divide
    Set output image values less than 0 equal to 0?:Yes
    Set output image values greater than 1 equal to 1?:Yes

IdentifyPrimaryObjects:[module_num:5|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:CorrDNA
    Name the primary objects to be identified:Nuclei
    Typical diameter of objects, in pixel units (Min,Max):10,60
    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:7.0
    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:0.0,1.0
    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

IdentifySecondaryObjects:[module_num:6|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:Cells
    Select the method to identify the secondary objects:Propagation
    Select the input image:CorrAGP
    Number of pixels by which to expand the primary objects:10
    Regularization factor:0.05
    Discard secondary objects touching the border of the image?:Yes
    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:1.0
    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

IdentifyTertiaryObjects:[module_num:7|svn_version:'Unknown'|variable_revision_number:3|show_window:False|notes:[]|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

MeasureColocalization:[module_num:8|svn_version:'Unknown'|variable_revision_number:5|show_window:False|notes:['Measure colocalization/correlation across objects and whole images across all channels.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Select images to measure:CorrAGP, CorrBrightfield, CorrDNA, CorrER, CorrMito, CorrRNA
    Set threshold as percentage of maximum intensity for the images:15.0
    Select where to measure correlation:Both
    Select objects to measure:Cells, Cytoplasm, Nuclei
    Run all metrics?:Yes
    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:Faster

MeasureGranularity:[module_num:9|svn_version:'Unknown'|variable_revision_number:4|show_window:False|notes:['Measure granularity across objects and whole images across all channels.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Select images to measure:CorrAGP, CorrBrightfield, CorrDNA, CorrER, CorrMito, CorrRNA
    Measure within objects?:Yes
    Select objects to measure:Cells, Cytoplasm, Nuclei
    Subsampling factor for granularity measurements:0.25
    Subsampling factor for background reduction:0.25
    Radius of structuring element:10
    Range of the granular spectrum:16

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

MeasureObjectIntensity:[module_num:11|svn_version:'Unknown'|variable_revision_number:4|show_window:False|notes:['Measure object intensity across all channels.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Select images to measure:CorrAGP, CorrBrightfield, CorrDNA, CorrER, CorrMito, CorrRNA
    Select objects to measure:Cells, Cytoplasm, Nuclei

MeasureObjectIntensityDistribution:[module_num:12|svn_version:'Unknown'|variable_revision_number:6|show_window:False|notes:['Measure object radial distribution for magnitudes only with default parameters.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Select images to measure:CorrAGP, CorrBrightfield, CorrDNA, CorrER, CorrMito, CorrRNA
    Hidden:3
    Hidden:1
    Hidden:0
    Calculate intensity Zernikes?:Magnitudes only
    Maximum zernike moment:9
    Select objects to measure:Cells
    Object to use as center?:These objects
    Select objects to use as centers:None
    Select objects to measure:Cytoplasm
    Object to use as center?:These objects
    Select objects to use as centers:None
    Select objects to measure:Nuclei
    Object to use as center?:These objects
    Select objects to use as centers:None
    Scale the bins?:Yes
    Number of bins:4
    Maximum radius:100

MeasureObjectNeighbors:[module_num:13|svn_version:'Unknown'|variable_revision_number:3|show_window:False|notes:['Measure nuclei neighbors that are adjacent.']|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:Adjacent
    Neighbor distance:5
    Consider objects discarded for touching image border?:Yes
    Retain the image of objects colored by numbers of neighbors?:No
    Name the output image:ObjectNeighborCount
    Select colormap:Blues
    Retain the image of objects colored by percent of touching pixels?:No
    Name the output image:PercentTouching
    Select colormap:Oranges

MeasureObjectNeighbors:[module_num:14|svn_version:'Unknown'|variable_revision_number:3|show_window:False|notes:['Measure cells neighbors that are adjacent.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Select objects to measure:Cells
    Select neighboring objects to measure:Cells
    Method to determine neighbors:Adjacent
    Neighbor distance:5
    Consider objects discarded for touching image border?:Yes
    Retain the image of objects colored by numbers of neighbors?:No
    Name the output image:ObjectNeighborCount
    Select colormap:Blues
    Retain the image of objects colored by percent of touching pixels?:No
    Name the output image:PercentTouching
    Select colormap:Oranges

MeasureObjectSizeShape:[module_num:15|svn_version:'Unknown'|variable_revision_number:3|show_window:False|notes:['Measure area and shape features for objects using default parameters.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Select object sets to measure:Cells, Cytoplasm, Nuclei
    Calculate the Zernike features?:Yes
    Calculate the advanced features?:No

MeasureTexture:[module_num:16|svn_version:'Unknown'|variable_revision_number:7|show_window:False|notes:['Measure texture across images and objects across all channels with default parameters.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Select images to measure:CorrAGP, CorrBrightfield, CorrDNA, CorrER, CorrMito, CorrRNA
    Select objects to measure:Cells, Cytoplasm, Nuclei
    Enter how many gray levels to measure the texture at:256
    Hidden:1
    Measure whole images or objects?:Both
    Texture scale to measure:3

OverlayOutlines:[module_num:17|svn_version:'Unknown'|variable_revision_number:4|show_window:False|notes:['Create overlay for nuclei objects.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Display outlines on a blank image?:Yes
    Select image on which to display outlines:None
    Name the output image:NucleiOutlines
    Outline display mode:Color
    Select method to determine brightness of outlines:Max of image
    How to outline:Inner
    Select outline color:#008000
    Select objects to display:Nuclei

OverlayOutlines:[module_num:18|svn_version:'Unknown'|variable_revision_number:4|show_window:False|notes:['Create overlay of cells outlines.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Display outlines on a blank image?:Yes
    Select image on which to display outlines:None
    Name the output image:CellsOutlines
    Outline display mode:Color
    Select method to determine brightness of outlines:Max of image
    How to outline:Inner
    Select outline color:#008000
    Select objects to display:Cells

SaveImages:[module_num:19|svn_version:'Unknown'|variable_revision_number:16|show_window:False|notes:['Save nuclei outlines for each image set (well and site per plate).']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Select the type of image to save:Image
    Select the image to save:NucleiOutlines
    Select method for constructing file names:Single name
    Select image name for file prefix:None
    Enter single file name:NucleiOutlines_\g<Plate>_\g<Well>_\g<Site>
    Number of digits:4
    Append a suffix to the image file name?:No
    Text to append to the image name:
    Saved file format:tiff
    Output file location:Default Output Folder|
    Image bit depth:16-bit integer
    Overwrite existing files without warning?:No
    When to save:Every cycle
    Record the file and path information to the saved image?:No
    Create subfolders in the output folder?:No
    Base image folder:Elsewhere...|
    How to save the series:T (Time)
    Save with lossless compression?:Yes

SaveImages:[module_num:20|svn_version:'Unknown'|variable_revision_number:16|show_window:False|notes:['Save cells object outlines for each image set (well and site per plate).']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Select the type of image to save:Image
    Select the image to save:CellsOutlines
    Select method for constructing file names:Single name
    Select image name for file prefix:None
    Enter single file name:CellsOutlines_\g<Plate>_\g<Well>_\g<Site>
    Number of digits:4
    Append a suffix to the image file name?:No
    Text to append to the image name:
    Saved file format:tiff
    Output file location:Default Output Folder|
    Image bit depth:16-bit integer
    Overwrite existing files without warning?:No
    When to save:Every cycle
    Record the file and path information to the saved image?:No
    Create subfolders in the output folder?:No
    Base image folder:Elsewhere...|
    How to save the series:T (Time)
    Save with lossless compression?:Yes

ExportToDatabase:[module_num:21|svn_version:'Unknown'|variable_revision_number:28|show_window:False|notes:['Export data as an SQLite file.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Database type:SQLite
    Database name:DefaultDB
    Add a prefix to table names?:No
    Table prefix:MyExpt_
    Output file location:Default Output Folder|
    Create a CellProfiler Analyst properties file?:No
    Database host:
    Username:
    Password:
    Name the SQLite database file:alsf_morphology_features.sqlite
    Calculate the per-image mean values of object measurements?:No
    Calculate the per-image median values of object measurements?:No
    Calculate the per-image standard deviation values of object measurements?:No
    Calculate the per-well mean values of object measurements?:No
    Calculate the per-well median values of object measurements?:No
    Calculate the per-well standard deviation values of object measurements?:No
    Export measurements for all objects to the database?:All
    Select the objects:
    Maximum # of characters in a column name:64
    Create one table per object, a single object table or a single object view?:One table per object type
    Enter an image url prepend if you plan to access your files via http:
    Write image thumbnails directly to the database?:No
    Select the images for which you want to save thumbnails:
    Auto-scale thumbnail pixel intensities?:Yes
    Select the plate type:None
    Select the plate metadata:None
    Select the well metadata:None
    Include information for all images, using default values?:Yes
    Properties image group count:1
    Properties group field count:1
    Properties filter field count:0
    Workspace measurement count:1
    Experiment name:ALSF_features
    Which objects should be used for locations?:None
    Enter a phenotype class table name if using the Classifier tool in CellProfiler Analyst:
    Export object relationships?:Yes
    Overwrite without warning?:Never
    Access CellProfiler Analyst images via URL?:No
    Select the classification type:Object
    Select an image to include:None
    Use the image name for the display?:Yes
    Image name:Channel1
    Channel color:red
    Do you want to add group fields?:No
    Enter the name of the group:
    Enter the per-image columns which define the group, separated by commas:ImageNumber, Image_Metadata_Plate, Image_Metadata_Well
    Do you want to add filter fields?:No
    Automatically create a filter for each plate?:No
    Create a CellProfiler Analyst workspace file?:No
    Select the measurement display tool:ScatterPlot
    Type of measurement to plot on the X-axis:Image
    Enter the object name:None
    Select the X-axis measurement:None
    Select the X-axis index:ImageNumber
    Type of measurement to plot on the Y-axis:Image
    Enter the object name:None
    Select the Y-axis measurement:None
    Select the Y-axis index:ImageNumber