CellProfiler Pipeline: http://www.cellprofiler.org
Version:5
DateRevision:405
GitHash:
ModuleCount:16
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 file/folder names
    Metadata source:File name
    Regular expression to extract from file name:^(?P<Channel>.*)-(?P<FileName>.*)well(?P<Well>.*)_EM.*_Pos(?P<Position>.*).ome.tif
    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?:No

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:[{'ATAD1': 'FileName', 'Gos28': 'FileName', 'Nuclei': 'FileName', 'Mito': 'FileName'}, {'ATAD1': 'Position', 'Gos28': 'Position', 'Nuclei': 'Position', 'Mito': 'Position'}]
    Image set matching method:Metadata
    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 Channel "C1")
    Name to assign these images:Nuclei
    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 Channel "C2")
    Name to assign these images:Gos28
    Name to assign these objects:Nucleus
    Select the image type:Grayscale image
    Set intensity range from:Image metadata
    Maximum intensity:255.0
    Select the rule criteria:and (metadata does Channel "C3")
    Name to assign these images:ATAD1
    Name to assign these objects:Nucleus
    Select the image type:Grayscale image
    Set intensity range from:Image metadata
    Maximum intensity:255.0
    Select the rule criteria:and (file does contain "C4")
    Name to assign these images:Mito
    Name to assign these objects:Cytoplasm
    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

ImageMath:[module_num:5|svn_version:'Unknown'|variable_revision_number:5|show_window:False|notes:['Subtracting background fluorescence from the ATAD1-HaloTag channel. ']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Operation:None
    Raise the power of the result by:1.0
    Multiply the result by:1.0
    Add to result:-.00112
    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?:No
    Name the output image:ImageAfterMathATAD1
    Image or measurement?:Image
    Select the first image:ATAD1
    Multiply the first image by:1.0
    Measurement:
    Image or measurement?:Measurement
    Select the second image:None
    Multiply the second image by:1.0
    Measurement:Scaling_[None]

ImageMath:[module_num:6|svn_version:'Unknown'|variable_revision_number:5|show_window:False|notes:['Subtracting background fluorescence from the MitoTracker channel. ']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Operation:None
    Raise the power of the result by:1.0
    Multiply the result by:1.0
    Add to result:-.00112
    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?:No
    Name the output image:ImageAfterMathMito
    Image or measurement?:Image
    Select the first image:Mito
    Multiply the first image by:1.0
    Measurement:
    Image or measurement?:Measurement
    Select the second image:None
    Multiply the second image by:1.0
    Measurement:Scaling_[None]

ImageMath:[module_num:7|svn_version:'Unknown'|variable_revision_number:5|show_window:False|notes:['Subtracting background fluorescence from the EGFP-Gos28 channel. ']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Operation:None
    Raise the power of the result by:1.0
    Multiply the result by:1.0
    Add to result:-.00104
    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?:No
    Name the output image:ImageAfterMathGos28
    Image or measurement?:Image
    Select the first image:Gos28
    Multiply the first image by:1.0
    Measurement:
    Image or measurement?:Measurement
    Select the second image:None
    Multiply the second image by:1.0
    Measurement:Scaling_[None]

ImageMath:[module_num:8|svn_version:'Unknown'|variable_revision_number:5|show_window:False|notes:['Subtracting background fluorescence from the nuclei channel. ']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Operation:None
    Raise the power of the result by:1.0
    Multiply the result by:1.0
    Add to result:-.00103
    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?:No
    Name the output image:ImageAfterMathNuclei
    Image or measurement?:Image
    Select the first image:Nuclei
    Multiply the first image by:1.0
    Measurement:
    Image or measurement?:Measurement
    Select the second image:None
    Multiply the second image by:1.0
    Measurement:Scaling_[None]

IdentifyPrimaryObjects:[module_num:9|svn_version:'Unknown'|variable_revision_number:14|show_window:False|notes:['Identifying cells using the nuclear stain. ']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Select the input image:ImageAfterMathNuclei
    Name the primary objects to be identified:Nuclei_identified
    Typical diameter of objects, in pixel units (Min,Max):50,200
    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: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?: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
    Display accepted local maxima?:No
    Select maxima color:Blue
    Use advanced settings?:Yes
    Threshold setting version:11
    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
    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:10|svn_version:'Unknown'|variable_revision_number:10|show_window:False|notes:['Identifying transfected cells by ATAD1-HaloTag signal. ']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Select the input objects:Nuclei_identified
    Name the objects to be identified:ATAD1_identified
    Select the method to identify the secondary objects:Propagation
    Select the input image:ImageAfterMathATAD1
    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:11
    Threshold strategy:Global
    Thresholding method:Minimum Cross-Entropy
    Threshold smoothing scale:0.0
    Threshold correction factor:1.05
    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?:Three classes
    Assign pixels in the middle intensity class to the foreground or the background?:Background
    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

MaskObjects:[module_num:11|svn_version:'Unknown'|variable_revision_number:3|show_window:False|notes:['Making a mask around the signal for ATAD1 and the nucleus. ']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Select objects to be masked:ATAD1_identified
    Name the masked objects:Masked_ATAD1
    Mask using a region defined by other objects or by binary image?:Objects
    Select the masking object:Nuclei_identified
    Select the masking image:None
    Handling of objects that are partially masked:Keep overlapping region
    Fraction of object that must overlap:0.5
    Numbering of resulting objects:Renumber
    Invert the mask?:Yes

MeasureObjectSizeShape:[module_num:12|svn_version:'Unknown'|variable_revision_number:3|show_window:False|notes:['Measuring the size of ATAD1-HaloTag transfected cells. ']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Select object sets to measure:Masked_ATAD1
    Calculate the Zernike features?:No
    Calculate the advanced features?:No

FilterObjects:[module_num:13|svn_version:'Unknown'|variable_revision_number:8|show_window:False|notes:['Filtering cells whose size is below the minimum area. ']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Select the objects to filter:Masked_ATAD1
    Name the output objects:Masked_Filt_ATAD1
    Select the filtering mode:Measurements
    Select the filtering method:Limits
    Select the objects that contain the filtered objects:None
    Select the location of the rules or classifier file:Elsewhere...|
    Rules or classifier file name:rules.txt
    Class number:1
    Measurement count:1
    Additional object count:0
    Assign overlapping child to:Both parents
    Select the measurement to filter by:AreaShape_Area
    Filter using a minimum measurement value?:Yes
    Minimum value:200
    Filter using a maximum measurement value?:No
    Maximum value:1.0

MeasureObjectIntensity:[module_num:14|svn_version:'Unknown'|variable_revision_number:4|show_window:False|notes:['Measuring the ATAD1-HaloTag signal for each cell to approximate the expession level of ATAD1. ']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Select images to measure:ATAD1, ImageAfterMathATAD1
    Select objects to measure:ATAD1_identified, Masked_Filt_ATAD1

MeasureColocalization:[module_num:15|svn_version:'Unknown'|variable_revision_number:5|show_window:False|notes:['Measuring colocalization between the EGFP-Gos28 signal and the MitoTracker/ATAD1-HaloTag signal within the ATAD1-HaloTag positive cells. ']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Select images to measure:ImageAfterMathATAD1, ImageAfterMathGos28, ImageAfterMathMito
    Set threshold as percentage of maximum intensity for the images:15.0
    Select where to measure correlation:Within objects
    Select objects to measure:Masked_Filt_ATAD1
    Run all metrics?:No
    Calculate correlation and slope metrics?:Yes
    Calculate the Manders coefficients?:No
    Calculate the Rank Weighted Colocalization coefficients?:No
    Calculate the Overlap coefficients?:No
    Calculate the Manders coefficients using Costes auto threshold?:No
    Method for Costes thresholding:Fast

ExportToSpreadsheet:[module_num:16|svn_version:'Unknown'|variable_revision_number:13|show_window:False|notes:['Exporting measurements to an Excel file. ']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
    Select the column delimiter:Comma (",")
    Add image metadata columns to your object data file?:Yes
    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?: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?:Yes
    Press button to select measurements:Masked_Filt_ATAD1|Correlation_Correlation_ATAD1_Gos28
    Representation of Nan/Inf:NaN
    Add a prefix to file names?:Yes
    Filename prefix:First_run
    Overwrite existing files without warning?:No
    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
