CellProfiler Pipeline: http://www.cellprofiler.org Version:5 DateRevision:413 GitHash: ModuleCount:18 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.*)_(?P[A-Z][0-99]{2})_S(?P[0-99])_C(?P[0-9]) Regular expression to extract from folder name:(?P[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: 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:Color image Name to assign these images:OverlayRaw Match metadata:[] Image set matching method:Order Set intensity range from:Image metadata Assignments count:2 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 (file does contain "C1") Name to assign these images:BrightfieldOriginal 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 (file does contain "C2") Name to assign these images:GFPOriginal Name to assign these objects:Nucleus 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?:Yes grouping metadata count:1 Metadata category:Well Threshold:[module_num:5|svn_version:'Unknown'|variable_revision_number:12|show_window:False|notes:['Threshold to select for worm bodies', '']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Select the input image:BrightfieldOriginal Name the output image:Threshold Threshold strategy:Adaptive Thresholding method:Minimum Cross-Entropy Threshold smoothing scale:0.7 Threshold correction factor:1.0 Lower and upper bounds on threshold:.5,1.0 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:250 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:6|svn_version:'Unknown'|variable_revision_number:14|show_window:False|notes:['worm objects rough approximation']|batch_state:array([], dtype=uint8)|enabled:False|wants_pause:False] Select the input image:Threshold Name the primary objects to be identified:WormsRough Typical diameter of objects, in pixel units (Min,Max):60,1000 Discard objects outside the diameter range?:Yes Discard objects touching the border of the image?:Yes 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:7.0 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: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:0.3,1.0 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 ConvertObjectsToImage:[module_num:7|svn_version:'Unknown'|variable_revision_number:1|show_window:False|notes:[]|batch_state:array([], dtype=uint8)|enabled:False|wants_pause:False] Select the input objects:WormsRough Name the output image:Worms_rough_approxbinary Select the color format:Binary (black & white) Select the colormap:Default UntangleWorms:[module_num:8|svn_version:'Unknown'|variable_revision_number:2|show_window:False|notes:['Untangle worms and output non-overlapping worms as objects']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Select the input binary image:Threshold Overlap style:Both Name the output overlapping worm objects:Overlappingworms Name the output non-overlapping worm objects:NonOverlappingWorms Training set file location:Default Input Folder sub-folder|Downloads Training set file name:Training Set UntanglingWorms Supplemental File 2.xml Use training set weights?:Yes Overlap weight:5.0 Leftover weight:10.0 Retain outlines of the overlapping objects?:No Outline colormap?:Default Name the overlapped outline image:OverlappedWormOutlines Retain outlines of the non-overlapping worms?:Yes Name the non-overlapped outlines image:NonoverlappedWormOutlines Train or untangle worms?:Untangle Minimum area percentile:1.0 Minimum area factor:0.85 Maximum area percentile:90.0 Maximum area factor:1.0 Minimum length percentile:1.0 Minimum length factor:0.9 Maximum length percentile:99.0 Maximum length factor:1.1 Maximum cost percentile:90.0 Maximum cost factor:1.9 Number of control points:21 Maximum radius percentile:90.0 Maximum radius factor:1.0 Maximum complexity:High Custom complexity:400 EnhanceOrSuppressFeatures:[module_num:9|svn_version:'Unknown'|variable_revision_number:7|show_window:False|notes:['Enhancement of aggregates through background removal']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Select the input image:GFPOriginal Name the output image:AggEnhanced Select the operation:Enhance Feature size:8 Feature type:Speckles Range of hole sizes:1,10 Smoothing scale:2.0 Shear angle:0.0 Decay:0.95 Enhancement method:Tubeness Speed and accuracy:Slow Rescale result image:No IdentifyPrimaryObjects:[module_num:10|svn_version:'Unknown'|variable_revision_number:14|show_window:False|notes:['Aggregate counting']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Select the input image:AggEnhanced Name the primary objects to be identified:Aggregates Typical diameter of objects, in pixel units (Min,Max):1,10 Discard objects outside the diameter range?:No Discard objects touching the border of the image?:No 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:7.0 Speed up by using lower-resolution image to find local maxima?:No 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?:Yes Select maxima color:Blue Use advanced settings?:Yes Threshold setting version:12 Threshold strategy:Adaptive Thresholding method:Robust Background Threshold smoothing scale:1.1 Threshold correction factor:1.0 Lower and upper bounds on threshold:0.10,1.0 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?: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:Robust Background ConvertObjectsToImage:[module_num:11|svn_version:'Unknown'|variable_revision_number:1|show_window:False|notes:['Convert Aggregate identification to picture for export']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Select the input objects:Aggregates Name the output image:AggregateIdentification Select the color format:Color Select the colormap:Default OverlayOutlines:[module_num:12|svn_version:'Unknown'|variable_revision_number:4|show_window:False|notes:['Overlay aggregate outlines and worm body outlines']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Display outlines on a blank image?:No Select image on which to display outlines:GFPOriginal Name the output image:OrigOverlay Outline display mode:Color Select method to determine brightness of outlines:Max of image How to outline:Inner Select outline color:magenta Select objects to display:NonOverlappingWorms Select outline color:red Select objects to display:Aggregates OverlayOutlines:[module_num:13|svn_version:'Unknown'|variable_revision_number:4|show_window:False|notes:['Outline worm bodies upon BrightfieldOriginal']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Display outlines on a blank image?:No Select image on which to display outlines:BrightfieldOriginal Name the output image:Worm_outlines Outline display mode:Color Select method to determine brightness of outlines:Max of image How to outline:Inner Select outline color:green Select objects to display:NonOverlappingWorms RelateObjects:[module_num:14|svn_version:'Unknown'|variable_revision_number:5|show_window:False|notes:['Defines the number of aggregates per each identified worm']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Parent objects:NonOverlappingWorms Child objects:Aggregates Calculate child-parent distances?:None Calculate per-parent means for all child measurements?:No 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:None Parent name:None Parent name:None Parent name:None Parent name:None Parent name:None Parent name:None Parent name:None Parent name:None Parent name:None Parent name:None Parent name:None Parent name:None Parent name:None Parent name:None Parent name:None Parent name:None Parent name:None Parent name:None Parent name:None Parent name:None Parent name:None Parent name:None Parent name:None Parent name:None Parent name:None Parent name:None Parent name:None Parent name:None Parent name:None Parent name:None Parent name:None Parent name:None Parent name:None Parent name:None Parent name:None Parent name:None SaveImages:[module_num:15|svn_version:'Unknown'|variable_revision_number:15|show_window:False|notes:['Save aggregate picture']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Select the type of image to save:Image Select the image to save:AggregateIdentification Select method for constructing file names:From image filename Select image name for file prefix:GFPOriginal Enter single file name:Aggregate Identification Number of digits:4 Append a suffix to the image file name?:Yes Text to append to the image name:Agg Saved file format:tiff Output file location:Default Output Folder| Image bit depth:8-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) SaveImages:[module_num:16|svn_version:'Unknown'|variable_revision_number:15|show_window:False|notes:['Save outlines that are overlayed']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Select the type of image to save:Image Select the image to save:OrigOverlay Select method for constructing file names:From image filename Select image name for file prefix:BrightfieldOriginal Enter single file name:Outlines Number of digits:4 Append a suffix to the image file name?:Yes Text to append to the image name:Outlines Saved file format:tiff Output file location:Default Output Folder| Image bit depth:8-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) SaveImages:[module_num:17|svn_version:'Unknown'|variable_revision_number:15|show_window:False|notes:['Save worms identified as picture']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Select the type of image to save:Image Select the image to save:Worm_outlines Select method for constructing file names:From image filename Select image name for file prefix:BrightfieldOriginal Enter single file name:Worm Identification Number of digits:4 Append a suffix to the image file name?:Yes Text to append to the image name:Bodies Saved file format:tiff Output file location:Default Output Folder| Image bit depth:8-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) ExportToSpreadsheet:[module_num:18|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?:Yes Add image file and folder names to your object data file?:No Select the measurements to export:Yes 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| 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:NonOverlappingWorms|Worm_ControlPointY_8,NonOverlappingWorms|Worm_ControlPointY_7,NonOverlappingWorms|Worm_ControlPointY_5,NonOverlappingWorms|Worm_ControlPointY_2,NonOverlappingWorms|Worm_ControlPointY_6,NonOverlappingWorms|Worm_ControlPointY_4,NonOverlappingWorms|Worm_ControlPointY_15,NonOverlappingWorms|Worm_ControlPointY_20,NonOverlappingWorms|Worm_ControlPointY_3,NonOverlappingWorms|Worm_ControlPointY_11,NonOverlappingWorms|Worm_ControlPointY_10,NonOverlappingWorms|Worm_ControlPointY_18,NonOverlappingWorms|Worm_ControlPointY_16,NonOverlappingWorms|Worm_ControlPointY_17,NonOverlappingWorms|Worm_ControlPointY_19,NonOverlappingWorms|Worm_ControlPointY_9,NonOverlappingWorms|Worm_ControlPointY_12,NonOverlappingWorms|Worm_ControlPointY_13,NonOverlappingWorms|Worm_ControlPointY_21,NonOverlappingWorms|Worm_ControlPointY_1,NonOverlappingWorms|Worm_ControlPointY_14,NonOverlappingWorms|Worm_ControlPointX_17,NonOverlappingWorms|Worm_ControlPointX_11,NonOverlappingWorms|Worm_ControlPointX_15,NonOverlappingWorms|Worm_ControlPointX_5,NonOverlappingWorms|Worm_ControlPointX_2,NonOverlappingWorms|Worm_ControlPointX_14,NonOverlappingWorms|Worm_ControlPointX_4,NonOverlappingWorms|Worm_ControlPointX_10,NonOverlappingWorms|Worm_ControlPointX_9,NonOverlappingWorms|Worm_ControlPointX_12,NonOverlappingWorms|Worm_ControlPointX_19,NonOverlappingWorms|Worm_ControlPointX_1,NonOverlappingWorms|Worm_ControlPointX_20,NonOverlappingWorms|Worm_ControlPointX_8,NonOverlappingWorms|Worm_ControlPointX_3,NonOverlappingWorms|Worm_ControlPointX_16,NonOverlappingWorms|Worm_ControlPointX_13,NonOverlappingWorms|Worm_ControlPointX_21,NonOverlappingWorms|Worm_ControlPointX_18,NonOverlappingWorms|Worm_ControlPointX_7,NonOverlappingWorms|Worm_ControlPointX_6,NonOverlappingWorms|Worm_Angle_8,NonOverlappingWorms|Worm_Angle_14,NonOverlappingWorms|Worm_Angle_6,NonOverlappingWorms|Worm_Angle_4,NonOverlappingWorms|Worm_Angle_9,NonOverlappingWorms|Worm_Angle_18,NonOverlappingWorms|Worm_Angle_2,NonOverlappingWorms|Worm_Angle_15,NonOverlappingWorms|Worm_Angle_16,NonOverlappingWorms|Worm_Angle_1,NonOverlappingWorms|Worm_Angle_5,NonOverlappingWorms|Worm_Angle_10,NonOverlappingWorms|Worm_Angle_19,NonOverlappingWorms|Worm_Angle_7,NonOverlappingWorms|Worm_Angle_13,NonOverlappingWorms|Worm_Angle_11,NonOverlappingWorms|Worm_Angle_17,NonOverlappingWorms|Worm_Angle_3,NonOverlappingWorms|Worm_Angle_12,NonOverlappingWorms|Worm_Length,NonOverlappingWorms|Children_Aggregates_Count,NonOverlappingWorms|Location_Center_X,NonOverlappingWorms|Location_Center_Y,NonOverlappingWorms|Number_Object_Number,Aggregates|Location_Center_Z,Aggregates|Location_Center_X,Aggregates|Location_Center_Y,Aggregates|Number_Object_Number,Aggregates|Parent_NonOverlappingWorms Representation of Nan/Inf:Null Add a prefix to file names?:Yes Filename prefix:MyExpt_ Overwrite existing files without warning?:No Data to export:NonOverlappingWorms 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:Aggregates Combine these object measurements with those of the previous object?:Yes File name:DATA.csv Use the object name for the file name?:Yes