TIMELAPSE CELLPROFILER MANUAL

Parameters require manual input from the user whereas, in the stand-alone version, some modules can inherit parameter values from other modules.

Parameters for some CellProfiler modules are limited/constrained compared to the stand-alone version, most notably:.

Modules used by the pipeline aren’t available in Galaxy.The Galaxy tool currently uses CellProfiler 3.9. The pipeline was built with a different version of CellProfiler.Some pipelines created with stand-alone CellProfiler may not work with the Galaxy CellProfiler tool. The Galaxy CellProfiler Tool: toolshed.g2.bx.psu.edu/repos/bgruening/cp_cellprofiler/cp_cellprofiler/3.1.9+galaxy0 tool takes two inputs: a CellProfiler pipeline and an image collection. Warning: Important information: CellProfiler in Galaxy Here we will link objects if they significantly overlap between the current and previous frames. Linking is done by matching objects and several criteria or matching rules are available. Tracking is done by first segmenting objects then linking objects between consecutive frames. To demonstrate how automatic tracking can be applied in such situations, this tutorial will track dividing nuclei in a short time-lapse recording of one mitosis of a syncytial blastoderm stage Drosophila embryo expressing a GFP-histone gene that labels chromatin. One of these challenges is the tracking of individual objects as it is often impossible to manually follow a large number of objects over many time points. However, automated time-lapse imaging can produce large amounts of data that can be challenging to process. Combining fluorescent markers with time-lapse imaging is a common approach to collect data on dynamic cellular processes such as cell division (e.g. Lower and upper bounds on threshold:0.0,1.Most biological processes are dynamic and observing them over time can provide valuable insights. Name the new primary objects:FilteredNuclei Number of pixels by which to expand the primary objects:10ĭiscard secondary objects touching the border of the image?:Noĭiscard the associated primary objects?:No Select the method to identify the secondary objects:Propagation IdentifySecondaryObjects:|batch_state:array(, dtype=uint8)|enabled:True|wants_pause:False] RelateObjects:|batch_state:array(, dtype=uint8)|enabled:True|wants_pause:False]Ĭalculate per-parent means for all child measurements?:Noĭo you want to save the children with parents as a new object set?:No Two-class or three-class thresholding?:Three classes Typical diameter of objects, in pixel units (Min,Max):7,80 Name the primary objects to be identified:PH3

Two-class or three-class thresholding?:Two classesĪssign pixels in the middle intensity class to the foreground or the background?:Foreground Select the measurement to threshold with:None Lower and upper bounds on threshold:0.0,1.0 Thresholding method:Minimum Cross-Entropy Handling of objects if excessive number of objects identified:Continue Speed up by using lower-resolution image to find local maxima?:Yesįill holes in identified objects?:After declumping onlyĪutomatically calculate size of smoothing filter for declumping?:YesĪutomatically calculate minimum allowed distance between local maxima?:Yes Suppress local maxima that are closer than this minimum allowed distance:7.0 Method to draw dividing lines between clumped objects:Intensity Method to distinguish clumped objects:Intensity Typical diameter of objects, in pixel units (Min,Max):8,80ĭiscard objects outside the diameter range?:Yesĭiscard objects touching the border of the image?:Yes Name the primary objects to be identified:Nuclei IdentifyPrimaryObjects:|batch_state:array(, dtype=uint8)|enabled:True|wants_pause:False] Groups:|batch_state:array(, dtype=uint8)|enabled:True|wants_pause:False] Select the rule criteria:and (file does contain 'd2.tif') Select the rule criteria:and (file does contain 'd1.tif') Select the rule criteria:and (file does contain 'd0.tif') NamesAndTypes:|batch_state:array(, dtype=uint8)|enabled:True|wants_pause:False] Select the filtering criteria:and (file does contain '') Regular expression to extract from file name:^(?P.*)_(?P)$ Metadata extraction method:Extract from file/folder names Metadata:|batch_state:array(, dtype=uint8)|enabled:True|wants_pause:False] Select the rule criteria:and (extension does isimage) (directory doesnot containregexp '\\.') Images:|batch_state:array(, dtype=uint8)|enabled:True|wants_pause:False]

Timelapse cellprofiler