Integrative Toolkit to Analyze Cellular Signals: Forces, Motion, Morphology, and Fluorescence

NOTE: Samples examined using the iTACS platform are cells adhered to a soft substrate. The protocol for assessing mechanical and chemical signals is divided into two sequential parts: Acquisition and Training Module (AcTrM) and Analysis and Visualization Module (AnViM).

1. Acquisition and Training Module (AcTrM)

NOTE: AcTrM automates the process of data acquisition and user self-training. Before any data acquisition, prepare a soft substrate capable of providing information necessary to quantify forces that cells exert on it.

1. Hydrogel preparation
   NOTE: The goal here is to prepare a 1,250 Pa shear modulus, approximately 100 µm thickness, and 22 mm diameter polyacrylamide (PAA) hydrogel.
   1. Prepare polyacrylamide solution by following the method of Yeung et al. and cast the hydrogels following steps described by Trepat et al.^14,15. One exception to the procedure is that the beads embedded immediately underneath the cells are 0.5 µm in diameter and emit yellow fluorescence.
   2. Skip the step of attaching 2 µm beads to the coverglass if the viewing area is expected to have a large cell-free region.
      NOTE: Hydrogel preparation protocol is now fairly established in the field¹⁶. Throughout the subsequent description, the 0.5 µm beads are referred to as `top beads', and the 2 µm beads are referred to as `bottom beads'. However, the bottom beads are optional where the imaged region contains a large cell-free area. The top bead pattern from such a cell-free region will serve the purpose of the bottom bead pattern.
   3. Mount the hydrogel with embedded fluorescent beads on the microscope stage.
   4. Allow 15-20 min for the temperature of the plate to attain a steady-state.
      NOTE: The plate's top surface is functionalized with extracellular matrix proteins, but the cells are not yet seeded on the hydrogel.
2. Reference image acquisition
   1. Part 1: Creating a position list
      NOTE: Manual input in this step includes following the AcTrM prompts to choose locations with the best bead distribution. No previously created files are used in this step. Key new folders produced in this step include `t0imgs', `tnimgs', and `textfiles' folders, and the file produced includes the position list file. See Figure 2 for the visual description of the following steps that guide the creation of a position list using AcTrM. The demonstrated example acquires data at 20x magnification.
      1. Start µManager 2.0 – Beta.
      2. Run AcTrM by clicking on the AcTrM.bsh button in the IMBL Resources window.
      3. In the window titled Define Acquisition Properties, select the appropriate objective, tolerance for the accuracy of lateral position (i.e., XY) recovery, step size of the rough and refined refocusing (i.e., z) operation, and value of acceptable image correlation coefficient for focus recovery.
         NOTE: A finer tolerance for the lateral position recovery will slow position recovery, but a substantial tolerance will need position correction during data analysis and may cause difficulty in focus recovery. A smaller step size will slow the refocusing operation, but a very high step size may cause rapid movement with opportunities to miss the focus.
      4. In the AcTrM – Step 0 window, select Fresh Acquisition to create a position list.
         NOTE: The window titled AcTrM – Step 1 lists all the key next steps. These steps involve moving the stage, adjusting the focus, and clicking on buttons in the µManager. These steps guide in constructing the list of positions suitable for data acquisition.
      5. Click on Live de Micromanager to visualize the samples for manual adjustments listed in the AcTrM – Step 1 window.
      6. Follow the steps listed on this window.
      7. Now acquire the image of the beads. Select the appropriate channel for the top beads.
      8. Ensure to look at the bottom beads as well. To do so, select the channels for the bottom beads. A blurry image of bottom beads is seen.
         NOTE: Channels can be switched from the preset dropdown menu on the main µManager window. If the bottom beads are used in the experiment, ensure that they are present in the selected position. These beads will appear blurry.
      9. Upon selecting the appropriate position, click on Mark in the Stage Position List window to save the position.
         NOTE: The best position is defined by a dense and uniform distribution of the top beads embedded immediately underneath the top surface (i.e., top beads) and at least two beads attached to the cover glass (i.e., bottom beads) (Supplementary Figure S1). Focus recovery is faster if the bottom beads appear as large, out-of-focus rings. However, if experiments are done in one position with no need for focus or lateral position recovery, ignore instructions related to the bottom beads image.
      10. Follow steps 6-9 described in Figure 2 to include additional positions into the list.
          NOTE: Choose a few additional positions so that a round of elimination can allow for the best positions chosen on the plate.
   2. Part 2: Acquisition of reference images
      NOTE: This step does not involve any manual input. Previously created key files used in this step include `textfiles/*.pos'. Key new files and folders produced in this step include those within `t0imgs' and `tnimgs' folders. See Figure 3 and Supplementary Figure S2 for the visual description of the following steps that guide the acquisition of reference images using AcTrM. The AcTrM – Step 2 window also lists all the key steps.
      1. Following the steps listed in AcTrM – Step 2 window, make the choices in the Multi-Dimensional Acquisition window. For example, to perform a long-time lapse, indicate a number of images to be taken, select the first channel as phase channel, and then select the next for the top beads and the one after that is for bottom beads. Click on Close in the Multi-Dimensional Acquisition window, and then click on OK in the ActrM – Step 2 window.
      2. In the AcTrM – Step 3 window, choose to engage the reference-image-based XYZ position recovery. The choice is generally yes. However, if images are acquired at one position with no room for focus or stage drift, the choice in AcTrM – Step 3 window will be No.
      3. In the AcTrM – XYZ Recovery Options window, set the channel for rough XYZ recovery, whether to perform refined XYZ recovery, region, and channel for refined XYZ recovery and the direction to begin refocusing (Supplementary Figure S4). When completed, AcTrM will acquire reference images.
         NOTE: Typical choices for the channel will be the bottom beads channel. XYZ recovery works best when carried out with the full image in the current implementation. Reference images will typically include a transmitted light image of the hydrogel, a fluorescent image of top beads, and a fluorescent image of the bottom beads. Each image set's content may vary based on the choices made in the Multi-Dimensional Acquisition window. Still, the software will acquire the reference image set at each position determined in Figure 2. At the end of this step, three folders are created in the chosen directory: `t0imgs', `tnimgs', and `textfiles'. The `t0imgs' folder contains reference images in the format recognized by µManager and used in subsequent steps; `tnimgs' folder contains separate TIFF images with filenames `c0_p0_t0.tif', `c1_p0_t0.tif', etc. Here, `c' stands for the channel, `p' stands for the position, and `t' stands for the time. Following these letters are the channel number, position number, and frame number, respectively. The folder `textfiles' contains the position list in XML format and user choices for image acquisition and position recovery.
3. Cell seeding and growth
   NOTE: The iTACS platform has the flexibility to accommodate sample preparation protocols used in common in vitro assessment of mechanical behavior of adherent cells, including sparse cells, fully confluent monolayer, network formation assay, and monolayers with holes or significant gaps.
   1. Culture rat pulmonary microvascular endothelial cells to confluence in a flask^17,18.
   2. Detach the cells using trypsin. Resuspend the cells in a culture medium containing 10% fetal bovine serum to a concentration 1 x 10⁶ cells/mL.
   3. Place a 5 µL droplet of the resuspended cells on a partially dry hydrogel surface and place it in the cell culture incubator.
      NOTE: After 2 days in the culture medium containing 10% fetal bovine serum, the cells in that droplet form a crowded island of cells¹.
4. Automated image acquisition for the remaining experiment
   NOTE: Manual input for this step includes following the AcTrM prompts to resume the image acquisition. Key previously created files used by this step include `textfiles/*.pos' and bottom bead image files in the folder `t0imgs'. Key new files produced in this step include updated position list files and images `tnimgs/*_t*.tif'.
   1. Ensure that the microscope environmental control system reaches stable tissue culture conditions.
   2. Gently mount the plate containing cultured cells onto the microscope stage.
   3. Allow 15-20 min for the temperature and humidity to stabilize.
      NOTE: See Figure 4 for the visual description of the following steps that guide the acquisition of images for the remaining experiment using AcTrM.
   4. Start µManager 2.0 – Beta.
   5. Run AcTrM by clicking on the AcTrM.bsh button in the IMBL Resources window.
      NOTE: Ignore the choices made in the Define Acquisition Properties window but use the choices made in the previous step.
   6. In the AcTrM – Step 0 window, select Continue Paused Acquisition.
   7. Select the magnification and directory identified in the Multi-Dimensional Acquisition window in the earlier step where data folders ('t0imags', `tnimgs', and `textfiles') were saved.
      NOTE: The title of the window guides the user to choose the appropriate directory.
   8. In the Repositioning the Plate window, select choices for repositioning the plate (three noncollinear positions) along with the channel used for repositioning.
      NOTE: Saved images will be seen in the camera. If overlapping images display as a red,green, and black color image, perform manual adjustment.
   9. Click on Accept to proceed with the acquisition.
      NOTE: This step overcomes the slight shifts from the irreproducibility of plate alignment when the plate is remounted on the microscope stage. Follow AcTrM prompts to expedite alignment at each of the three positions by showing a composite image of the reference image shown in red (typically of the bottom beads) and the image currently observed through the objective shown in green. Getting the green sufficiently close to red leaves less work for the software. When the overlap is perfect, the composite image appears yellow and black. Sufficiently close is typically when the same bottom beads are visible in both red and green images, and the corresponding red and green out-of-focus rings are touching each other. After the plate repositioning is complete, AcTrM takes the stage to each selected position and recovers XYZ position by matching the reference image with what is currently seen through the camera. The first lateral (XY) position is matched, and then the focus (Z) is matched. Rough recovery is followed by refined recovery of the position and focus. Updates of the current status of the experiment are displayed on the screen through a four-part window shown in Supplementary Figure S3. The acquired images are saved in the `tnimgs' folder following `*_t1.tif', `*_t2.tif', indicating the time count for the image set. If XYZ recovery identifies an updated position, the new position list is generated and saved in the `textfiles' folder.

2. Analysis and Visualization Module (AnViM)

1. Setting up automated data analysis
   NOTE: Manual input in this step includes identifying the location of the `tnimgs' folder. Key previously created files used in this step include `tnimgs/*.tif'. Key new files and folders produced in this step include the `analysis' folder in the same parent folder as `tnimgs' and folders for each position `analysis/p*'. Within each `analysis/p*', this step creates a new `*.tif' image files within `phs' and `tny ' folders. These images are cropped and de-drifted images of cells and top beads. The other files created include `analysis/analysisChoices.txt' which lists analysis choices, `analysis/p*/skipAnalysis.txt', which lists instances where analysis is skipped due to significant preexisting drift, and `analysis/p*/part_shift_values_pixel_degree.dat' which lists estimated drift values. AnViM does not alter the raw data in the `tnimgs' folder. See Figure 5 for the visual description of the following steps that guide the setting up of automated data analysis using AnViM.
   1. Start the Fiji software and select the first option in the MSM drop-down menu labeled as MSM – pre-processing.
   2. Using the file browser dialog, select the folder containing the `tnimgs' folder, which contains the analyzed data.
   3. Define the channel for the images. Following the guidelines from Supplementary Figure S5, identify the channel numbers of the transmitted light image of the cells (phase contrast image of the cells), bottom beads image and top beads image. The following three checkboxes (`Move files to the position folder', `Do additional correction for rigid motion', and `Crop data and save in position folder') are typically checked. Finally, define tolerance for rejecting heavily drifted data, pixel size, and sides of the image where the cells cross.
   4. Respond to the prompt for enhancing the brightness and contrast of the bottom bead images so the beads appear prominently. Adjust this using the slider bar in the menu and click on OK.
   5. Now perform position correction to get rid of the shifts, if any. Once done, an analysis folder is created.
      NOTE: Contrast enhancement is typically not needed, but this provision is available for experiments where exposure to lasers needs to be minimized. After that choice, AnViM copies the files from the `tnimgs' folder to the `analysis' folder. The files corresponding to each position are saved in folders `analysis/p0, analysis/p1', etc. Within each of these position folders, AnViM makes `cels', `defs', and `refs' folders containing the original transmitted light image, top beads images, and bottom beads images, respectively (Supplementary Figure S6). AnViM then analyzes rigid motion in the images of the bottom beads and creates a `phs' folder containing a corrected transmitted light image of the cells and a `tny' folder containing updated top beads images. Finally, user choices of the channels, operations, tolerance, pixel size, and boundary-crossing are saved in the `analysisChoices.txt' file (Supplementary Figure S6).
2. Quantification of deformation of hydrogel and monolayer
   NOTE: It is important to note that quantification of movement from a sequence of images is a rapidly evolving field¹⁹. The technology is constantly optimized for features, including speed, accuracy, specific features within the raw images, and specific deformation patterns. Hence, it is likely that some users may use a different deformation quantification approach than the one presented here.
   1. Part 1: Quantification of hydrogel deformation
      NOTE: Manual inputs in this step include identifying data directory and selection of grid resolution. Key previously created files used in this step include `p*/tny/*.tif'. Key new files produced in this include `p*/displacement/*_disp.dat' that lists displacement vectors of the top surface of the hydrogel. See Figure 6 for the visual description of the following steps to engage, via AnViM, the Particle Image Velocimetry analysis on the top beads images²⁰.
      1. Start the Fiji software, and from the MSM drop-down menu, select MSM – Gel Deformation.
      2. From here, select the option that is suitable for the experiment.
      3. Using the file browser dialog, select the parent directory of the `analysis' folder containing the analyzed data.
      4. In the Parameters for Calculating Gel Deformation window, select appropriate cross-correlation window size, noise level, and threshold (Supplementary Figure S7)²⁰.
         NOTE: The results are saved in a newly created `displacement' directory within each position folder `analysis/p0, analysis/p1', etc. This is where all the output files are stored.
   2. Part 2: Quantification of monolayer deformation
      NOTE: Manual inputs in this step include identifying the data directory and selection of grid resolution. Key previously created files used in this step include `p*/tny/*.tif'. Key new files produced in this include `p*/velocity/*_vel.dat' that lists motion vectors of the cells. See Figure 7 for the visual description of the steps to engage, via AnViM, the Particle Image Velocimetry analysis on the top beads images²⁰. The procedure is similar to the one followed for quantifying hydrogel deformation and selects MSM – Cellular Motion from the MSM drop-down menu. The results are saved in a newly created `velocity' directory within each position folder `analysis/p0', `analysis/p1', etc.
3. Quantification of cell-ECM and cell-cell forces
   NOTE: Manual input in this step includes identifying the data directory, indicating the hydrogel stiffness, and responding to cellular cluster segmentation prompts to detect cells from the no-cell region. Key previously created files used in this step include `p*/displacement/*_disp.dat'. Key new files produced in this step include: `p*/traction/*_trac.dat', which lists forces exerted by the cells on the hydrogel; `p*/traction/*_domain.dat', which lists the location of grid points containing cells; and input files `p*/traction.in, p*/clusterInput.txt' and `p*/prestress.in' that record user choices for this step. Following the first quantitative assessment of cell-ECM and cell-cell forces, several variations to the technique have been developed^1,15. The variations focus on particular cases of substrates, cells, experimental conditions, or numerical tools^7,8,21,22. See Figure 8 for the visual description to engage via AnViM, the Fourier Transform Traction Microscopy, and Monolayer Stress Microscopy analysis on the hydrogel deformation data^1,2,15.
   1. Start the Fiji software, and from the MSM drop-down menu, select MSM – Cell-ECM and Cell-Cell Forces (third option in the dropdown menu).
   2. Using the file browser dialog, select the parent directory of the `analysis' folder containing the folders `tnimgs' and `analysis' containing analyzed data. Click on Select.
   3. In the Parameters for Calculating Cellular Forces window, enter the shear modulus, thickness of the hydrogel and the anticipated noise level. Select OK. This lets it execute traction via the MATLAB function.
      NOTE: Following these inputs, AnViM computes cell-ECM forces.
   4. After that, indicate whether the monolayer is confluent. If the entire cell image is covered with cells, then the answer is Yes. In that case, the cell-cell forces will be computed across the whole frame. On the other hand, if a portion of the image does not have cells, then the answer is No. In that case, follow AnViM prompts to facilitate segmentation of the image region that contains cells.
   5. If the answer is no, manually draw a polygon around the non-cell object when the software prompts to do so, and then select an appropriate method(s) for segmentation. The software will ask for the color (black or white) of the cells.
   6. Check the Fill Spots Automatically option in the software and click on OK.
      NOTE: The steps for segmenting a non-confluent monolayer will be covered in the first part of `Section 2.4. Cell-ECM forces are stored in `*_trac.dat ' files in a newly created directory `traction' within each position folder, and the input to the cell-ECM force calculation software is saved in the file `traction.in' (Supplementary Figure S8). Cell-cell forces are stored in `*_prestress.dat' files in a newly created directory `prestress' within each position folder, and the input to the cell-cell force calculation software is saved in the file `prestress.in' (Supplementary Figure S9).
4. Mapping grid point values on individual cells
   NOTE: One of the current focuses of iTACS is to introduce a straightforward approach to interpret the measured mechanical signals in the field. This approach is beneficial for examining mechanical interactions among neighboring cells of a cluster¹⁸. Overall, the properties quantified until now are on regularly spaced grid points across the cellular cluster. This data identifies median, mean, and standard deviation of selected properties within the morphological boundary of individual cells and assigns those as cellular physical properties/signals. From these, the standard deviation is used to indicate variability, the difference between mean and median is used to indicate the nature of distribution, and the median value is used to indicate the overall state of the cells for the selected properties.
   1. Part 1: Segmentation of the image region that contains cells
      NOTE: Manual input to this step includes identifying data directory and responding to the segmentation prompts to detect cells from the no-cell region. Key previously created files used in this step include `p*/phs/*.tif'. Key new files produced in this step include `p*/phs/bwImages/*.tif' which are binary images separating cell regions from no-cell regions, `p*/phs/textResults/frameNum_percentHealed.txt', which lists percent image area covered by cells in each instance, and `p*/clusterInput.txt', which records user choices entered in the AcTrM interface. See Figure 9 for the visual description of the following steps to segment the image region that contains cells. This part must be completed before computing the cell-cell forces. In that case, these steps need not be repeated. Also, if these steps are conducted before the cell-cell force calculations, they are not requested at the beginning of the force calculations.
      1. Start the Fiji software, and from the MSM drop-down menu, select Segmentation – Cellular Cluster.
      2. Using the file browser dialog, select the position directory `analysis/p0', `analysis/p1', etc., that contains properties quantified on regularly spaced grid points.
      3. Indicate whether the monolayer is confluent.
         NOTE: The steps below are invoked only when the monolayer is not confluent. Follow AnViM prompts to apply the novel multi-pronged approach to identify the image regions that contain cells. The process involves four methods – each approaching segmentation in a different manner. One or multiple of these methods used in combination cover a wide variety of images of the cells. Therefore, try different approaches to find which combination works best for their data.
      4. Adjust the `Domain connection factor' and `Smear factor' to obtain optimum segmentation.
         NOTE: The `Smear factor' makes the regions that contain cells larger.
      5. Indicate whether the cells appear black or white in the binary image.
      6. In the Directions to Clean the Boundary Image window, choose whether to clean the image automatically or manually.
         NOTE: Unwanted features of the images are black spots on the pixels occupied by cells and white spots on the pixels disconnected from the cell cluster to be analyzed. Analysis can only be done on the regions that are connected. So multiple disconnected regions must be analyzed separately.
   2. Part 2: Segmentation of the individual cells in the images
      NOTE: Manual inputs to this step include identifying the data directory and responding to the segmentation prompts to detect individual cells within the image. Key previously created files used in this step include `p*/phs/*.tif' and `p*/phs/bwImages/*.tif'. Key new files produced include `p*/phs/textResults/*.csv', which contain cellular morphological properties. See Figure 10 for the visual description of the following steps to segment individual cells of the monolayer.
      1. Start the Fiji software, and from the MSM drop-down menu, select Segmentation – Individual Cells.
      2. Using the file browser dialog, select the position directory `analysis/p0', `analysis/p1', etc., that contains properties quantified on regularly spaced grid points.
      3. In the Choose the Input Parameters window, indicate the maximum aspect ratio, prominence of how much the cell center stands out compared to the cell boundary, and two blurring parameters to guide the detection of the cells (Supplementary Figure S10).
      4. On the image stack for each position, draw a polygon on the smallest normal cell. This is used to calculate the area. Anything smaller than this will not be considered as a cell by the software.
      5. Next draw a polygon around the largest normal cell and indicate whether the cell center or the cell-cell interface is brighter.
         NOTE: AnViM then creates files `phs/textResults/0001.csv', `phs/textResults/0002.csv' , etc., for each frame containing information on cells within that frame. At this stage, this file includes morphological information about the cells, including area, centroid, perimeter, orientation, circularity, aspect ratio, roundedness, solidity, distance from the no-cell region. The length unit in these properties is pixels, and the angle is in degrees. Finally, this file is updated to contain cellular pixel intensity, motion, and forces in the subsequent steps.
   3. Part 3: Mapping of the pixel intensities on the cells
      NOTE: Manual inputs in this step include identifying the data directory and selecting mapping properties and parameters. Key previously created files used in this step include `p*/phs/*.tif' (or `p*/fluo/*.tif ') and `p*/phs/bwImages/*.tif'. Key new files produced in this step include `p*/phs/textResults/*.csv', which lists cellular morphological properties. See Figure 11 for the visual description of the following steps to assess the pixel intensities in the region encompassed by individual cells and their neighboring region and define them as properties of the cells.
      1. Start the Fiji software, and from the MSM drop-down menu, select Map on Cells – Intensities.
      2. Using the file browser dialog, select the position directory `analysis/p0', `analysis/p1', etc., that contains properties quantified on regularly spaced grid points.
      3. Select Detect Cell Division or Quantify Cellular Fluorescence when prompted by the software. Define the size of the neighboring region. Check both Collect Properties of the Neighboring Region and Collect Properties of the Cells boxes. Click on OK.
      4. In the Purpose of Recording the Cellular Intensity window, indicate what type of image to be used for intensity mapping, the size of the neighboring region, and whether data is collected for individual cells or both cells and their neighboring regions (Supplementary Figure S11).
         NOTE: Mapping the pixel intensities of a phase-contrast image allows detection of cell division events. Mapping fluorescent image intensities will enable detection of fluctuations in the fluorescently tagged cytoplasmic molecules. The output of the above steps is the mean, median, standard deviation, minimum, and maximum pixel intensity values for individual cells. These numbers are entered as new columns in the files `phs/textResults/0001.csv', `phs/textResults/0002.csv' , etc.
   4. Part 4: Mapping of the forces and motion on the cells
      NOTE: Manual inputs to this step include identifying the data directory and selecting mapping properties and parameters. Key previously created files used in this step include `p*/phs/textResults/*.csv', `p*/velocity/*_vel.dat', `p*/displacement/*_disp.dat', `p*/traction/*_trac.dat', `p*/prestress/*_prestress.dat', and `p*/phs/bwImages/*.tif '. No new files are created during this step. Instead, the new information (cellular force and motion properties) are added to the files `p*/phs/textResults/*.csv '. See Figure 12 for the visual description of the steps to assess the forces and motion in the region encompassed by individual cells and their neighboring region and define them as properties of the cells.
      1. Choose from the MSM drop-down menu Map on Cells – Motion/Force Data (Supplementary Figure S12).
      2. Then, follow the steps listed in step 2.4.3.
         NOTE: New columns are added to the files `phs/textResults/0001.csv', `phs/textResults/0002.csv', etc. and include the mean, median, and standard deviation of speed, the orientation of velocity, average cytoskeletal tension, tension anisotropy, strain energy in the hydrogel, the orientation of highest tension, and magnitude of cell-ECM traction (Supplementary Figure S13).
5. Visualization of results
   1. Part 1: Tracking of the cellular identities across the experiment
      NOTE: Manual inputs to this step include identifying the data directory and selecting mapped properties to visualize. Key previously created files used in this step include `p*/phs/textResults/*.csv'. Key new files produced during this step include `p*/phs/textResults/cellTimeTrace_*.csv', which contains a time trace of the cellular data. See Figure 13 for the visual description of the following steps to track the properties of individual cells over the entire duration of the experiment.
      1. Start the Fiji software, and from the MSM drop-down menu, select Results – Track Data.
      2. Using the file browser dialog, select the position directory `analysis/p0', `analysis/p1', etc., containing cellular properties to be tracked. When done click on Select.
      3. In the Choose Starting Point for Tracking window, choose the starting frame for monitoring, and the number of frames simultaneously tracked (Supplementary Figure S14). Always start from frame number 2 as velocity cannot be determined for frame number 1. When done, click on OK.
      4. In the Check the Variables to Make Tracks window, choose the variables either by typing the variable names or selecting the terms from the checkboxes (Supplementary Figure S15). Then, click on OK.
         NOTE: Tracking generates `phs/textResults/cellTimeTrace_*.csv' files with each column containing a unique cell number and each successive row representing the consecutive time instance.
   2. Part 2: Generation of time tracks of the assessed cellular properties
      NOTE: Manual inputs to this step include identifying the data directory and selecting mapped properties to visualize. Key previously created files used in this step include `p*/phs/textResults/cellTimeTrace_*.csv'. Key new files produced during this step include `p*/phs/trackedDataPlots/*.tif', which contain time track plots and `p*/phs/trackedDataPlots/*.csv', which contain plot data. See Figure 14 for the visual description of the following steps to generate time tracks of the assessed cellular properties.
      1. Start the Fiji software, and from the MSM drop-down menu, select Results – plot.
      2. Using the file browser dialog, select the position directory `analysis/p0', `analysis/p1', etc., containing tracked cellular properties to be plotted.
      3. Choose whether to limit the plotting to cells with unbroken tracks by clicking on the Yes or No button.
         NOTE: This option ignores the cells, which could not be detected in one or more time instances.
      4. Choose the number of variables to be plotted simultaneously and click on OK.
         NOTE: Currently, AnViM allows a maximum of three variables to be displayed in the same plot.
      5. Choose individual variables for plotting using a drop-down menu.
         NOTE: These steps create a tagged image file format (TIFF) file and a comma-separated data file within the `phs/trackedDataPlots/' folder. The filename is composed of variable names separated by an underscore and ends with a cell number.
   3. Part 3: Generation of heat maps of the assessed cellular properties
      NOTE: Manual inputs in this step include identifying the data directory and selecting mapped properties to visualize. Key previously created files used in this step include `p*/phs/textResults/cellTimeTrace_*.csv'. Key new files generated in this step include `p*/phs/segmentedImages/cellPropMaps/*.tif', which are the heatmaps of cellular properties. See Figure 15 for the visual description of the steps to generate heat maps of the assessed cellular properties.
      1. Choose from the MSM drop-down menu Results – Picture.
      2. Follow the steps described in step 2.5.2.
         NOTE: The output is stored as TIFF file files in the `phs/segmentedImages/cellPropMaps/' folder. The filenames are the time instance number and variable name separated by an underscore.