Get acquainted with Vala's CyteSeer automated cell image analysis software. More detailed information on automated cell imaging applications, kits and more powerful software techniques can be found in the articles section of our website.
If you run into any problems with installation or licensing, please contact technical support at email@example.com or 1-858-461-6861.
CyteSeer Main Window
Download, install and launch CyteSeer from your Mac, Windows or Linux workstation. Most features are accessed from this CyteSeer main window.
Choose which algorithm to run from the drop down list. We chose a straightforward cell-by-cell ploidy analysis for this quick start example.
Use CyteSeer Supported Formats
Make sure your images conform to a naming format available within CyteSeer. CyteSeer can read most standard tif images with the generic and free-form naming conventions. We also support many standard formats from other microscopy, image cytometry and high-content analysis vendors. The conventions help clearly define which image correlates to which field, well and fluorescent dye during analysis. Vala actively expands the list of standard supported formats. If your system isn't natively supported, please let us know.
Choose Source and Destination Directory
Browse your local or network file system for the appropriate source and destination directories. Source and Destination Folders can – but are not required to – be the same.
Source Directory: Browse to the directory storing the unprocessed images.
Destination Directory: The Destination Directory is where CyteSeer will save the results.
Example Data Available Online: Example complete data-sets are available in the Software-->Downloads section of the Vala website.
CyteSeer Image and Data Viewing is Free: You can explore complete data-sets inside CyteSeer for free. For most data-sets, point CyteSeer's source directory to the "plate" folder – i.e. Adipocytes_Lipid – and destination directory to the "Results" folder – i.e. Adipocytes_Lipid/Results.
Define How Many Image Within Each Well to Analyze
Define how many 'Images Within Well' are to be analyzed. 'Images Across' and 'Images Down' refers to how many image fields were acquired within a given well. Though CyteSeer tends to name functions with respect to well plates, any collection of images from custom plate or microscope slides can be used.
Use The Run Button to Start an Analysis
Click the 'Run' button and wait for the analysis to complete. By default, all the wells CyteSeer finds in the Source Directory will be analyzed.
Getting an Active 'Run' button: An indication one of the earlier steps was not completed properly is the Run button is disabled or if the 'Wells to Run Algorithm On' box is empty. It's likely that the incorrect image naming convention is selected or that either the source or destination directories were not set correctly.
CyteSeer Analyses Require a License: The 'Run' button will not complete new analyses without a license for CyteSeer. CyteSeer will automatically connect you to the Vala Sciences website to automatically generate a demo license key. If you do have a license, browse to the where that file saved on your workstation to put it in use.
Analysis Progress Shown on the Bottom of the Main Window: A CyteSeer analysis creates image masks for regions of the cell (viewable via View -> Images -> Set Colors) and cell-by-cell numeric data (viewable via View -> Data) as part of it's "Run". The bottom of the main screen will generally display the current status of the current run in progress.
View Results in the Image & Data Viewers: If a run is complete, view your results in the image and data viewers.
There are reasons to make changes to other available parameters like Computational Cluster Size, Minimum Nuclear Size, Pre-Filter, Thresholding & Sensitivity but these can be left in their default values as a starting point.
In general, the sensitivity and the nuclear size parameters are the main parameters that require adjustment for routine analyses. Increasing the sensitivity will generally grow the size of the relevant image mask. Decreasing the nuclear size will help CyteSeer consider two nearby nuclei independently.
View Image or View Data
Now that a basic analysis is complete, CyteSeer provides two major sets of tools to further inspect the data.
Inspect your image or numeric data through the View menu.
1) The Image Viewer allows careful study of how the raw images and masks created by CyteSeer algorithms compare. If the default image analysis parameters are unsatisfactory, we will have to make changes to the algorithm (i.e. nuclear size or sensitivity).
2) If the raw images and masks match up as expected by eye, we use the Data Viewer to see how well these more qualitative judgements correlate with numeric results.
The Cell According to CyteSeer
All CyteSeer analyses start by breaking down each image into core biological component masks for cells & tissues and then aggregates measurements as needed for experiments with many slides, wells, plates etc.
1) First, CyteSeer identifies all of the nuclei available from the nuclear images. A nuclear mask for each cell is established where the mask contains all of the pixels locations automatically identified as nuclear for a given cell.
2) Next, CyteSeer analyzes a second image – a lipid droplet image in this example –such that the lipid droplets are assigned to the lipid droplet mask. A rich set of data parameters are then calculated on a “per cell basis”.
3) Third, CyteSeer tries to define the cell boundaries. This varies from assay to assay. It can be done by cell border, cell membrane or – as in this case – by roughly estimating which droplets belong to which cell.
View different wells at different times with the image viewer. Click on 'B04' to see the images in B04.
View Images and Image Masks in the Image Viewer
The 'Set Colors" dialog controls a central powerful aspect of CyteSeer.
The original images from your microscope are visually combined with the masks generated by CyteSeer. The masks are the result of CyteSeer's automated cell analysis engine and all the numeric data are derived from these masks. If you want to count how lipid droplets (green) there are on a cell by cell basis, you'll want to visually check how well the masks match the original images. In this example, we're looking at a nuclear stain in blue and a lipid droplet stain in green. Masks outlining the edge of the nucleus and lipid droplets are shown in red and green respectively. The yellow lines define the cell regions and show the unique cell ID for each cell that CyteSeer finds.
No image processing is perfect over every cell in every image, but this image viewer allows you to get a feel for how well the current analysis settings are working.
How Well Do the Masks Match the Unprocessed Images?
In the image above, an overlay of yellow and red outlines of the automatically generated masks of the nuclei and lipids are shown.
Due to variable staining and imaging conditions, an algorithm's sensitivity may need adjusting.
Adjust sensitivity and nuclear size first: If the masks do not meet expectations, then the images need to be reprocessed with new sensitivity and/or nuclear size settings. This is repeated heuristically until the you are either satisfied with how well the algorithm is generating a representative mask or decide that a more sophisticated algorithm is required.
Develop new algorithms yourself or with Vala's help: CyteSeer has an integrated graphically driven algorithm development tool available for advanced users. Vala also actively works with many groups to develop and deploy new algorithms.
Adjust Sensitivity and Size to Get Better Masks
As imaging conditions vary wildly from sample to sample and system to system, it often makes sense to rerun the samples with a different sensitivity and/or size value on the main CyteSeer window.
If CyteSeer creates masks that are too small for certain parts of the cell, the sensitivity is too low. If the mask area is too large, the sensitivity is too high. In routine use, CyteSeer will likely work best with a sensitivities of 25% to 400%.
The size values most often refer to nuclear size. If CyteSeer breaks clearly single nuclei into multiple nuclei, the size value is too low. If two nearby nuclei are counted as one, the size value is too large. In routine use, CyteSeer will likely work best with a nuclear sizes from 3 to 30.
CyteSeer Organizes Data by Cell, Well and Plate
CyteSeer automatically identifies every cell in the microscope image set and creates a rich set of numeric data for every cell describing it's size, shape and intensity.
The "Well Data" tab looks at each well individually.
1) Select one or more wells of interest
2) Select one or more measurements of interest
3) View a table or graph of measurements for every cell in every well you've chosen
View Every Measurement for Every Cell
1) Set up gates only if you need them. Gating is a very powerful way to optimize many experiments but isn't always required.
2) Choose the set of measurements. We're looking at counting the number of lipid droplets in this example.
3) View the measurement for every cell. i.e. Cell ID 5 has 4 lipid droplets.
In the 'Well Plate Data' tab of the Data Viewer Click 'Create Bar Graphs'
1) Create, update or edit a plate map with information for your experiment. This can be anything that helps describe your data from concentration to time points.
2) Select the condition.
3) Click the measurement to create a bar graph to the right. Note the error bars and average values.
Please explore our Vala applications and CyteSeer tutorials section of the website for more detail on what else can be done. If what you're looking for isn't there, please don't hesitate to contact us with more detailed answers.
Vala Sciences Contact Information
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