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This example using an image from monkey muscle images (courtesy Tatiana Kostrominova). This is an RGB images in which the laminin is visualized in the green channel, and the myosin isoform is visualized in the red channel. There is no information in the blue channel, but that’s ok. This figure is a screenshot of the image loaded into CyteSeer.

All of the images from the monkey data set in the same directory, so there are multiple lines in the “Wells to run Algorithm On” field (A01, A02, etc.). These files are named using the Vala “Generic naming” convention (Monkey_A01f01d1.tif). Though this can be useful for organization, files don't have to be named like this. CyteSeer recognizes most common formats and names tif, jpg, gif etc. via the “Free Form RGB Image” choice from the drop down choices under “Naming Conventions” in the main menu.

CyteSeer’s main menu. See that I’ve chosen the “Skeletal Muscle Algorithm” in the “Algorithm to run” field. The "Results Folder " will be set automatically but this can be set to any folder. This example uses “single” images from a sample,  as opposed to the “tiled” images we get from well plates, when run on an automated system. Make sure that the “Images Within Well” “Images Across” = 1, and “Images Down” =1, and the “Computational Cluster Size” is also set to “Images Across” =1, and “Images down” =1.

Importantly, when you chose the Skeletal Muscle algorithm, CyteSeer immediately assumes that you may wish to analyze both fiber size, utilizing the fiber outlines, and the expression of a protein of interest. There are two fields to correctly assign in the “Channel Folder” column (one for “Skeletal Muscle” – the top choice), and one for the channel which contains the information relevant to the protein of interest (Protein 1). Since your images use the green channel for the fiber outline, I chose the green channel from the “pull down” menu within the Channel Folder field for the “Skeletal Muscle” line. Since the myosin is visualized on the red channel, I chose the “red channel” option for protein 1. For this example, I selected just chose one of the images to analyze (the top image, labeled A01). I pressed the “run” button, and CyteSeer analyzed the image in less than 10 seconds.

Analysis of the fibers by CyteSeer for the first monkey image. Notice on the “zoomed” portion of the figure, on the right panel, that fiber #130 is red and fiber #128 is not.

OK… so we have the masks… but how to get to the data? I chose the “View Data’ from the main menu. Next, I chose the Well Data Tab to display the large Data Table.

Next, I chose just a few of the dozens of data parameters from the menu.

You can do this manually in two steps:
1) Click "Uncheck All" followed by "Update"
2) Search for the measurements you'd like to use via the "Show" checkboxes and click "Update". The measurements displayed are updated in real-time as you type in your search term.

All data tables displayed on this screen are exportable to comma separated values (csv) files with the "Export" button.

Also note the "Cell ID Count:" is 303/303 [100%]. This means CyteSeer has found 303 fibers in this image.

I find creating a custom measurement set via the "All Measurements" a better option for any analysis performed more than once.

Custom measurement sets are useful so that you don't have to find your measurements over an over again. Once we select "Ok" on this screen, we'll have a new measurement set available on the "All Measurements" drop-down menu named "Muscle Set 1".

Select "Muscle Set 1" and click "Update".

For this example, I've selected:
Area of Fiber Mask (Area Fm): It is the best estimate of the area (in pixels) for the skeletal muscle fiber
Average Pixel Intensity for Protein-1 of the Fiber Mask (API Pi-1 Fm): The myosin is visualized in the red channel

Note that the API for fiber 130 is 212, and fiber 130 was bright red, whereas API for fiber 128 is just 56, which is low. In fact, the value of 56 is about at background – though API is as low as 45 or so for certain fibers. Thus, Fiber #130 would be scored as positive for the myosin isoform, whereas Fiber #128 is negative.

The upper left panel of this data tables window allows you to find just the myosin positive fibers.
To do this:
1) Click the "New" button
2) Name the gate something appropriate. I've chosen "Myosin Positive" here.
3) Select the measurement of interest. In this example, we'll use the same Average Pixel Intensity of Protein-1 Image on Fiber Mask (API Pi-1 Fm)
4) Select greater than ">" 100 as your "Actual Value".
5) Click "Ok" to save the gate

Select this newly created gate and click the "Gated" button. Two thing happen here.
1) The "Cell ID Count:" now reads 83/303 [27.4%]. This is the myosin positive fiber count!
2) The data table displays data from myosin positive fibers only. Note that Fiber #130 is still shown, as expected.

The myosin positive fiber count may be the final numeric result but the gates are available in CyteSeer galleries as well.
1) From the main window, goto View --> Data --> Well Data --> Display Cell Gallery
2) Select the "Myosin Positive" gate and click "Gated" to visualize a gallery on myosin positive fibers. The lower left image is fiber #130.

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Many thanks to Tatiana Kostrominova at Indiana University for her invaluable work on this project.