Vala Sciences

Above is a screenshot highlighting the sophisticated tools of the image viewer in one place. The Image Viewer should be used to adjust the settings of the image analysis to improve the performance of the automated algorithms for each assay. Cell-by-cell image and segmentation data are shown. This example displays the nuclear (blue) and whole cell (yellow) edge masks in addition to the RNA (green) interior mask. Original nuclear image data is also shown (blue).

Optimizing the performance of CyteSeer ViewRNA : CyteSeer ViewRNA ’s default setting (Nuclear Size =10, Nuclear Sensitivity = 100, RNA Sensitivity = 100) are appropriate for digital microscopy workstations utilizing 20X objectives, and for images captured with typical digital cameras. While these settings are likely to be very good for most circumstances, users are encouraged to run test analyses at various settings, to further optimize CyteSeer ViewRNA for their systems.

The nuclear channel image from well E15 of the PMA vs. IL8 tutorial data set is shown in the upper left, and lower left panels for reference. The middle panels show the Nuclear Mask Edges image for well E15 produced by CyteSeerTM-ViewRNA with the nuclear size specified as either 5 (upper row), or 16, lower row, using the default setting for the Nuclear Sensitivity (100%) and RNA Sensitivity (100%). The right panels show the Whole Cell Mask Edges image for the two analyses, which indicates the boundaries of the cells as estimated by the program.

Recognizing the nuclei: For optimal data analysis, CyteSeer ViewRNA must identify the position of each nucleus in the nuclear image for every field of view. To help CyteSeer ViewRNA recognize the nuclei of different cell types and at different magnifications, and different overall staining intensities, two user- adjustable controls are provided relevant to the nuclear images. These are the expected Nuclear Size, and the Nuclear Sensitivity adjustments.
Adjusting the expected Nuclear Size value: A number between 1 and 99 can be entered into the Nuclear Size field in CyteSeer ViewRNA ’s main menu. These numbers do not correspond to an exact physical dimension of the nucleus, but – instead – are relative. To illustrate how the nuclear size adjustment works, load the PMA vs. IL8 tutorial data set into CyteSeer ViewRNA, specify a new output folder (name it NS5Nuc100RNA100), set the Nuclear Size to 5 (the Nuclear and RNA Sensitivities should both be at 100%), select well E15 for analysis and run the program. Next, specify a new output folder (name it NS16Nuc100RNA100), set the Nuclear Size to 16, and run the program on well E15 again. Use the Image Viewer to determine how well the program did at identifying the nuclei. The two images are shown side by side in Figure 15. The Nuclear Mask Edges image shows the boundary circles for the nuclei identified by CyteSeer ViewRNA . For the Nuclear Size 5 analysis, many of the original nuclei are subdivided into two or more circles in the Nuclear Mask Edges image. Thus, Nuclear Size 5 is too low a value for this cell type and magnification. To confirm this, call up the Whole Cell Mask Edges image for E15 from the NS5Nuc100RNA100 folder, which displays the boundaries of the cells as estimated by the program (the upper right image in the figure above); many very small shapes are shown that are too small to represent authentic cells and many cell boundary lines cross nuclei (some are sectioned into 2 or even 4 cells).

    Next bring up the Nuclear Mask Edges and Whole-Cell Mask Edges images for the analysis with Nuclear Size 16 (from the folder NS16Nuc100RNA100). The Nuclear Mask Edges images features single circles at the position of nearly every authentic nuclei in the field of view (lower middle panel, figure 15), indicating that the program performed correctly. Furthermore, the cell boundaries are appropriately sized and rarely cross nuclei. Thus, for the tutorial data set, a Nuclear Size of 16 will result in accurate cell counts, and an accurate count of the number of RNA spots per cell. Thus, if CyteSeer ViewRNA is “splitting” nuclei in the images from your samples, enter a larger number for the Nuclear Size.

Using a higher number for the Nuclear Sensitivity may result in the recognition of fewer nuclei.

Recognizing the RNA spots from the Panomics QuantiGene assay: The ability of the CyteSeer ViewRNA to analyze the RNA image can be adjusted using the RNA Sensitivity feature. As the number entered for this parameter increases, so will number of spots counted by the program. However, the risk of also quantifying small image artifacts as authentic RNA spots also increases as the value entered for this parameter increases.

To illustrate the effects of changing the RNA Sensitivity factor in recognizing the RNA spots, the image from well G15, of the PMA vs. IL8 tutorial set was analyzed at RNA Sensitivity setting of 100, 50, and 200 and the results are shown below. An RNA Sensitivity setting of 100 – which is the default – did an excellent job of recognizing the individual spots that make up the RNA image for well G15. Increasing the sensitivity by using a setting of 200 increased the number of spots that were recognized, but also introduced what were likely to be artifacts into the analysis. Fewer artifacts were found when reducing RNA Sensitivity setting to 50, but may have missed some of the authentic spots.

There are likely to be two distinct philosophies about RNA spot recognition. Some biologists are likely to adjust the settings very carefully, so that the spot pattern produced by CyteSeer ViewRNA most exactly matches what they see when looking through their microscope or at images, using all of the image enhancement tools at their disposal. The RNA Sensitivity tool along with the nuclei recognition tools described elsewhere can certainly be used to optimize the program in this manner. Another philosophy, which may be preferred by researchers performing screening assays, may be to select RNA Sensitivity parameters that yield the greatest separation between certain experimental conditions. For example – reducing the sensitivity might diminish the number of “false positives” in a large screen. In any event, it is very easy to run CyteSeer ViewRNA repeatedly on the same image sets, to determine the settings that are right for your purpose.