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main:imageselectionmodel [2017/04/10 17:05] 127.0.0.1 external edit |
main:imageselectionmodel [2017/08/04 13:58] bshirley |
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====== Image selection model ====== | ====== Image selection model ====== | ||
- | An image selection model is a series of filters which exclude undesirable images within a sample from use in [[main: | + | An image selection model is a series of filters which exclude undesirable images within a sample from use in [[main: |
===== Apply an image selection model ===== | ===== Apply an image selection model ===== | ||
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+ | ===== Suggested procedure for creating a new image selection model ===== | ||
+ | 1. Load a set of processed calibration and test samples. | ||
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+ | 2. Create a [[main: | ||
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+ | 3. To create new Image Exclusion Filter thresholds: Examine distributions to find thresholds (as +S.D. above or below the mean value for the test) that can be applied to the majority of samples that remove a subset of images. This should be based on outlier values that distinguish the majority of images for a test from rarer images. For example, we expect 46 chromosomes in a metaphase cell. Most images will contain <60 objects (chromosomes + nuclei). Images with >60 objects are infrequent and are more likely to indicate excessive sister chromatid separation or multiple metaphase cells, or a lot of debris may be present. | ||
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+ | 4. To test a threshold for a test, open the [[main: | ||
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+ | 5. Repeat step 4 for the other tests that you wish to apply to the data. The filtering is cumulative: images that are removed by one test, if selected for removal by another, will not be repeatedly eliminated. | ||
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+ | 6. After all of the image selection filters have been determined, then decide whether additional thresholds are required based on sorting. The combined Z score or [[main: | ||
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+ | 7. Save the combined image selection model on the “apply image selection model” window by selecting “Save Current User Customized Model” and assigning a name to the model. Hint: assign a model name that describes the filters used in the model for future reference. The model name will appear in you list of models that can be applied to future samples. | ||
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+ | 8. Note: After Z score based thresholding, | ||
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+ | 9. [[main: | ||
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