A significant problem in quantifying microscopic foci such as stress granules and P-bodies is the unambiguous identification of what is a “real” foci, versus something that is artifactual. Additionally, the intensity of a stress granule foci relative to the background can also be variable, including between cells; this is a frequent problem in yeast live cell microscopy.
To combat these issues, Ilya Shabanov developed a freely available tool called HARLEY which runs in the chrome browser, and which allows intuitive user-based model training to reproducibly and automatically identify foci of interest in yeast. This is particularly important as user reproducibility in foci quantification is far from perfect, as we discovered based on testing multiple users reproducibility in scoring stress granules. Numerous other tools relating to foci quantification, including extensive co-localization metrics, are also part of the HARLEY package.
We hope to expand HARLEY’s applicability to other biological models in the future.
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