While other tools such as Ilastik ( Berg et al., 2019) and Advanced Cell Classifier ( Piccinini et al., 2017) can provide a GUI for training classifiers with image-based data, these do not include data exploration and visualization tools like those in CellProfiler Analyst. The software includes several tools for users to visualize and filter their datasets, alongside tools for training machine learning classifier models within a convenient graphical user interface that is geared toward working with image data ( Dao et al., 2016). CellProfiler Analyst is a data exploration package for helping users to explore and extract information from large datasets, including (but not limited to) those produced by CellProfiler pipelines ( Jones et al., 2008). Spreadsheet programs are familiar but lack features and integration with source images that biologists often need. Free software packages such as ImageJ ( Schneider et al., 2012) and CellProfiler ( McQuin et al., 2018) allow users to extract hundreds or thousands of numerical measurements from their image data, but it is ultimately on the user to determine which of these features are relevant to the biological problem being investigated. This necessitates automated computational analysis to efficiently derive biological insights from the raw data. With the increasing adoption of high-throughput microscopy, scientists have been able to generate large datasets containing thousands of individual images.
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