| Summary: | <p>Abstract</p> <p>Background</p> <p>Many high-throughput genomic experiments, such as Synthetic Genetic Array and yeast two-hybrid, use colony growth on solid media as a screen metric. These experiments routinely generate over 100,000 data points, making data analysis a time consuming and painstaking process. Here we describe <it>ScreenMill</it>, a new software suite that automates image analysis and simplifies data review and analysis for high-throughput biological experiments.</p> <p>Results</p> <p>The <it>ScreenMill</it>, software suite includes three software tools or "engines": an open source <it>Colony Measurement Engine </it>(<it>CM Engine</it>) to quantitate colony growth data from plate images, a web-based <it>Data Review Engine </it>(<it>DR Engine</it>) to validate and analyze quantitative screen data, and a web-based <it>Statistics Visualization Engine </it>(<it>SV Engine</it>) to visualize screen data with statistical information overlaid. The methods and software described here can be applied to any screen in which growth is measured by colony size. In addition, the <it>DR Engine </it>and <it>SV Engine </it>can be used to visualize and analyze other types of quantitative high-throughput data.</p> <p>Conclusions</p> <p><it>ScreenMill </it>automates quantification, analysis and visualization of high-throughput screen data. The algorithms implemented in S<it>creenMill </it>are transparent allowing users to be confident about the results <it>ScreenMill </it>produces. Taken together, the tools of <it>ScreenMill </it>offer biologists a simple and flexible way of analyzing their data, without requiring programming skills.</p>
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