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Background  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  ScreenMill , a new software suite that automates image analysis and simplifies data review and analysis for high-throughput biological experiments.    Results  The  ScreenMill , software suite includes three software tools or "engines": an open source  Colony Measurement Engine  ( CM Engine ) to quantitate colony growth data from plate images, a web-based  Data Review Engine  ( DR Engine ) to validate and analyze quantitative screen data, and a web-based  Statistics Visualization Engine  ( SV Engine ) 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  DR Engine  and  SV Engine  can be used to visualize and analyze other types of quantitative high-throughput data.    Conclusions   ScreenMill  automates quantification, analysis and visualization of high-throughput screen data. The algorithms implemented in S creenMill  are transparent allowing users to be confident about the results  ScreenMill  produces. Taken together, the tools of  ScreenMill  offer biologists a simple and flexible way of analyzing their data, without requiring programming skills.

ScreenMill: A freely available software suite for growth measurement, analysis and visualization of high-throughput screen data