Abstract 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 <it>ScreenMill</it>, a new software suite that automates image analysis and simplifies data review and analysis for high-throughput biological experiments. Results 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. Conclusions <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

Dittmar, John C

Reid, Robert JD

Rothstein, Rodney

English

PubMed

Abstract 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 ScreenMill 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.</p

Rothstein Rodney

Reid Robert JD

Dittmar John C

Directory of Open Access Journals

BMC Bioinformatics

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

Abstract
 
 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 ScreenMill 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.
 </jats:sec

John C Dittmar

Robert JD Reid

Rodney Rothstein

Crossref

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

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. 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. ScreenMill automates quantification, analysis and visualization of high-throughput screen data. The algorithms implemented in ScreenMill 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

Dittmar, John

Reid, Robert J.D.

Rothstein, Rodney Joel

Columbia University Academic Commons

Springer - Publisher Connector

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

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