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ScreenMill: A freely available software suite for growth measurement, analysis and visualization of high-throughput screen data
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 descr...
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2010
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2909220/ https://www.ncbi.nlm.nih.gov/pubmed/20584323 http://dx.doi.org/10.1186/1471-2105-11-353 |
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author | Dittmar, John C Reid, Robert JD Rothstein, Rodney |
author_facet | Dittmar, John C Reid, Robert JD Rothstein, Rodney |
author_sort | Dittmar, John C |
collection | PubMed |
description | 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. |
format | Text |
id | pubmed-2909220 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-29092202010-07-24 ScreenMill: A freely available software suite for growth measurement, analysis and visualization of high-throughput screen data Dittmar, John C Reid, Robert JD Rothstein, Rodney BMC Bioinformatics Software 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. BioMed Central 2010-06-28 /pmc/articles/PMC2909220/ /pubmed/20584323 http://dx.doi.org/10.1186/1471-2105-11-353 Text en Copyright ©2010 Dittmar et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Software Dittmar, John C Reid, Robert JD Rothstein, Rodney ScreenMill: A freely available software suite for growth measurement, analysis and visualization of high-throughput screen data |
title | ScreenMill: A freely available software suite for growth measurement, analysis and visualization of high-throughput screen data |
title_full | ScreenMill: A freely available software suite for growth measurement, analysis and visualization of high-throughput screen data |
title_fullStr | ScreenMill: A freely available software suite for growth measurement, analysis and visualization of high-throughput screen data |
title_full_unstemmed | ScreenMill: A freely available software suite for growth measurement, analysis and visualization of high-throughput screen data |
title_short | ScreenMill: A freely available software suite for growth measurement, analysis and visualization of high-throughput screen data |
title_sort | screenmill: a freely available software suite for growth measurement, analysis and visualization of high-throughput screen data |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2909220/ https://www.ncbi.nlm.nih.gov/pubmed/20584323 http://dx.doi.org/10.1186/1471-2105-11-353 |
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