HTS-Corrector: software for the statistical analysis and correction of experimental high-throughput screening data

Motivation: High-throughput screening (HTS) plays a central role in modern drug discovery, allowing for testing of >100 000 compounds per screen. The aim of our work was to develop and implement methods for minimizing the impact of systematic error in the analysis of HTS data. To the best of our...

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Bibliographic Details
Published inBioinformatics Vol. 22; no. 11; pp. 1408 - 1409
Main Authors Makarenkov, Vladimir, Kevorkov, Dmytro, Zentilli, Pablo, Gagarin, Andrei, Malo, Nathalie, Nadon, Robert
Format Journal Article
LanguageEnglish
Published Oxford Oxford University Press 01.06.2006
Oxford Publishing Limited (England)
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Summary:Motivation: High-throughput screening (HTS) plays a central role in modern drug discovery, allowing for testing of >100 000 compounds per screen. The aim of our work was to develop and implement methods for minimizing the impact of systematic error in the analysis of HTS data. To the best of our knowledge, two new data correction methods included in HTS-Corrector are not available in any existing commercial software or freeware. Results: This paper describes HTS-Corrector, a software application for the analysis of HTS data, detection and visualization of systematic error, and corresponding correction of HTS signals. Three new methods for the statistical analysis and correction of raw HTS data are included in HTS-Corrector: background evaluation, well correction and hit-sigma distribution procedures intended to minimize the impact of systematic errors. We discuss the main features of HTS-Corrector and demonstrate the benefits of the algorithms. Availability: The Microsoft Windows version and a detailed description of the software are freely available at the following URL: Contact:makarenkov.vladimir@uqam.ca
Bibliography:istex:6D7AD86FFCD5C1855075489724FD0FE1EC63F28C
Associate Editor: Jonathan Wren
To whom correspondence should be addressed.
ark:/67375/HXZ-NHVBK8KX-2
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ISSN:1367-4803
1460-2059
1367-4811
DOI:10.1093/bioinformatics/btl126