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Bioinformatics Advance Access originally published online on April 4, 2006
Bioinformatics 2006 22(11):1408-1409; doi:10.1093/bioinformatics/btl126
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© The Author 2006. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

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

Vladimir Makarenkov 1,*, Dmytro Kevorkov 1, Pablo Zentilli 1, Andrei Gagarin 1, Nathalie Malo 2 and Robert Nadon 2

1 Departement d'informatique, Université du Québec à Montreal C.P.8888, suc.Centre-Ville, Montreal, QC, H3C 3P8, Canada
2 McGill University and Genome Quebec Innovation Centre 740 Dr Penfield, Montreal, QC, H3A 1A4, Canada

*To whom correspondence should be addressed.

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: http://www.labunix.uqam.ca/~makarenv/hts.html

Contact: makarenkov.vladimir{at}uqam.ca

Received on February 9, 2006; revised on March 20, 2006; accepted on March 28, 2006

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V. Makarenkov, P. Zentilli, D. Kevorkov, A. Gagarin, N. Malo, and R. Nadon
An efficient method for the detection and elimination of systematic error in high-throughput screening
Bioinformatics, July 1, 2007; 23(13): 1648 - 1657.
[Abstract] [Full Text] [PDF]


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