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J Biomol Screen. 2015 Feb;20(2):230-41. doi: 10.1177/1087057114548853. Epub 2014 Sep 4.

Improving detection of rare biological events in high-throughput screens.

Author information

1
McGill University and Genome Quebec Innovation Centre, Montreal, Quebec, Canada Department of Human Genetics, McGill University, Montreal, Quebec, Canada.
2
Equipe Criblage pour des Molécules Bio-Actives (CMBA), U1038 INSERM/CEA/UJF, CEA Grenoble, Grenoble Cedex 09, France.
3
McGill University and Genome Quebec Innovation Centre, Montreal, Quebec, Canada.
4
Equipe Criblage pour des Molécules Bio-Actives (CMBA), U1038 INSERM/CEA/UJF, CEA Grenoble, Grenoble Cedex 09, France Institut Albert Bonniot, CRI INSERM/UJF U823, Team 3 "Polarity, Development and Cancer," Rond-point de la Chantourne, La Tronche Cedex, France.
5
McGill University and Genome Quebec Innovation Centre, Montreal, Quebec, Canada Department of Human Genetics, McGill University, Montreal, Quebec, Canada robert.nadon@mcgill.ca.

Abstract

The success of high-throughput screening (HTS) strategies depends on the effectiveness of both normalization methods and study design. We report comparisons among normalization methods in two titration series experiments. We also extend the results in a third experiment with two differently designed but otherwise identical screens: compounds in replicate plates were either placed in the same well locations or were randomly assigned to different locations. Best results were obtained when randomization was combined with normalization methods that corrected for within-plate spatial bias. We conclude that potent, reliable, and accurate HTS requires replication, randomization design strategies, and more extensive normalization than is typically done and that formal statistical testing is desirable. The Statistics and dIagnostic Graphs for HTS (SIGHTS) Microsoft Excel Add-In software is available to conduct most analyses reported here.

KEYWORDS:

normalization; randomization; statistical analysis; study design

PMID:
25190066
DOI:
10.1177/1087057114548853
[Indexed for MEDLINE]

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