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Please note that, as of 18 July 2017, Microarrays has been renamed to High-Throughput and is now published here.
Article

A Flexible Microarray Data Simulation Model

Microarray Platform, IGBMC, CNRS-INSERM-UdS, 1 rue Laurent Fries, Parc d'Innovation,67400 Illkirch, France
Microarrays 2013, 2(2), 115-130; https://doi.org/10.3390/microarrays2020115
Received: 1 March 2013 / Revised: 7 April 2013 / Accepted: 15 April 2013 / Published: 17 April 2013
Microarray technology allows monitoring of gene expression profiling at the genome level. This is useful in order to search for genes involved in a disease. The performances of the methods used to select interesting genes are most often judged after other analyzes (qPCR validation, search in databases...), which are also subject to error. A good evaluation of gene selection methods is possible with data whose characteristics are known, that is to say, synthetic data. We propose a model to simulate microarray data with similar characteristics to the data commonly produced by current platforms. The parameters used in this model are described to allow the user to generate data with varying characteristics. In order to show the flexibility of the proposed model, a commented example is given and illustrated. An R package is available for immediate use. View Full-Text
Keywords: microarray data; simulation model; R code microarray data; simulation model; R code
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MDPI and ACS Style

Dembélé, D. A Flexible Microarray Data Simulation Model. Microarrays 2013, 2, 115-130. https://doi.org/10.3390/microarrays2020115

AMA Style

Dembélé D. A Flexible Microarray Data Simulation Model. Microarrays. 2013; 2(2):115-130. https://doi.org/10.3390/microarrays2020115

Chicago/Turabian Style

Dembélé, Doulaye. 2013. "A Flexible Microarray Data Simulation Model" Microarrays 2, no. 2: 115-130. https://doi.org/10.3390/microarrays2020115

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