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BATS: a Bayesian user-friendly software for Analyzing Time Series microarray experiments

Claudia Angelini1*, Luisa Cutillo2, Daniela De Canditiis3, Margherita Mutarelli4 and Marianna Pensky5

Author Affiliations

1 Istituto per le Applicazioni del Calcolo, 'Mauro Picone', CNR-Napoli, Italy

2 Telethon Institute of Genetics and Medicine, Napoli, Italy

3 Istituto per le Applicazioni del Calcolo, 'Mauro Picone', CNR-Roma, Italy

4 Dipartimento di Patologia generale, Seconda Università di Napoli, Italy

5 Department of Mathematics, University of Central Florida, USA

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BMC Bioinformatics 2008, 9:415  doi:10.1186/1471-2105-9-415

Published: 6 October 2008

Abstract

Background

Gene expression levels in a given cell can be influenced by different factors, namely pharmacological or medical treatments. The response to a given stimulus is usually different for different genes and may depend on time. One of the goals of modern molecular biology is the high-throughput identification of genes associated with a particular treatment or a biological process of interest. From methodological and computational point of view, analyzing high-dimensional time course microarray data requires very specific set of tools which are usually not included in standard software packages. Recently, the authors of this paper developed a fully Bayesian approach which allows one to identify differentially expressed genes in a 'one-sample' time-course microarray experiment, to rank them and to estimate their expression profiles. The method is based on explicit expressions for calculations and, hence, very computationally efficient.

Results

The software package BATS (Bayesian Analysis of Time Series) presented here implements the methodology described above. It allows an user to automatically identify and rank differentially expressed genes and to estimate their expression profiles when at least 5–6 time points are available. The package has a user-friendly interface. BATS successfully manages various technical difficulties which arise in time-course microarray experiments, such as a small number of observations, non-uniform sampling intervals and replicated or missing data.

Conclusion

BATS is a free user-friendly software for the analysis of both simulated and real microarray time course experiments. The software, the user manual and a brief illustrative example are freely available online at the BATS website: http://www.na.iac.cnr.it/bats webcite