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DepthTools: an R package for a robust analysis of gene expression data

Aurora Torrente12*, Sara López-Pintado34 and Juan Romo5

Author Affiliations

1 Functional Genomics Team, European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK

2 Departamento de Ciencia e Ingeniería de Materiales e Ingeniería Química, Universidad Carlos III de Madrid, Av Universidad, 30, 28911, Leganés, Spain

3 Mailman School of Public Health, Columbia University, 722 West 168th Street, NY 10032, New York, USA

4 Departamento de Economía, Métodos Cuantitativos e Historia Económica, Universidad Pablo de Olavide, Carretera de Utrera, Km 1, 41013, Sevilla, Spain

5 Departamento de Estadística, Universidad Carlos III de Madrid, C/ Madrid, 126, 28903, Getafe, Spain

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BMC Bioinformatics 2013, 14:237  doi:10.1186/1471-2105-14-237

Published: 25 July 2013

Abstract

Background

The use of DNA microarrays and oligonucleotide chips of high density in modern biomedical research provides complex, high dimensional data which have been proven to convey crucial information about gene expression levels and to play an important role in disease diagnosis. Therefore, there is a need for developing new, robust statistical techniques to analyze these data.

Results

depthTools is an R package for a robust statistical analysis of gene expression data, based on an efficient implementation of a feasible notion of depth, the Modified Band Depth. This software includes several visualization and inference tools successfully applied to high dimensional gene expression data. A user-friendly interface is also provided via an R-commander plugin.

Conclusion

We illustrate the utility of the depthTools package, that could be used, for instance, to achieve a better understanding of genome-level variation between tumors and to facilitate the development of personalized treatments.

Keywords:
Data depth; Robustness; R package; R commander plug-in