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BMC Research Notes

, 3:277

Microarray normalization and optimization

Abstract

BackgroundThe increasing number of methodologies and tools currently available to analyse gene expression microarray data can be confusing for non specialist users.

FindingsBased on the experience of biostatisticians of Institut Curie, we propose both a clear analysis strategy and a selection of tools to investigate microarray gene expression data. The most usual and relevant existing R functions were discussed, validated and gathered in an easy-to-use R package EMA devoted to gene expression microarray analysis. These functions were improved for ease of use, enhanced visualisation and better interpretation of results.

ConclusionsStrategy and tools proposed in the EMA R package could provide a useful starting point for many microarrays users. EMA is part of Comprehensive R Archive Network and is freely available at http:-bioinfo.curie.fr-projects-ema-.

Electronic supplementary materialThe online version of this article doi:10.1186-1756-0500-3-277 contains supplementary material, which is available to authorized users.

Nicolas Servant, Eleonore Gravier contributed equally to this work.

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Autor: Nicolas Servant - Eleonore Gravier - Pierre Gestraud - Cecile Laurent - Caroline Paccard - Anne Biton - Isabel Brito - Jona

Fuente: https://link.springer.com/







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