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Normalisation of multicondition cDNA macroarray data

Lookup NU author(s): Nicola Dawes, Professor Jarka Glassey

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Abstract

Background. Normalisation is a critical step in obtaining meaningful information from the high-dimensional DNA array data. This is particularly important when complex biological hypotheses/questions, such a functional analysis and regulatory interactions within biological systems, are investigated. A nonparametric, intensity-dependent normalisation method based on global identification of self-consistent set (SCS) of genes is proposed here for such systems. Results. The SCS normalisation is introduced and its behaviour demonstrated for a range of user-defined parameters affecting sits performance. It is compared to a standard global normalisation method in terms of noise reduction and signal retention. Conclusions. The SCS normalisation results using 16 macroarray data sets from a Bacillus subtilis experiment confirm that the method is capable of reducing undesirable experimental variation whilst retaining important biological information. The ease and speed of implementation mean that this method can be easily adapted to other multicondition time/strain series single colour array data.

Publication metadata

Author(s): Dawes N, Glassey J

Publication type: Article

Publication status: Published

Journal: Comparative and Functional Genomics

Year: 2007

Volume: 2007

Pages: Article ID 90578 (12 pages)

Print publication date: 01/02/2007

ISSN (print): 1531-6912

ISSN (electronic): 1532-6268

Publisher: Hindawi Publishing Corp.

URL: http://dx.doi.org/10.1155/2007/90578

DOI: 10.1155/2007/90578

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