Nucleic Acids Research Advance Access originally published online on July 15, 2008
Nucleic Acids Research 2008 36(15):e97; doi:10.1093/nar/gkn428
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Nucleic Acids Research, 2008, Vol. 36, No. 15 e97
© 2008 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Methods Online |
Functional studies on transfected cell microarray analysed by linear regression modelling
1Department of Cancer Research and Molecular Medicine, 2Department of Mathematical Sciences, Norwegian University of Science and Technology (NTNU), Trondheim and 3Department of Food Science and Medical Technology, Sør-Trøndelag University College, Trondheim, Norway
*To whom correspondence should be addressed. Tel: +47 72 57 30 49; Fax: + 47 72 57 64 00; Email: christina.saten{at}ntnu.no Correspondence may also be addressed to Torunn Bruland. Tel: +47 72 57 30 49; Fax: + 47 72 57 64 00; Email: torunn.bruland{at}ntnu.no
Received March 13, 2008. Revised June 2, 2008. Accepted June 20, 2008.
Transfected cell microarray is a promising method for accelerating the functional exploration of the genome, giving information about protein function in the living cell. The microarrays consist of clusters of cells (spots) overexpressing or silencing a particular gene product. The subsequent analysis of the phenotypic consequences of such perturbations can then be detected using cell-based assays. The focus in the present study was to establish an experimental design and a robust analysis approach for fluorescence intensity data, and to address the use of replicates for studying regulation of gene expression with varying complexity and effect size. Our analysis pipeline includes measurement of fluorescence intensities, normalization strategies using negative control spots and internal control plasmids, and linear regression (ANOVA) modelling for estimating biological effects and calculating P-values for comparisons of interests. Our results show the potential of transfected cell microarrays in studying complex regulation of gene expression by enabling measurement of biological responses in cells with overexpression and downregulation of specific gene products, combined with the possibility of assaying the effects of external stimuli. Simulation experiments show that transfected cell microarrays can be used to reliably detect even quantitatively minor biological effects by including several technical and experimental replicates.