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Differential expression analyses were conducted using the LIMMA (Linear Models for Microarray Analysis) package from the Bioconductor project [12].
A Bayesian moderated t-test was applied to identify differentially expressed genes as implemented in the LIMMA (linear models for microarray analysis) package [27] from Bioconductor.
Standard deviations of the logarithm of fold change values were also estimated using the limma (Linear Models for Microarray Analysis) package [41].
For data visualisation, the heat maps of gene expression were created by importing relevant subsets of RMA processed microarray gene expression data into the dChip v1.3 microarray analysis package (http://www.biostat.harvard.edu/complab/dchip/).edu/complab/dchip/
Data was normalised by variance stabilizing normalization (VSN; [78]) and differentially expressed genes were detected using the 'Limma' (Linear Models for Microarray Analysis) package [79]; implementing the empirical Bayes linear modelling approach [80].
Software implementing these methods has been included in the widely used TM4 microarray analysis package.
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Some microarray analysis packages present systematically the results of several classification methods for a single data set.
Analysis of gene expression data was performed using the Bioconductor microarray analysis packages in R [ 112] and GeneSpring GX 7.3.1 (Agilent, Santa Clara, CA).
Probe-pairs from the gDNA.cel files were selected using a.cel file parser script [ 31] which produces a probe-mask file (.cdf) compatible with a range of microarray analysis packages and containing only probe-pairs in which the perfect-match probe has a gDNA hybridisation intensity greater than the user defined gDNA hybridisation threshold [ 22].
Probe pairs were identified in which the perfect match (PM) probe has a gDNA hybridization intensity greater than the user-defined threshold and were selected using a.cel file parser script (http://affymetrix.arabidopsis.info/xspecies/), which produces a probe mask file (.cdf) compatible with a range of microarray analysis packages (e.g., Genespring; Agilent Technologies).
Data was analyzed using Genespring microarray analysis software package (Agilent Technologies, Palo Alto, CA).
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