Fuzzy clustering of the expression data along seed development series. The six clusters showing the expression patterns during Arabidopsis seed development. The gene expression values were standardized to have a mean value of zero and a standard deviation of one for each gene profile. The transformed expressions were then clustered using the fuzzy c-means (FCM) clustering algorithm implemented in the Bioconductor Mfuzz package . Based on preliminary analysis, we found six clusters can well represent different expression patterns inherent in the dataset, and another FCM parameter m = 1.75. A membership value in the range of 0-1 was assigned in clustering and the cluster cores consisting of genes with membership value > = 0.90 were coloured pink.
Peng and Weselake BMC Genomics 2011 12:286 doi:10.1186/1471-2164-12-286