Clustering is an important tool in microarray data analysis. This unsupervised learning technique is commonly used to reveal structures hidden in large gene expression data sets. The vast majority of clustering algorithms applied so far produce hard partitions of the data, i.e. each gene is assigned exactly to one cluster. Hard clustering is favourable if clusters are well separated. However, this is generally not the case for microarray time-course data, where gene clusters frequently overlap. Additionally, hard clustering algorithms are often highly sensitive to noise. To overcome the limitations of hard clustering, we applied soft clustering which offers several advantages for researchers. First, it generates accessible internal cluster structures, i.e. it indicates how well corresponding clusters represent genes. This can be used for the more targeted search for regulatory elements. Second, the overall relation between clusters, and thus a global clustering structure, can be defined. Additionally, soft clustering is more noise robust and a priori pre-filtering of genes can be avoided. This prevents the exclusion of biologically relevant genes from the data analysis. Soft clustering was implemented here using the fuzzy c-means algorithm. Procedures to find optimal clustering parameters were developed. A software package for soft clustering has been developed based on the open-source statistical language R. The package called Mfuzz is freely available.

SUMMARY Data from a previous study suggested that peripheral blood monocytes in patients with rheumatoid arthritis (RA) may be activated. Therefore, in this study we sought further evidence of ‘presynovial’ activation of monocytes. Our results show that phenotypic changes are demonstrable in peripheral blood monocytes in patients with RA, including increased expression of CR3 (CDllb/CD18) and FcRI (CD64). However, changes are most extensive in synovial monocytes/macrophages and especially for HLA‐DR and intercellular adhesion molecule‐1 (ICAM‐1) (CD54). We conclude that monocyte/macrophage activation is most evident within the joint, and that ‘presynovial’ changes occur but are of limited extent.

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