Validation of consensus between proteomic and clinical chemistry datasets by applying a new randomisation F-test for generalised procrustes analysis

Abstract

The use of proteomic data for compound characterisation and toxicity prediction has recently gathered much interest in the pharmaceutical industry, particularly with the development of new high-throughput proteomic techniques such as surface-enhanced laser desorption/ionisation time of flight mass spectrometry (SELDI-ToF) mass spectrometry. To validate these techniques, comparison with established methods such as clinical chemistry endpoints is required; however, there is currently no statistical method available to assess whether the proteomic data describes the same toxicological information as the clinical chemistry data. In this paper, generalised procrustes analysis (GPA) is applied to obtain a consensus between SELDI-ToF data and clinical chemistry data, both obtained from a study of cholestasis in rats. The significance of the consensus and the dimension of the consensus space are diagnosed by a newly developed randomisation F-test method for GPA [Food Qual. Pref. 13 (2002) 191]. Two kinds of matching were considered, using individual animals or treatment groups as samples in GPA. The results show that the SELDI-ToF data has significant consensus with clinical chemistry data, and that the consensus can be visualised in the significant dimensions of group average space.