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Abstract Background Despite the widespread use of microarrays, much ambiguity regarding data analysis, interpretation and correlation of the different technologies exists. There is a considerable amount of interest in correlating results obtained between different microarray platforms. To date, only a few cross-platform evaluations have been published and unfortunately, no guidelines have been established on the best methods of making such correlations. To address this issue we conducted a thorough evaluation of two commercial microarray platforms to determine an appropriate methodology for making cross-platform correlations. Results In this study, expression measurements for 10,763 genes uniquely represented on Affymetrix U133A/B GeneChips® and Amersham CodeLink™ UniSet Human 20 K microarrays were compared. For each microarray platform, five technical replicates, derived from the same total RNA samples, were labeled, hybridized, and quantified according to each manufacturers' standard protocols. The correlation coefficient (r) of differential expression ratios for the entire set of 10,763 overlapping genes was 0.62 between platforms. However, the correlation improved significantly (r = 0.79) when genes within noise were excluded. In addition to levels of inter-platform correlation, we evaluated precision, statistical-significance profiles, power, and noise levels for each microarray platform. Accuracy of differential expression was measured against real-time PCR for 25 genes and both platforms correlated well with r values of 0.92 and 0.79 for CodeLink and GeneChip, respectively. Conclusions As a result of this study, we recommend using only genes called 'present' in cross-platform correlations. However, as in this study, a large number of genes may be lost from the correlation due to differing levels of noise between platforms. This is an important consideration given the apparent difference in sensitivity of the two platforms. Data from microarray analysis need to be interpreted cautiously and therefore, we provide guidelines for making cross-platform correlations. In all, this study represents the most comprehensive and specifically designed comparison of short-oligonucleotide microarray platforms to date using the largest set of overlapping genes.

Parkinson's disease pathogenesis proceeds through several phases, culminating in the loss of dopaminergic neurons of the substantia nigra (SN). Although the 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) model of oxidative SN injury is frequently used to study degeneration of dopaminergic neurons in mice and non-human primates, an understanding of the temporal sequence of molecular events from inhibition of mitochondrial complex 1 to neuronal cell death is limited. Here, microarray analysis and integrative data mining were used to uncover pathways implicated in the progression of changes in dopaminergic neurons after MPTP administration. This approach enabled the identification of small, yet consistently significant, changes in gene expression within the SN of MPTP-treated animals. Such an analysis disclosed dysregulation of genes in three main areas related to neuronal function: cytoskeletal stability and maintenance, synaptic integrity, and cell cycle and apoptosis. The discovery and validation of these alterations provide molecular evidence for an evolving cascade of injury, dysfunction, and cell death. [ABSTRACT FROM AUTHOR]

Standard controls and best practice guidelines advance acceptance of data from research, preclinical and clinical laboratories by providing a means for evaluating data quality. The External RNA Controls Consortium (ERCC) is developing commonly agreed-upon and tested controls for use in expression assays, a true industry-wide standard control.