Correction of technical bias in clinical microarray data improves concordance with known biological information
1 Children's Hospital Informatics Program at the Harvard-MIT Division of Health Sciences and Technology (CHIP@HST), Harvard Medical School, Boston, MA 02115, USA
2 Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, DK-2800 Lyngby, Denmark
Genome Biology 2008, 9:R26 doi:10.1186/gb-2008-9-2-r26Published: 4 February 2008
The performance of gene expression microarrays has been well characterized using controlled reference samples, but the performance on clinical samples remains less clear. We identified sources of technical bias affecting many genes in concert, thus causing spurious correlations in clinical data sets and false associations between genes and clinical variables. We developed a method to correct for technical bias in clinical microarray data, which increased concordance with known biological relationships in multiple data sets.