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Correction of technical bias in clinical microarray data improves concordance with known biological information
Aron Charles Eklund and Zoltan Szallasi
Genome Biology 2008, 9:R26

Abstract: 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.

The authors are in the Cancer systems biology group at CBS.



Publication links:

The R package bias for correction of technical bias

The latest version is 0.0.5, last updated March 13, 2012. See also the squash package for visualization with colorgrams.

Links to raw data unavailable from GEO:

R code to reproduce results:

Raw data ("AffyBatch" objects in R data format):




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