This page contains supplementary material for:
Correction of technical bias in clinical microarray data
improves concordance with known biological
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.
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):