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Correction of technical bias in clinical microarray data improves concordance with known biological information.

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.

SUBMITTER: Eklund AC

PROVIDER: S-EPMC2374720 | biostudies-literature | 2008

REPOSITORIES: biostudies-literature

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Correction of technical bias in clinical microarray data improves concordance with known biological information.

Eklund Aron C AC Szallasi Zoltan Z

Genome biology 20080204 2

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 relatio ...[more]

PMID: 18248669

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