期刊
GENOME BIOLOGY
卷 9, 期 2, 页码 -出版社
BMC
DOI: 10.1186/gb-2008-9-2-r26
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资金
- NATIONAL CANCER INSTITUTE [P50CA089393] Funding Source: NIH RePORTER
- NATIONAL LIBRARY OF MEDICINE [R21LM008823] Funding Source: NIH RePORTER
- NCI NIH HHS [P50 CA089393] Funding Source: Medline
- NLM NIH HHS [R21 LM008823, R21LM008823-01A1] Funding Source: Medline
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.
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