临床微阵列数据中技术偏差的校正提高了与已知生物学信息的一致性。
Correction of technical bias in clinical microarray data improves concordance with known biological information.
作者信息
Eklund Aron C, Szallasi Zoltan
机构信息
Children's Hospital Informatics Program at the Harvard-MIT Division of Health Sciences and Technology (CHIP@HST), Harvard Medical School, Boston, MA 02115, USA.
出版信息
Genome Biol. 2008;9(2):R26. doi: 10.1186/gb-2008-9-2-r26. Epub 2008 Feb 4.
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.
摘要
基因表达微阵列的性能已通过对照参考样本得到了充分表征，但在临床样本上的性能仍不太明确。我们确定了共同影响许多基因的技术偏差来源，从而在临床数据集中导致虚假相关性以及基因与临床变量之间的错误关联。我们开发了一种方法来校正临床微阵列数据中的技术偏差，该方法提高了与多个数据集中已知生物学关系的一致性。
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