A case study on the identification of confounding factors for gene disease association analysis.

Abstract excerpt

Variation in the expression of genes arises from a variety of sources. It is important to remove sources of variation between arrays of non-biological origin. Non-biological variation, caused by lurking confounding factors, usually attracts little attention, although it may substantially influence the expression profile of genes. In this study, we proposed a method which is able to identify the potential...

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