Objective: Microarray-based signatures for clinical application are often plagued by processing variability or batch effects that compromise the robustness of the test performance.
Methods: A splice variant array-based signature for early detection of Alzheimer's disease (AD) was developed using 315 AD or normal subjects processed in three disparate microarray batches.
Results: A modified top scoring pair classifier using the signature, is robust to batch effects and outperforms other common classifiers, with sensitivity and specificity of 88.3% (95% CI:81.2%, 93.4%) and 88.9% (95% CI:65.3%, 98.6%), respectively, on an independent cohort.
Conclusions: This splice-variant array-based signature shows promise for clinical diagnostic use in AD.
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| http://dx.doi.org/10.3109/1354750X.2013.773083 | DOI Listing |
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