Microarray Meta-Analysis and Cross-Platform Normalization: Integrative Genomics for Robust Biomarker Discovery

Microarrays

Christopher J. Walsh¹  Pingzhao Hu²  Jane Batt¹  Claudia C. Dos Santos¹ 

[1] Keenan and Li Ka Shing Knowledge Institute of Saint Michael’s Hospital, Toronto ON M5B 1W8, Canada; E-Mails:;Department of Biochemistry and Medical Genetics, University of Manitoba, Winnipeg R3E 0J9, MB, Canada; E-Mail:

关键词: microarray platform;    meta-analysis;    normalization;    biomarker;   

DOI  :  10.3390/microarrays4030389

来源: mdpi

【 摘 要 】

The diagnostic and prognostic potential of the vast quantity of publicly-available microarray data has driven the development of methods for integrating the data from different microarray platforms. Cross-platform integration, when appropriately implemented, has been shown to improve reproducibility and robustness of gene signature biomarkers. Microarray platform integration can be conceptually divided into approaches that perform early stage integration (cross-platform normalization) versus late stage data integration (meta-analysis). A growing number of statistical methods and associated software for platform integration are available to the user, however an understanding of their comparative performance and potential pitfalls is critical for best implementation. In this review we provide evidence-based, practical guidance to researchers performing cross-platform integration, particularly with an objective to discover biomarkers.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.