Microarray Data Integration: Frameworks and a List of Underlying Issues
Chintanu Kumar Sarmah,
Microarray technology is expanding rapidly providing an extensive as well as promising source of data for better addressing complex questions involving biological processes. The ever increasing number and publicly available gene expression studies of human and other organisms provide strong motivation to carry out cross-study analyses. Besides, microarray technology provides several platforms to investigators that include arrays from commercial vendors like Affymetrix® (Santa Clara, CA, USA), Agilent® (Palo Alto, CA, USA), and other proprietorial arrays of various laboratories. Integration of multiple studies that are based on the same technological platform, or, combining data from different array platforms carries the potential towards higher accuracy, consistency and robust information mining. The integrated result often allows constructing a more complete and broader picture. In this work, we highlight as well as exemplify two frameworks of microarray data integration approaches that are in practice. This follows a discussion on the important issues that may influence any microarray data integration attempt. The review, in general, intends to serve as a starting point for those interested in exploring this area of microarray study, while realizing the pertinent issues underneath.
Keywords: Data integration, issues, microarrays, microarray technology, review, polymerase chain reaction, Chemistry, molecular biology, organisms, cross-study analysis, Bioconductor, lung adenocarcinoma samples, lymph node status, breast cancer, diluting, Repositories, disease, tumor, diagnosis, drug development, genomics
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