Experimental design for gene microarray experiments and differential expression analysis


Advances in microarray technology open new challenges in data collection, analysis and interpretation. In this review paper, we focus on issues related to obtaining trustworthy normalized data and results of differential expression analysis. In particular, we briefly summarize discussions on sources of biological and technological variation, experimental design, design of arrays, normalization and error models, differential expression and multiple comparison issues. These issues remain major bottlenecks to developing standards and obtaining useful and applicable results of future analysis such as cluster analysis, network modeling, etc.

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