Producing gene expression data using microarray technology is an elaborate process with many potential sources of variability. Standard sample preparation protocols include a number of qualitative assessments meant to insure that good quality RNA is used in the hybridization experiments. Following hybridization and image processing, each microarray chip provides a wealth of information that can be used to assess the quality of the data. Recommended post hybridization quality assessment include general image quality assessment and analysis of intensity measures of specialized probes. We propose to describe some quality assessment procedures and quality control criteria. We aim at using much of data on the chip to assess its quality and compare two different microarray projects for detecting differences in quality assessment criteria of gene expression data with two sample t-tests statistic. For data from independent projects and samples the two sample t-tests appear more useful for the statistical analysis.
Quality assessment, Gene expression and Microarray
