Microarray quality metrics
Although microarrays are widely used and the interest in expression data is increasing with the appearance of new applications, the assessment of data quality remains a major concern. Microarray data quality can be affected by several factors at each step of the microarray experiment processing. The effects of some variability sources such as dye or gene effects can be corrected by normalisation procedures, whereas others remain there as noise. The assessment of data quality is an integral part of the microarray analysis process.
A tool for quality assessment
The objective of this project is to develop and disseminate quality metrics and tools for determining data quality. We are developing a new Bioconductor package, named arrayQualityMetrics, that provides a HTML report with diagnostic plots for one or dual color microarray data. The quality report contains the evaluation of the individual array quality, the existence of spatial effects, the reproducibility of the experiments, the homogeneity between the experiments, the GC content effects, the mapping of the reporters, the evaluation of the biological signal to noise ratio. This report can be used as a first step of the microarray analysis or to compare the efficiency of different methods of normalisation.
Examples
Here are links to some examples of HTML reports produced by arrayQualityMetrics:
Related Links
If you have any query concerning the package, please contact .