<p>This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p> <p>Post-normalization checking of microarrays rarely occurs, despite the problems that using unreliable data for inference can cause. This paper considers a number of
different ways to check microarrays after normalization for a variety of potential
problems. Four types of problem with microarray data that these checks can
identify are: clerical mistakes, array-wide hybridization problems, problems with
normalization and mishandling problems. Any of these can seriously affect the results
of any analysis. The three main techniques used to identify these problems are
dimension reduction techniques, false array plots and correlograms. None of the
techniques are computationally very intensive and all can be carried out in the <italic>R</italic>
statistical package. Once discovered, problems can either be rectified or excluded
from the data.</p>
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Comp Funct Genomics. 2003 Oct; 4(5):460-467