Quality control

In Expression Atlas, quality control of data from all microarray technologies (Affymetrix, Agilent and Illumina) is done using the ‘arrayQualityMetrics’ R package.

Quality control of microarray data begins with the visual inspection of the scanned microarray images to make sure that there are no obvious splotches, scratches or blank areas (4).

After feature extraction, the data analysis software packages can be used to make diagnostic plots (for example of background signal, average intensity values and percentage of genes above background) to help identify problematic arrays, reporters or samples (Figure 6).

Examples of quality control plots made when analysing differential expression data in Expression Atlas
Figure 6 Examples of quality control plots made when analysing differential expression data in Expression Atlas. Left to right: Array intensity distributions, PCA plot, density estimates. See the Expression Atlas help pages for an explanation of what each of these plots represents.