Table 4.

ANOVA results

Platform	Affymetrix (RMA)	Affymetrix (MAS5)	Agilent	Illumina
Concentration effect	2.48	2.77	4.53	2.19
Probe effect	0.54	0.55	0.44	0.38
Array effect	0.17	0.17	0.19	NA
Measurement error	0.47	0.72	0.69	0.54
Probe imbalance	0	0	3.60	0
Array imbalance	0	0	0	1059.67

To understand the variability contributed by differences in nominal concentrations, probe effect and array, we fitted a three-way ANOVA model containing only main effects to the expression values from the spike-in transcripts. The estimated SD of each effect is shown in the first three rows. The fourth row shows the SD of the error term. Finally, a measure of the amount of confounding between nominal concentration and the other two effects is included in rows five and six. We use the measure presented by Wu (17). An optimal design, such as a Latin Square, will have a measure of 0 for each imbalance. The more confounding the larger these values. Note, the large imbalance due to array in the Illumina design. In this experiment array and nominal concentration were completely confounded. However, because the array effect is small (the arrays are normalized) this was not as much of a problem. In the Agilent experiment, there is a small amount of confounding between probe and concentration because a Latin Square design was used with a single concentration/gene combination missing.