The most commonly utilized microarrays for mRNA profiling (Affymetrix) include probe sets of a series of perfect match and mismatch probes (typically 22 oligonucleotides per probe set). There are an increasing number of reported probe set algorithms that differ in their interpretation of a probe set to derive a single normalized signal representative of expression of each mRNA. These algorithms are known to differ in accuracy and sensitivity, and optimization has been done using a small set of standardized control microarray data. We hypothesized that different mRNA profiling projects have varying sources and degrees of confounding noise, and that these should alter the choice of a specific probe set algorithm. Also, we hypothesized that use of the Microarray Suite (MAS) 5.0 probe set detection p-value as a weighting function would improve the performance of all probe set algorithms.