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New statistical algorithms for Monitoring Gene Expression on GeneChip® Probe Arrays

Square experimental design used in the development of the statistical algorithms enabled thorough testing of a large set of transcripts over a broad range of concentrations. (Figure 1)

The Latin Square experimental design was used extensively in the algorithm development process to test a wide range of data sets, including transcript groups of E.coli, S. cerevisiae and H. sapiens . In the human Latin Square, each transcript group was designed to contain one distinct human transcript from 0 to 1024 pM in concentration. These were spiked into a labeled mixture of human RNA where these 14 transcripts showed no expression. In total, 12 transcripts were used to compute the results; two of the transcripts were removed from the final calculations due to low quality. In the yeast Latin Square, each transcript group contained eight different transcripts, labeled and spiked into a mixture of labeled human RNA. After hybridization to Human Genome U95Av2 or Yeast Genome S98 arrays respectively, Affymetrix® Microarray Suite (MAS) 4.0 containing the empirical algorithms and MAS 5.0 containing the new statistical algorithms were used to analyze the data.

In addition to Latin Square experiments, more conventional data sets were generated and analyzed where RNA from different sources was labeled and hybridized to GeneChip® probe arrays, followed by analysis with MAS 4.0 and MAS 5.0.

Results

Comparison of Expression Values Generated by MAS 4.0 and MAS 5.0

Analyses were performed to study the concordance between expression values generated by empirical algorithms (MAS 4.0) and statistical algorithms (MAS 5.0). Experiments performed with human adrenal gland RNA on human genome U95A arrays are shown in Figure 2.

As shown in Figure 2A, when results generated with MAS 4.0 and MAS 5.0 are
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