Correlation test to assess low-level processing of high-density oligonucleotide microarray data

Background: There are currently a number of competing techniques for low-level processing of oligonucleotide array data. The choice of technique has a profound effect on subsequent statistical analyses, but there is no method to assess whether a particular technique is appropriate for a specific data set, without reference to external data. Results: We analyzed coregulation between genes in order to detect insufficient normalization between arrays, where coregulation is measured in terms of statistical correlation. In a large collection of genes, a random pair of genes should have on average zero correlation, hence allowing a correlation test. For all data sets that we evaluated, and the three most commonly used low-level processing procedures including MAS5, RMA and MBEI, the housekeeping-gene normalization failed the test. For a real clinical data set, RMA and MBEI showed significant correlation for absent genes. We also found that a second round of normalization on the probe set le...

• Type: Journal
• Year: 2005
• Where: BMCBI
• Authors: Alexander Ploner, Lance D. Miller, Per Hall, Jonas Bergh, Yudi Pawitan
• Keywords: Average Zero Correlation, BMCBI 2005, Low-level Processing, Specific Data