Identifying Single Feature Polymorphisms Using Affymetrix Gene Expression Data

• Activity Number: 359
• Type: Contributed
• Date/Time: Tuesday, August 2, 2011 : 10:30 AM to 12:20 PM
• Sponsor: Biometrics Section
• Author(s): Cumhur Yusuf Demirkale*+
• Companies: University of Maryland, Baltimore
• Keywords: Affymetrix Gene Chips ; Linear Mixed Models ; Microarrays ; Outliers ; Robust Methods ; Single Feature Polymorphisms

Abstract

In microarray data analysis, the identification of Single Feature Polymorphisms (SFPs) is important for producing more accurate expression measurements when comparing samples of different genotypes. Also, portions of DNA that differ between parental lines can serve as markers for tracking DNA inheritance in offspring. We summarize several SFPs discovery methods in the literature. To identify single probe defining SFPs in the data, we developed two new algorithms where a difference value is defined for each probe after accounting for the overall gene expression level differences in the probe set. First method contrasts the difference value of each probe with the average of the difference values for the rest of the probes in that probe set. Second method is a robust version of the first method. The performances of all methods are compared through two publicly available published data sets, where truth about the sequence polymorphism is known for some "Gold Standard" probes.