Coincidence between transcriptome analyses on different microarray platforms using a parametric framework

Abstract

A parametric framework for the analysis of transcriptome data is demonstrated to yield coincident results when applied to data acquired using two different microarray platforms. Discrepancies among transcriptome studies are frequently reported, casting doubt on the reliability of collected data. The inconsistency among observations can be largely attributed to differences among the analytical frameworks employed for data analysis. The existing frameworks normalizes data against a standard determined from the data to be analyzed. In the present study, a parametric framework based on a strict model for normalization is applied to data acquired using an in-house printed chip and GeneChip. The framework is based on a common statistical characteristic of microarray data, and each data is normalized on the basis of a linear relationship with this model. In the proposed framework, the expressional changes observed and genes selected are coincident between platforms, achieving superior universality of data compared to other methods.