Selecting Reliable mRNA Expression Measurements Across Platforms Improves Downstream Analysis

In this study, we propose a statistical framework for selecting reliable measurements between platforms by modeling the correlations of mRNA expression levels using a beta-mixture model. The model-based selection provides an effective and objective way to separate good probes from probes with low quality, thereby improving the efficiency and accuracy of the analysis. The proposed method can be used to compare two microarray technologies or microarray and RNA sequencing measurements. We tested the approach in two matched profiling data sets, using microarray gene expression measurements from the same samples profiled on both Affymetrix and Illumina platforms. We also applied the algorithm to mRNA expression data to compare Affymetrix microarray data with RNA sequencing measurements. The algorithm successfully identified probes/genes with reliable measurements. Removing the unreliable measurements resulted in significant improvements for gene signature development and functional annotations.
Source: Cancer Informatics - Category: Cancer & Oncology Authors: Source Type: research