Mathematical Problems in Engineering
Volume 2012 (2012), Article ID 182758, 12 pages
Research Article

Robust Gene Expression Index

Department of Statistics, Middle East Technical University, 06531 Ankara, Turkey

Received 10 October 2011; Accepted 22 October 2011

Academic Editor: Gerhard-Wilhelm Weber

Copyright © 2012 Vilda Purutçuoǧlu. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The frequentist gene expression index (FGX) was recently developed to measure expression on Affymetrix oligonucleotide DNA arrays. In this study, we extend FGX to cover nonnormal log expressions, specifically long-tailed symmetric densities and call our new index as robust gene expression index (RGX). In estimation, we implement the modified maximum likelihood method to unravel the elusive solutions of likelihood equations and utilize the Fisher information matrix for covariance terms. From the analysis via the bench-mark datasets and simulated data, it is shown that RGX has promising results and mostly outperforms FGX in terms of relative efficiency of the estimated signals, in particular, when the data are nonnormal.