Robust Gene Expression Index

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2012-01-01

Author

Purutçuoğlu Gazi, Vilda

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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.

Subject Keywords

Oligonucleotide arrays, Probabilistic model, Estimators, Networks

URI

https://hdl.handle.net/11511/36348

Journal

MATHEMATICAL PROBLEMS IN ENGINEERING

DOI

https://doi.org/10.1155/2012/182758

Collections

Department of Statistics, Article

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Citation Formats

V. Purutçuoğlu Gazi, “Robust Gene Expression Index,” MATHEMATICAL PROBLEMS IN ENGINEERING, pp. 0–0, 2012, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/36348.