Robust gene expression index
type: Item
instance of: scholarly article
title: Robust gene expression index
zbMATH Open document ID: 1264.92019
DOI: 10.1155/2012/182758
author: Vilda Purutçuoğlu
published in: Mathematical Problems in Engineering
publication date: 2013-06-11T00:00:00Z
review text: Summary: The frequentist gene expression index (FGX) was recently developed to measure expressions of Affymetrix oligonucleotide DNA arrays. We extend FGX to cover non-normal log expressions, specifically long-tailed symmetric densities and call our new index as a robust gene expression index (RGX). In the estimation, we implement the modified maximum likelihood method to unravel the elusive solutions of the likelihood equations and utilize the Fisher information matrix for covariance terms. From the analysis via the bench-mark data sets and simulated data, it is shown that RGX gives promising results and mostly outperforms FGX in terms of relative efficiency of the estimated signals, in particular, when the data are non-normal.
Mathematics Subject Classification ID: 92C40
Mathematics Subject Classification ID: 92D10
Mathematics Subject Classification ID: 62P10
zbMATH DE Number: 6173076
Wikidata QID: Q58912550
describes a project that uses: BGX
describes a project that uses: gcrma
describes a project that uses: Affycomp III
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2012/182758
OpenAlex ID: W2036567128
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description: scientific article; zbMATH DE number 6173076