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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
biochemistry, genetics and molecular biology
Assessment of reliability of microarray data and estimation of signal thresholds using mixture modeling
Nucleic Acids Research, Volume 32, No. 8, Year 2004
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Description
DNA microarray is an important tool for the study of gene activities but the resultant data consisting of thousands of points are error-prone. A serious limitation in microarray analysis is the unreliability of the data generated from low signal intensities. Such data may produce erroneous gene expression ratios and cause unnecessary validation or post-analysis follow-up tasks. In this study, we describe an approach based on normal mixture modeling for determining optimal signal intensity thresholds to identify reliable measurements of the microarray elements and subsequently eliminate false expression ratios. We used univariate and bivariate mixture modeling to segregate the microarray data into two classes, low signal intensity and reliable signal intensity populations, and applied Bayesian decision theory to find the optimal signal thresholds. The bivariate analysis approach was found to be more accurate than the univariate approach; both approaches were superior to a conventional method when validated against a reference set of biological data that consisted of true and false gene expression data. Elimination of unreliable signal intensities in microarray data should contribute to the quality of microarray data including reproducibility and reliability of gene expression ratios. © Oxford University Press 2004; all rights reserved.
Authors & Co-Authors
Asyali, Musa H.
Saudi Arabia, Riyadh
King Faisal Specialist Hospital and Research Centre
Shoukri, Mohamed M.
Saudi Arabia, Riyadh
King Faisal Specialist Hospital and Research Centre
Demirkaya, Omer
Saudi Arabia, Riyadh
King Faisal Specialist Hospital and Research Centre
Khabar, Khalid S.A.
Saudi Arabia, Riyadh
King Faisal Specialist Hospital and Research Centre
Statistics
Citations: 40
Authors: 4
Affiliations: 1
Identifiers
Doi:
10.1093/nar/gkh544
ISSN:
03051048
Research Areas
Genetics And Genomics
Study Design
Cohort Study