Accurate estimates of microarray target concentration from a simple sequence-independent Langmuir model

Microarray technology is a commonly used tool for assessing global gene expression. Many models for estimation of target concentration based on observed microarray signal have been proposed, but, in general, these models have been complex and platform-dependent. We introduce a universal Langmuir mod...

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Bibliographic Details
Published in:PloS one 2010-12, Vol.5 (12), p.e14464-e14464
Main Authors: Gharaibeh, Raad Z, Fodor, Anthony A, Gibas, Cynthia J
Format: Article
Language:English
Subjects:
Acids
Analysis
Arrays
Bioinformatics
Biotechnology
Calibration
Complexity
Computational Biology - methods
Computer applications
Databases, Genetic
DNA microarrays
Experiments
Gene expression
Gene Expression Profiling
Gene Expression Regulation
Genes
Genetics and Genomics/Bioinformatics
Genetics and Genomics/Genomics
Genomics
Humans
Hybridization
Mathematical models
Models, Genetic
Models, Statistical
Nucleic Acid Hybridization
Oligonucleotide Array Sequence Analysis - methods
Parameters
Platforms
Quality control
Reproducibility of Results
RNA, Messenger - metabolism
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Summary:Microarray technology is a commonly used tool for assessing global gene expression. Many models for estimation of target concentration based on observed microarray signal have been proposed, but, in general, these models have been complex and platform-dependent. We introduce a universal Langmuir model for estimation of absolute target concentration from microarray experiments. We find that this sequence-independent model, characterized by only three free parameters, yields excellent predictions for four microarray platforms, including Affymetrix, Agilent, Illumina and a custom-printed microarray. The model also accurately predicts concentration for the MAQC data sets. This approach significantly reduces the computational complexity of quantitative target concentration estimates. Using a simple form of the Langmuir isotherm model, with a minimum of parameters and assumptions, and without explicit modeling of individual probe properties, we were able to recover absolute transcript concentrations with high R(2) on four different array platforms. The results obtained here suggest that with a "spiked-in" concentration series targeting as few as 5-10 genes, reliable estimation of target concentration can be achieved for the entire microarray.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0014464