18 research outputs found

    Non-linear analysis of GeneChip arrays

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    The application of microarray hybridization theory to Affymetrix GeneChip data has been a recent focus for data analysts. It has been shown that the hyperbolic Langmuir isotherm captures the shape of the signal response to concentration of Affymetrix GeneChips. We demonstrate that existing linear fit methods for extracting gene expression measures are not well adapted for the effect of saturation resulting from surface adsorption processes. In contrast to the most popular methods, we fit background and concentration parameters within a single global fitting routine instead of estimating the background before obtaining gene expression measures. We describe a non-linear multi-chip model of the perfect match signal that effectively allows for the separation of specific and non-specific components of the microarray signal and avoids saturation bias in the high-intensity range. Multimodel inference, incorporated within the fitting routine, allows a quantitative selection of the model that best describes the observed data. The performance of this method is evaluated on publicly available datasets, and comparisons to popular algorithms are presented

    Explaining differences in saturation levels for Affymetrix GeneChip® arrays

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    The experimental spike-in studies of microarray hybridization conducted by Affymetrix demonstrate a nonlinear response of fluorescence intensity signal to target concentration. Several theoretical models have been put forward to explain these data. It was shown that the Langmuir adsorption isotherm recapitulates a general trend of signal response to concentration. However, this model fails to explain some key properties of the observed signal. In particular, according to the simple Langmuir isotherm, all probes should saturate at the same intensity level. However, this effect was not observed in the publicly available Affymetrix spike-in data sets. On the contrary, it was found that the saturation intensities vary greatly and can be predicted based on the probe sequence composition. In our experimental study, we attempt to account for the unexplained variation in the observed probe intensities using customized fluidics scripts. We explore experimentally the effect of the stringent wash, target concentration and hybridization time on the final microarray signal. The washing effect is assessed by scanning chips both prior to and after the stringent wash. Selective labeling of both specific and non-specific targets allows the visualization and investigation of the washing effect for both specific and non-specific signal components. We propose a new qualitative model of the probe-target hybridization mechanism that is in agreement with observed hybridization and washing properties of short oligonucleotide microarrays. This study demonstrates that desorption of incompletely bound targets during the washing cycle contributes to the observed difference in saturation levels

    Using expression arrays for copy number detection: an example from E. coli-6

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    <p><b>Copyright information:</b></p><p>Taken from "Using expression arrays for copy number detection: an example from E. coli"</p><p>http://www.biomedcentral.com/1471-2105/8/203</p><p>BMC Bioinformatics 2007;8():203-203.</p><p>Published online 14 Jun 2007</p><p>PMCID:PMC1914360.</p><p></p> panel shows signal before transformation (raw data), lower panel shows signal after transformation (grey dots) and result of fit to the HMM (black solid line)

    Using expression arrays for copy number detection: an example from E. coli-0

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    <p><b>Copyright information:</b></p><p>Taken from "Using expression arrays for copy number detection: an example from E. coli"</p><p>http://www.biomedcentral.com/1471-2105/8/203</p><p>BMC Bioinformatics 2007;8():203-203.</p><p>Published online 14 Jun 2007</p><p>PMCID:PMC1914360.</p><p></p
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