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Updated: Aug 10, 2026

Single-cell Gene Expression Profiling Using FACS and qPCR with Internal Standards
Published on: February 25, 2017
A calibration method for estimating absolute expression levels from microarray data
Kristof Engelen1, Bart Naudts, Bart De Moor
1BIOI@SCD, Department of Electrical Engineering K.U.Leuven, Kasteelpark Arenberg 10, B-3001 Leuven, Belgium.
Motivation:
We describe an approach to normalize spotted microarray data, based on a physically motivated calibration model. This model consists of two major components, describing the hybridization of target transcripts to their corresponding probes on the one hand, and the measurement of fluorescence from the hybridized, labeled target on the other hand. The model parameters and error distributions are estimated from external control spikes.
Results:
Using a publicly available dataset, we show that our procedure is capable of adequately removing the typical non-linearities of the data, without making any assumptions on the distribution of differences in gene expression from one biological sample to the next. Since our model links target concentration to measured intensity, we show how absolute expression values of target transcripts in the hybridization solution can be estimated up to a certain degree.
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