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Dendrou CA, Fung E, Esposito L, et al. Fluorescence intensity normalisation: correcting for time effects in large-scale flow cytometric analysis. Adv Bioinformatics. 2009;476106doi: 10.1155/2009/476106.
Dendrou, C. A., Fung, E., Esposito, L., Todd, J. A., Wicker, L. S., & Plagnol, V. (2009). Fluorescence intensity normalisation: correcting for time effects in large-scale flow cytometric analysis. Advances in bioinformatics, 476106. https://doi.org/10.1155/2009/476106
Dendrou, Calliope A, et al. "Fluorescence intensity normalisation: correcting for time effects in large-scale flow cytometric analysis." Advances in bioinformatics vol. (2009): 476106. doi: https://doi.org/10.1155/2009/476106
Dendrou CA, Fung E, Esposito L, Todd JA, Wicker LS, Plagnol V. Fluorescence intensity normalisation: correcting for time effects in large-scale flow cytometric analysis. Adv Bioinformatics. 2009;476106. doi: 10.1155/2009/476106. Epub 2009 Nov 17. PMID: 20049162; PMCID: PMC2798117.
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Adv Bioinformatics. 2009;476106. doi: 10.1155/2009/476106. Epub 2009 Nov 17.

Fluorescence intensity normalisation: correcting for time effects in large-scale flow cytometric analysis.

Advances in bioinformatics

Calliope A Dendrou, Erik Fung, Laura Esposito, John A Todd, Linda S Wicker, Vincent Plagnol

Affiliations

  1. Juvenile Diabetes Research Foundation/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, Cambridge Institute for Medical Research, University of Cambridge, Cambridge CB2 0XY, UK.

PMID: 20049162 PMCID: PMC2798117 DOI: 10.1155/2009/476106

Abstract

A next step to interpret the findings generated by genome-wide association studies is to associate molecular quantitative traits with disease-associated alleles. To this end, researchers are linking disease risk alleles with gene expression quantitative trait loci (eQTL). However, gene expression at the mRNA level is only an intermediate trait and flow cytometry analysis can provide more downstream and biologically valuable protein level information in multiple cell subsets simultaneously using freshly obtained samples. Because the throughput of flow cytometry is currently limited, experiments may need to span over several weeks or months to obtain a sufficient sample size to demonstrate genetic association. Therefore, normalisation methods are needed to control for technical variability and compare flow cytometry data over an extended period of time. We show how the use of normalising fluorospheres improves the repeatability of a cell surface CD25-APC mean fluorescence intensity phenotype on CD4(+) memory T cells. We investigate two types of normalising beads: broad spectrum and spectrum matched. Lastly, we propose two alternative normalisation procedures that are usable in the absence of normalising beads.

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