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Fluorescence Intensity Normalisation: Correcting for Time Effects in Large-Scale Flow Cytometric Analysis
Author(s) -
Calliope A. Dendrou,
Erik Fung,
Laura Esposito,
John A. Todd,
Linda S. Wicker,
Vincent Plagnol
Publication year - 2009
Publication title -
advances in bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.33
H-Index - 20
eISSN - 1687-8035
pISSN - 1687-8027
DOI - 10.1155/2009/476106
Subject(s) - flow cytometry , expression quantitative trait loci , quantitative trait locus , computational biology , genome wide association study , genetic architecture , phenotype , biology , cytometry , repeatability , allele , gene , genetics , genotype , single nucleotide polymorphism , mathematics , statistics
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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