流式细胞术
表达数量性状基因座
数量性状位点
计算生物学
全基因组关联研究
遗传建筑学
表型
生物
细胞仪
重复性
等位基因
基因
遗传学
基因型
单核苷酸多态性
数学
统计
作者
Calliope A. Dendrou,Erik Fung,Laura Esposito,John A. Todd,Linda S. Wicker,Vincent Plagnol
摘要
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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