Statistical models discriminating between complex samples measured with microfluidic receptor-cell arrays.

摘要: Data analysis for flow-based in-vitro receptomics array, like a tongue-on-a-chip, is complicated by the relatively large variability within and between arrays, transfected DNA types, spots, cells spots. Simply averaging responses of spots same type would lead to high variances low statistical power. This paper presents an approach based on linear mixed models, allowing quantitative robust comparison complex samples indicating which receptors are responsible any differences. These models easily extended take into account additional effects such as build-up cell stress combine data from replicated experiments. The increased analytical power this brings research discussed.