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基于液滴的数字 PCR 分析中体积分布不均匀的统计分析。

Statistical Analysis of Nonuniform Volume Distributions for Droplet-Based Digital PCR Assays.

机构信息

Department of Chemistry , University of Washington , Seattle , Washington 98195-1700 , United States.

出版信息

J Am Chem Soc. 2019 Jan 30;141(4):1515-1525. doi: 10.1021/jacs.8b09073. Epub 2019 Jan 15.

Abstract

We present a method to determine the concentration of nucleic acids in a sample by partitioning it into droplets with a nonuniform volume distribution. This digital PCR method requires no special equipment for partitioning, unlike other methods that require nearly identical volumes. Droplets are generated by vortexing a sample in an immiscible oil to create an emulsion. PCR is performed, and droplets in the emulsion are imaged. Droplets with one or more copies of a nucleic acid are identified, and the nucleic acid concentration of the sample is determined. Numerical simulations of droplet distributions were used to estimate measurement error and dynamic range and to examine the effects of the total volume of droplets imaged and the shape of the droplet size distribution on measurement accuracy. The ability of the method to resolve 1.5- and 3-fold differences in concentration was assessed by using simulations of statistical power. The method was validated experimentally; droplet shrinkage and fusion during amplification were also assessed experimentally and showed negligible effects on measured concentration.

摘要

我们提出了一种通过将样品分配到具有不均匀体积分布的液滴中来确定样品中核酸浓度的方法。与需要几乎相同体积的其他方法不同,这种数字 PCR 方法不需要用于分配的特殊设备。通过在不混溶的油中涡旋样品来产生液滴以形成乳液。进行 PCR,并对乳液中的液滴进行成像。鉴定出含有一个或多个核酸拷贝的液滴,并确定样品中的核酸浓度。使用液滴分布的数值模拟来估计测量误差和动态范围,并研究成像的液滴总体积和液滴尺寸分布的形状对测量精度的影响。通过使用统计功效的模拟来评估该方法分辨 1.5 倍和 3 倍浓度差异的能力。该方法已通过实验验证;在扩增过程中液滴的收缩和融合也通过实验进行了评估,结果表明对测量浓度的影响可以忽略不计。

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