光学精密工程2018，Vol.26Issue(3)：647-653,7.DOI:10.3788/OPE.20182603.0647
微滴式数字PCR中低浓度荧光微滴分类
Identification of florescent droplets at low concentrations for droplet digital PCR
摘要
Abstract
In the digital Polymerase Chain Reaction(dPCR) detection process,discriminating positive droplets from negative ones directly affect the final concentration,which is one of the important factors affecting the accuracy of the instrument.Current methods do not take into account the influence of sample concentration on the result error,resulting in a larger deviation from the actual results at a low concentration.In this paper,a florescent droplets classification method was designed based on generalized Pareto distribution.It was discussed that the possible effects of misclassification at different concentrations on the results,determined the high quantiles of generalized Pareto distribution,and verified the proposed method on the self-made droplet digital PCR.Experimental results showed that for the method proposed,the linear regression of samples with target copies from 5 to 5000 got an r2 =0.995 6 and a detection limit of less than 5 copies/samples,while that of the comparison method was less than 50 copies/sample.These results indicate that the proposed method improves the lower detection limit of the droplet digital PCR by oneorder,and can achieve automated droplet classification at ultra-low concentration.关键词
数字PCR/广义帕累托分布/荧光微滴分类Key words
digital PCR/generalized Pareto distribution/florescent droplets classification分类
信息技术与安全科学引用本文复制引用
刘聪,董文飞,张涛,周武平,蒋克明,黎海文..微滴式数字PCR中低浓度荧光微滴分类[J].光学精密工程,2018,26(3):647-653,7.基金项目
中国科学院科研装备研制资助项目(No.YZ201444) （No.YZ201444）
苏州市科技发展计划资助项目(No.SYG201503) （No.SYG201503）
