Machine Learning Enabled Decoding of Color-coded Droplet Arrays and Its Application in Multiplex Digital Nucleic Acid Analysis / 分析化学

ABSTRACT

To address the throughput limitations of digital nucleic acid analysis,a tricolor combination-based droplet coding technique was developed to achieve multiplex digital nucleic acid analysis with flexible throughput expansibility.To improve the analysis efficiency,a machine learning-based method was further developed for automatic decoding of color-coded droplet array.The machine learning algorithm empowered the computer program to automatically extract the color-position-quantity information of the droplets.By correlating this color-position-quantity of droplets before and after nucleic acid amplification,the proportion of positive droplets for each target was rapidly determined.This droplet decoding strategy was applied to multiplex digital nucleic acid analysis.The experimental results demonstrated that this droplet decoding method was fast and accurate,with a decoding process completed within 2 min.Furthermore,the droplet identification accuracy exceeded 99%.Additionally,the obtained nucleic acid quantification results exhibited a good correlation(R2＞0.99)with those reported by a commercial digital PCR instrument.