Optimized Multiple Fluorescence Based Detection in Single Molecule Synthesis Process Under High Noise Level Environment

Abstract

Single molecule sequencing contributes to overall human advancement in the areas including but not limited to genomics, transcriptomics, clinical test, drug development, and cancer screening. Furthermore, fluorescence based sequencing is mostly employed in single molecule sequencing among other methods, specifically in the fields of DNA sequencing. Contemporary fluorescence labeling methods utilize a Charge-coupled Device camera to capture snapshots of multiple pixels on the single molecule sequencing. We propose a method for fluorescence labeling detection with a single pixel, which excels in high accuracy and low resource requirement in the low signal-to-noise ratio conditions. Such a method also benefits from higher throughput compared to others. The context in this study explores the single molecule synthesis process modeling using negative binomial distributions. Also, including the method of maximum likelihood and Viterbi algorithm in this modeling improves signal detection accuracy. The fluorescence-based model is most beneficial to simulate actual experiment processes and to facilitate in understanding the relations between fluorescence emission and signal receiving event.