Sequencing by Emergence (SEQE) is a new single-molecule nucleic acid (DNA/RNA) sequencing technology that estimates sequence as an emergent property of the binding and localization of a repertoire of short oligonucleotide probes. SEQE promises to deliver accurate, ultra-long, haplotype-phased reads at the whole genome-scale for very low cost within 10 minutes. The data SEQE generates requires entirely new inference techniques. In this paper we introduce a probabilistic model of the SEQE measurement process and an algorithm that estimates sequence by solving a convex relaxation of the corresponding maximum likelihood problem. We demonstrate the effectiveness of our algorithm on a variety of simulated datasets.

翻译：(SEQE)是一种新型的单分子核核酸(DNA/RNA)测序技术,该技术将测序作为小型寡核糖核酸探针系列的紧凑性和本地化的新兴特性。 SEQE承诺在10分钟内以极低的成本在整个基因组尺度上提供准确、超长、机车型级读数。SEQE生成的数据需要全新的推论技术。在本文中,我们引入了SEQE测量过程的概率模型和一种算法,该算法通过解决相应最大可能性问题的共分解放松来估计序列。我们展示了我们对于各种模拟数据集的算法的有效性。