Emmett Kevin J, Rosenstein Jacob K, van de Meent Jan-Willem, Shepard Ken L, Wiggins Chris H
Department of Physics, Columbia University, New York, New York.
School of Engineering, Brown University, Providence, Rhode Island.
Biophys J. 2015 Apr 21;108(8):1852-5. doi: 10.1016/j.bpj.2015.03.013.
Nanopore sequencing promises long read-lengths and single-molecule resolution, but the stochastic motion of the DNA molecule inside the pore is, as of this writing, a barrier to high accuracy reads. We develop a method of statistical inference that explicitly accounts for this error, and demonstrate that high accuracy (>99%) sequence inference is feasible even under highly diffusive motion by using a hidden Markov model to jointly analyze multiple stochastic reads. Using this model, we place bounds on achievable inference accuracy under a range of experimental parameters.
纳米孔测序有望实现长读长和单分子分辨率，但截至撰写本文时，DNA分子在孔内的随机运动是高精度读取的一个障碍。我们开发了一种统计推断方法，明确考虑了这种误差，并证明即使在高度扩散运动的情况下，通过使用隐马尔可夫模型联合分析多个随机读取，高精度（>99%）的序列推断也是可行的。使用该模型，我们在一系列实验参数下确定了可实现的推断精度的界限。
