详细信息
High-bandwidth nanopore data analysis by using a modified hidden Markov model ( SCI-EXPANDED收录 EI收录)
文献类型:期刊文献
英文题名:High-bandwidth nanopore data analysis by using a modified hidden Markov model
作者:Zhang, Jianhua[1];Liu, Xiuling[1];Ying, Yi-Lun[2,3];Gu, Zhen[2,3];Meng, Fu-Na[2,3];Long, Yi-Tao[2,3]
机构:[1]East China Univ Sci & Technol, Sch Informat Sci & Engn, Shanghai 200237, Peoples R China;[2]East China Univ Sci & Technol, Key Lab Adv Mat, Shanghai 200237, Peoples R China;[3]East China Univ Sci & Technol, Dept Chem, Shanghai 200237, Peoples R China
年份:2017
卷号:9
期号:10
起止页码:3458
外文期刊名:NANOSCALE
收录:;EI(收录号:20171103440388);WOS:【SCI-EXPANDED(收录号:WOS:000397125500014)】;
基金:This work was supported in part by the National Natural Science Foundation of China (NSFC) under Grant No. 21505043, No. 21327807 and No. 61075070. YLY's work was also supported by the Chinese Postdoctoral Fund under Grant No. 2016 T90340. The authors would like to thank the anonymous reviewers for their insightful, constructive and inspiring comments and suggestions which helped to improve this paper.
语种:英文
外文关键词:Bandwidth - Gene encoding - Viterbi algorithm - Hidden Markov models - Trellis codes - DNA sequences
摘要:Nanopore-based sensing is an emerging analytical technique with a number of important applications, including single-molecule detection and DNA sequencing. In this paper, we developed a Modified Hidden Markov Model (MHMM) to analyze directly the raw (unfiltered) nanopore current blockade data, which significantly reduced the filtering-induced distortion of the nanopore events. Traditionally, prior to further analysis, the measured nanopore data need to be pre-filtered to supress the strong noises. Nonetheless, this would result in the distortion of the shape of the blockade current especially for rapid translocations and bumping blockades. The HMM has been proved to be robust with respect to highly noisy data and thus ideally suitable for processing raw nanopore data directly. Unfortunately, its performance is somehow sensitive to the initial parameters usually preset arbitrarily. To overcome this problem, we use the Fuzzy c-Means (FCM) algorithm to initialize the HMM parameters automatically. Then we use the Viterbi training algorithm to optimize the HMM. Finally, the application results on both the simulated and experimental data are presented to demonstrate the practicability of the developed method for accurate detection of the nanopore current blockade events. The proposed method enables detection of the nanopore events at the highest bandwidth of the commercial instruments to extract the true useful information about the single molecules under analysis.
参考文献:
正在载入数据...
