Confidence intervals for Markov chain transition probabilities based on next generation sequencing reads data

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	Confidence intervals for Markov chain transition probabilities based on next generation sequencing reads data
	Wan, Lin 1; Kang, Xin 2; Ren, Jie 3; Sun, Fengzhu 3
	2020
发表期刊	QUANTITATIVE BIOLOGY
ISSN	2095-4689
卷号	8 期号:2 页码:143-154
摘要	Background Markov chains (MC) have been widely used to model molecular sequences. The estimations of MC transition matrix and confidence intervals of the transition probabilities from long sequence data have been intensively studied in the past decades. In next generation sequencing (NGS), a large amount of short reads are generated. These short reads can overlap and some regions of the genome may not be sequenced resulting in a new type of data. Based on NGS data, the transition probabilities ofMCcan be estimated by moment estimators. However, the classical asymptotic distribution theory for MC transition probability estimators based on long sequences is no longer valid. Methods In this study, we present the asymptotic distributions of several statistics related to MC based on NGS data. We show that, after scaling by the effective coverage d defined in a previous study by the authors, these statistics based on NGS data approximate to the same distributions as the corresponding statistics for long sequences. Results We apply the asymptotic properties of these statistics for finding the theoretical confidence regions for MC transition probabilities based on NGS short reads data. We validate our theoretical confidence intervals using both simulated data and real data sets, and compare the results with those by the parametric bootstrap method. Conclusions We find that the asymptotic distributions of these statistics and the theoretical confidence intervals of transition probabilities based on NGS data given in this study are highly accurate, providing a powerful tool for NGS data analysis.
关键词	DNA FREQUENCIES PREDICTION Markov chains next generation sequencing transition probabilities confidence intervals
收录类别	CSCD
语种	英语
资助项目	[NSFC] ; [National Key R&D Program of China] ; [NCMIS of CAS] ; [LSC of CAS] ; [Youth Innovation Promotion Association of CAS] ; [US National Science Foundation (NSF)] ; [National Institutes of Health (NIH)]
CSCD记录号	CSCD:6791308
引用统计
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/57720
专题	中国科学院数学与系统科学研究院
作者单位	1.中国科学院数学与系统科学研究院 2.复旦大学 3.University Southern Calif, Quantitat & Computat Biol Program, Los Angeles, CA 90089 USA
推荐引用方式 GB/T 7714	Wan, Lin,Kang, Xin,Ren, Jie,et al. Confidence intervals for Markov chain transition probabilities based on next generation sequencing reads data[J]. QUANTITATIVE BIOLOGY,2020,8(2):143-154.
APA	Wan, Lin,Kang, Xin,Ren, Jie,&Sun, Fengzhu.(2020).Confidence intervals for Markov chain transition probabilities based on next generation sequencing reads data.QUANTITATIVE BIOLOGY,8(2),143-154.
MLA	Wan, Lin,et al."Confidence intervals for Markov chain transition probabilities based on next generation sequencing reads data".QUANTITATIVE BIOLOGY 8.2(2020):143-154.