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	Inference of Markovian properties of molecular sequences from NGS data and applications to comparative genomics
	Ren, Jie ; Song, Kai ; Deng, Minghua ; Reinert, Gesine ; Cannon, Charles H. ; Sun, Fengzhu
	2016
关键词	DNA-SEQUENCES STATISTICAL-INFERENCE CHAIN ANALYSIS ALIGNMENT METAGENOMICS FREQUENCIES PREDICTION ENHANCERS BROWSER WORDS
英文摘要	Motivation: Next-generation sequencing (NGS) technologies generate large amounts of short read data for many different organisms. The fact that NGS reads are generally short makes it challenging to assemble the reads and reconstruct the original genome sequence. For clustering genomes using such NGS data, word-count based alignment-free sequence comparison is a promising approach, but for this approach, the underlying expected word counts are essential. A plausible model for this underlying distribution of word counts is given through modeling the DNA sequence as a Markov chain (MC). For single long sequences, efficient statistics are available to estimate the order of MCs and the transition probability matrix for the sequences. As NGS data do not provide a single long sequence, inference methods on Markovian properties of sequences based on single long sequences cannot be directly used for NGS short read data. Results: Here we derive a normal approximation for such word counts. We also show that the traditional Chi-square statistic has an approximate gamma distribution, using the Lander-Waterman model for physical mapping. We propose several methods to estimate the order of the MC based on NGS reads and evaluate those using simulations. We illustrate the applications of our results by clustering genomic sequences of several vertebrate and tree species based on NGS reads using alignment-free sequence dissimilarity measures. We find that the estimated order of the MC has a considerable effect on the clustering results, and that the clustering results that use an MC of the estimated order give a plausible clustering of the species.; National Natural Science Foundation of China [31171262, 31428012, 31471246]; National Key Basic Research Project of China [2015CB910303]; US National Institutes of Health [P50 HG 002790]; NSF [DMS 1518001, OCE-1136818]; EPSRC [EP/K032402/1]; SCI(E); PubMed; ARTICLE; fsun@usc.edu; 7; 993-1000; 32
语种	英语
出处	SCI ; PubMed
出版者	BIOINFORMATICS
内容类型	其他
源URL	[http://hdl.handle.net/20.500.11897/419099]
专题	数学科学学院
推荐引用方式 GB/T 7714	Ren, Jie,Song, Kai,Deng, Minghua,et al. Inference of Markovian properties of molecular sequences from NGS data and applications to comparative genomics. 2016-01-01.

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