XTBG OpenIR  > 其他
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
Source PublicationBIOINFORMATICS
Volume32Issue:7Pages:993-1000
AbstractMotivation: 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.
KeywordDna-sequences Statistical-inference Chain Analysis Alignment Metagenomics Frequencies Prediction Enhancers Browser Words
Document Type期刊论文
Identifierhttp://ir.xtbg.org.cn/handle/353005/9883
Collection其他
Recommended Citation
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[J]. BIOINFORMATICS,2016,32(7):993-1000.
APA Ren, Jie,Song, Kai,Deng, Minghua,Reinert, Gesine,Cannon, Charles H.,&Sun, Fengzhu.(2016).Inference of Markovian properties of molecular sequences from NGS data and applications to comparative genomics.BIOINFORMATICS,32(7),993-1000.
MLA Ren, Jie,et al."Inference of Markovian properties of molecular sequences from NGS data and applications to comparative genomics".BIOINFORMATICS 32.7(2016):993-1000.
Files in This Item:
File Name/Size DocType Version Access License
Inference of Markovi(1927KB) 开放获取CC BY-NC-SAApplication Full Text
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Ren, Jie]'s Articles
[Song, Kai]'s Articles
[Deng, Minghua]'s Articles
Baidu academic
Similar articles in Baidu academic
[Ren, Jie]'s Articles
[Song, Kai]'s Articles
[Deng, Minghua]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Ren, Jie]'s Articles
[Song, Kai]'s Articles
[Deng, Minghua]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.