DocumentCode :
683898
Title :
A new genome assembly method based on dynamic overlap
Author :
Lian, Shuaibin ; Dai, Xianhua
Author_Institution :
School of Information Science and Technology, Sun Yat-sen University, Guangzhou, China
fYear :
2013
fDate :
23-25 March 2013
Firstpage :
1
Lastpage :
5
Abstract :
The Next Generation Sequencing platform can generate shorter reads, higher coverage, higher throughput than the Sanger sequencing. These lowest cost technologies can produce deeper coverage of most species, including mammals, in few days at one run. The sequence data produced by one of these instruments consist of millions or billions of sequence reads ranging from 50 to 150nt in length. These short read must be assembled de novo before further genome analysis can begin. Unfortunately, genome assembly remains a difficult problem challenged by many reasons, especially the short reads and the complex repeats structure that longer than the reads. There are many assembly algorithms and software recently, most of them appear powerless by facing repeats, especially for the identical ones and cannot get the unique assembly result with the completely same input data. How to get the unique and stable assembly result when repeats that longer than read contained into the input data set is becoming a key issue. In this perspective, we proposed a genome assembly method based on dynamic overlap which can get unique result from the beginning of randomly selected read and can resolve high similarity repeats whose length is hundreds times of read length, more importantly, we use single-end data but not paired-end information to resolve high similarity repeats.
Keywords :
Assembly; Bioinformatics; Genomics; Heuristic algorithms; Indexes; Next generation networking; Sequential analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Science and Technology (ICIST), 2013 International Conference on
Conference_Location :
Yangzhou
Print_ISBN :
978-1-4673-5137-9
Type :
conf
DOI :
10.1109/ICIST.2013.6747487
Filename :
6747487
Link To Document :
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