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The combination of direct and paired link graphs can boost repetitive genome assembly.
Shi, Wenyu; Ji, Peifeng; Zhao, Fangqing.
Afiliação
  • Shi W; Computational Genomics Lab, Beijing Institutes of Life Science, Chinese Academy of Sciences, Beijing 100101, China.
  • Ji P; Computational Genomics Lab, Beijing Institutes of Life Science, Chinese Academy of Sciences, Beijing 100101, China.
  • Zhao F; Computational Genomics Lab, Beijing Institutes of Life Science, Chinese Academy of Sciences, Beijing 100101, China.
Nucleic Acids Res ; 45(6): e43, 2017 04 07.
Article em En | MEDLINE | ID: mdl-27924003
ABSTRACT
Currently, most paired link based scaffolding algorithms intrinsically mask the sequences between two linked contigs and bypass their direct link information embedded in the original de Bruijn assembly graph. Such disadvantage substantially complicates the scaffolding process and leads to the inability of resolving repetitive contig assembly. Here we present a novel algorithm, inGAP-sf, for effectively generating high-quality and continuous scaffolds. inGAP-sf achieves this by using a new strategy based on the combination of direct link and paired link graphs, in which direct link is used to increase graph connectivity and to decrease graph complexity and paired link is employed to supervise the traversing process on the direct link graph. Such advantage greatly facilitates the assembly of short-repeat enriched regions. Moreover, a new comprehensive decision model is developed to eliminate the noise routes accompanying with the introduced direct link. Through extensive evaluations on both simulated and real datasets, we demonstrated that inGAP-sf outperforms most of the genome scaffolding algorithms by generating more accurate and continuous assembly, especially for short repetitive regions.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Algoritmos / Análise de Sequência de DNA / Genômica Tipo de estudo: Clinical_trials / Evaluation_studies / Prognostic_studies Idioma: En Ano de publicação: 2017 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Algoritmos / Análise de Sequência de DNA / Genômica Tipo de estudo: Clinical_trials / Evaluation_studies / Prognostic_studies Idioma: En Ano de publicação: 2017 Tipo de documento: Article