Literature DB >> 19535537

A fast hybrid short read fragment assembly algorithm.

Bertil Schmidt1, Ranjan Sinha, Bryan Beresford-Smith, Simon J Puglisi.   

Abstract

SUMMARY: The shorter and vastly more numerous reads produced by second-generation sequencing technologies require new tools that can assemble massive numbers of reads in reasonable time. Existing short-read assembly tools can be classified into two categories: greedy extension-based and graph-based. While the graph-based approaches are generally superior in terms of assembly quality, the computer resources required for building and storing a huge graph are very high. In this article, we present Taipan, an assembly algorithm which can be viewed as a hybrid of these two approaches. Taipan uses greedy extensions for contig construction but at each step realizes enough of the corresponding read graph to make better decisions as to how assembly should continue. We show that this approach can achieve an assembly quality at least as good as the graph-based approaches used in the popular Edena and Velvet assembly tools using a moderate amount of computing resources.

Mesh:

Year:  2009        PMID: 19535537     DOI: 10.1093/bioinformatics/btp374

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  14 in total

1.  Assembler for de novo assembly of large genomes.

Authors:  Te-Chin Chu; Chen-Hua Lu; Tsunglin Liu; Greg C Lee; Wen-Hsiung Li; Arthur Chun-Chieh Shih
Journal:  Proc Natl Acad Sci U S A       Date:  2013-08-21       Impact factor: 11.205

Review 2.  Assembly algorithms for next-generation sequencing data.

Authors:  Jason R Miller; Sergey Koren; Granger Sutton
Journal:  Genomics       Date:  2010-03-06       Impact factor: 5.736

3.  Comparing de novo genome assembly: the long and short of it.

Authors:  Giuseppe Narzisi; Bud Mishra
Journal:  PLoS One       Date:  2011-04-29       Impact factor: 3.240

4.  DecGPU: distributed error correction on massively parallel graphics processing units using CUDA and MPI.

Authors:  Yongchao Liu; Bertil Schmidt; Douglas L Maskell
Journal:  BMC Bioinformatics       Date:  2011-03-29       Impact factor: 3.169

5.  A practical comparison of de novo genome assembly software tools for next-generation sequencing technologies.

Authors:  Wenyu Zhang; Jiajia Chen; Yang Yang; Yifei Tang; Jing Shang; Bairong Shen
Journal:  PLoS One       Date:  2011-03-14       Impact factor: 3.240

6.  SEED: efficient clustering of next-generation sequences.

Authors:  Ergude Bao; Tao Jiang; Isgouhi Kaloshian; Thomas Girke
Journal:  Bioinformatics       Date:  2011-08-02       Impact factor: 6.937

7.  Parallelized short read assembly of large genomes using de Bruijn graphs.

Authors:  Yongchao Liu; Bertil Schmidt; Douglas L Maskell
Journal:  BMC Bioinformatics       Date:  2011-08-25       Impact factor: 3.169

Review 8.  RNA-seq: from technology to biology.

Authors:  Samuel Marguerat; Jürg Bähler
Journal:  Cell Mol Life Sci       Date:  2009-10-27       Impact factor: 9.261

9.  GapFiller: a de novo assembly approach to fill the gap within paired reads.

Authors:  Francesca Nadalin; Francesco Vezzi; Alberto Policriti
Journal:  BMC Bioinformatics       Date:  2012-09-07       Impact factor: 3.169

10.  Effects of GC bias in next-generation-sequencing data on de novo genome assembly.

Authors:  Yen-Chun Chen; Tsunglin Liu; Chun-Hui Yu; Tzen-Yuh Chiang; Chi-Chuan Hwang
Journal:  PLoS One       Date:  2013-04-29       Impact factor: 3.240

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