Fast and accurate de novo genome assembly from long uncorrected reads

Genome Research

Volumn 27, Issue 5, 2017, Pages 737-746

  Vaser, Robert ^a   Sović, Ivan ^b   Nagarajan, Niranjan ^c   Šikić, Mile ^a,d  

^a UNIVERSITY OF ZAGREB   (Croatia)

^b RUDER BO KOVI INSTITUTE   (Croatia)

^c GENOME INSTITUTE OF SINGAPORE   (Singapore)

^d BIOINFORMATICS INSTITUTE   (Singapore)

Author keywords

[No Author keywords available]

Indexed keywords

ANALYTICAL ERROR; ARTICLE; BACTERIAL CHROMOSOME; BACTERIAL GENOME; CAENORHABDITIS ELEGANS; COMPARATIVE STUDY; CONSENSUS SEQUENCE; CONTROLLED STUDY; ESCHERICHIA COLI K 12; FUNGAL GENOME; GENOME SIZE; MICROBIAL GENOME; NONHUMAN; PRIORITY JOURNAL; SACCHAROMYCES CEREVISIAE; ALGORITHM; CONTIG MAPPING; DNA SEQUENCE; GENOMICS; PROCEDURES; SEQUENCE ALIGNMENT; STANDARDS;

ALGORITHMS; CONTIG MAPPING; GENOMICS; SEQUENCE ALIGNMENT; SEQUENCE ANALYSIS, DNA;

EID: 85019121900     PISSN: 10889051     EISSN: 15495469     Source Type: Journal    
DOI: 10.1101/gr.214270.116     Document Type: Article

References (19)

1. Berlin K, Koren S, Chin C-S, Drake JP, Landolin JM, Phillippy AM. 2015. Assembling large genomes with single-molecule sequencing and locality-sensitive hashing. Nat Biotechnol 33: 623-630.
2. Chaisson MJ, Tesler G. 2012. Mapping single molecule sequencing reads using basic local alignment with successive refinement (BLASR): application and theory. BMC Bioinformatics 13: 238.
3. Chin C-S, Alexander DH, Marks P, Klammer AA, Drake J, Heiner C, Clum A, Copeland A, Huddleston J, Eichler EE, et al. 2013. Nonhybrid, finished microbial genome assemblies from long-read SMRT sequencing data. Nat Methods 10: 563-569.
4. Chin C-S, Peluso P, Sedlazeck FJ, Nattestad M, Concepcion GT, Clum A, Dunn C, O'Malley R, Figueroa-Balderas R, Morales-Cruz A, et al. 2016. Phased diploid genome assembly with single molecule real-time sequencing. Nat Methods 13: 1050-1054.
5. Delcher AL, Salzberg SL, Phillippy AM. 2003. Using MUMmer to identify similar regions in large sequence sets. Curr Protoc Bioinformatics Chapter 10: Unit 10.3.
6. Gotoh O. 1982. An improved algorithm for matching biological sequences. J Mol Biol 162: 705-8.
7. Istace B, Friedrich A, d'Agata L, Faye S, Payen E, Beluche O, Caradec C, Davidas S, Cruaud C, Liti G, et al. 2016. de novo assembly and population genomic survey of natural yeast isolates with the Oxford Nanopore MinION sequencer. bioRxiv doi: 10.1101/066613.
8. Koren S, Walenz BP, Berlin K, Miller JR, Phillippy AM. 2017. Canu: scalable and accurate long-read assembly via adaptive k-mer weighting and repeat separation. Genome Res (this issue). doi: 10.1101/gr.215087.116.
9. Lee C. 2003. Generating consensus sequences from partial order multiple sequence alignment graphs. Bioinformatics 19: 999-1008.
10. Lee C, Grasso C, Sharlow MF. 2002. Multiple sequence alignment using partial order graphs. Bioinformatics 18: 452-464.
11. Li H. 2016. Minimap and miniasm: fast mapping and de novo assembly for noisy long sequences. Bioinformatics 32: 2103-2110.
12. Loman NJ, Quick J, Simpson JT. 2015. A complete bacterial genome assembled de novo using only nanopore sequencing data. Nat Methods 12: 733-735.
13. Loose M, Malla S, Stout M. 2016. Real-time selective sequencing using nanopore technology. Nat Methods 13: 751-754.
14. Myers G. 1999. A fast bit-vector algorithm for approximate string matching based on dynamic programming. J ACM46: 395-415.
15. Rognes T, Seeberg E. 2000. Six-fold speed-up of Smith-Waterman sequence database searches using parallel processing on common microprocessors. Bioinformatics 16: 699-706.
16. Šošić M, Šikić M. 2016. Edlib: A C/C++ library for fast, exact sequence alignment using edit distance. bioRxiv doi: 10.1101/070649.
17. Sović I, Križanović K, Skala K, Šikić M. 2016a. Evaluation of hybrid and nonhybrid methods for de novo assembly of nanopore reads. Bioinformatics 32: 2582-2589.
18. Sović I, Šikić M, Wilm A, Fenlon SN, Chen S, Nagarajan N. 2016b. Fast and sensitive mapping of error-prone nanopore sequencing reads with GraphMap. Nat Commun 7: 11307.
19. Ye C, Ma Z. 2016. Sparc: a sparsity-based consensus algorithm for long erroneous sequencing reads. PeerJ 4: e2016.