MEGAHIT: an ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph

MEGAHIT is a NGS de novo assembler for assembling large and complex metagenomics data in a time- and cost-efficient manner. It finished assembling a soil metagenomics dataset with 252 Gbps in 44.1 and 99.6 h on a single computing node with and without a graphics processing unit, respectively. MEGAHI...

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Bibliographic Details
Published in	Bioinformatics Vol. 31; no. 10; pp. 1674 - 1676
Main Authors	Li, Dinghua, Liu, Chi-Man, Luo, Ruibang, Sadakane, Kunihiko, Lam, Tak-Wah
Format	Journal Article
Language	English
Published	England 15.05.2015
Subjects	Algorithms Assembling Assembly Bioinformatics Graphics processing units Graphs High-Throughput Nucleotide Sequencing Mathematical models Metagenomics - methods Partitioning Software Soil Soil (material)
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Abstract	MEGAHIT is a NGS de novo assembler for assembling large and complex metagenomics data in a time- and cost-efficient manner. It finished assembling a soil metagenomics dataset with 252 Gbps in 44.1 and 99.6 h on a single computing node with and without a graphics processing unit, respectively. MEGAHIT assembles the data as a whole, i.e. no pre-processing like partitioning and normalization was needed. When compared with previous methods on assembling the soil data, MEGAHIT generated a three-time larger assembly, with longer contig N50 and average contig length; furthermore, 55.8% of the reads were aligned to the assembly, giving a fourfold improvement. Availability and implementation: The source code of MEGAHIT is freely available at https://github.com/voutcn/megahit under GPLv3 license. Contact: rb@l3-bioinfo.com or twlam@cs.hku.hk Supplementary information: Supplementary data are available at Bioinformatics online.
AbstractList	MEGAHIT is a NGS de novo assembler for assembling large and complex metagenomics data in a time- and cost-efficient manner. It finished assembling a soil metagenomics dataset with 252 Gbps in 44.1 and 99.6 h on a single computing node with and without a graphics processing unit, respectively. MEGAHIT assembles the data as a whole, i.e. no pre-processing like partitioning and normalization was needed. When compared with previous methods on assembling the soil data, MEGAHIT generated a three-time larger assembly, with longer contig N50 and average contig length; furthermore, 55.8% of the reads were aligned to the assembly, giving a fourfold improvement.MEGAHIT is a NGS de novo assembler for assembling large and complex metagenomics data in a time- and cost-efficient manner. It finished assembling a soil metagenomics dataset with 252 Gbps in 44.1 and 99.6 h on a single computing node with and without a graphics processing unit, respectively. MEGAHIT assembles the data as a whole, i.e. no pre-processing like partitioning and normalization was needed. When compared with previous methods on assembling the soil data, MEGAHIT generated a three-time larger assembly, with longer contig N50 and average contig length; furthermore, 55.8% of the reads were aligned to the assembly, giving a fourfold improvement. MEGAHIT is a NGS de novo assembler for assembling large and complex metagenomics data in a time- and cost-efficient manner. It finished assembling a soil metagenomics dataset with 252Gbps in 44.1 and 99.6h on a single computing node with and without a graphics processing unit, respectively. MEGAHIT assembles the data as a whole, i.e. no pre-processing like partitioning and normalization was needed. When compared with previous methods on assembling the soil data, MEGAHIT generated a three-time larger assembly, with longer contig N50 and average contig length; furthermore, 55.8% of the reads were aligned to the assembly, giving a fourfold improvement.Availability and implementation: The source code of MEGAHIT is freely available at https://github.com/voutcn/megahit under GPLv3 license. Supplementary information: Supplementary data are available at Bioinformatics online. MEGAHIT is a NGS de novo assembler for assembling large and complex metagenomics data in a time- and cost-efficient manner. It finished assembling a soil metagenomics dataset with 252 Gbps in 44.1 and 99.6 h on a single computing node with and without a graphics processing unit, respectively. MEGAHIT assembles the data as a whole, i.e. no pre-processing like partitioning and normalization was needed. When compared with previous methods on assembling the soil data, MEGAHIT generated a three-time larger assembly, with longer contig N50 and average contig length; furthermore, 55.8% of the reads were aligned to the assembly, giving a fourfold improvement. MEGAHIT is a NGS de novo assembler for assembling large and complex metagenomics data in a time- and cost-efficient manner. It finished assembling a soil metagenomics dataset with 252 Gbps in 44.1 and 99.6 h on a single computing node with and without a graphics processing unit, respectively. MEGAHIT assembles the data as a whole, i.e. no pre-processing like partitioning and normalization was needed. When compared with previous methods on assembling the soil data, MEGAHIT generated a three-time larger assembly, with longer contig N50 and average contig length; furthermore, 55.8% of the reads were aligned to the assembly, giving a fourfold improvement. Availability and implementation: The source code of MEGAHIT is freely available at https://github.com/voutcn/megahit under GPLv3 license. Contact: rb@l3-bioinfo.com or twlam@cs.hku.hk Supplementary information: Supplementary data are available at Bioinformatics online.
Author	Luo, Ruibang Li, Dinghua Sadakane, Kunihiko Lam, Tak-Wah Liu, Chi-Man
Author_xml	– sequence: 1 givenname: Dinghua surname: Li fullname: Li, Dinghua – sequence: 2 givenname: Chi-Man surname: Liu fullname: Liu, Chi-Man – sequence: 3 givenname: Ruibang surname: Luo fullname: Luo, Ruibang – sequence: 4 givenname: Kunihiko surname: Sadakane fullname: Sadakane, Kunihiko – sequence: 5 givenname: Tak-Wah surname: Lam fullname: Lam, Tak-Wah
BackLink	https://www.ncbi.nlm.nih.gov/pubmed/25609793$$D View this record in MEDLINE/PubMed
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References	Gurevich (2023020115461644300_btv033-B4) 2013; 29 Luo (2023020115461644300_btv033-B8) 2012; 1 Bankevich (2023020115461644300_btv033-B1) 2012; 19 Peng (2023020115461644300_btv033-B9) 2012; 28 Liu (2023020115461644300_btv033-B7) 2014 Howe (2023020115461644300_btv033-B5) 2014; 111 Qin (2023020115461644300_btv033-B10) 2010; 464 Chikhi (2023020115461644300_btv033-B3) 2012 Langmead (2023020115461644300_btv033-B6) 2012; 9 Bowe (2023020115461644300_btv033-B2) 2012
References_xml	– start-page: 225 volume-title: Algorithms in Bioinformatics year: 2012 ident: 2023020115461644300_btv033-B2 article-title: Succinct de Bruijn Graphs doi: 10.1007/978-3-642-33122-0_18 – start-page: 236 volume-title: Algorithms in Bioinformatics year: 2012 ident: 2023020115461644300_btv033-B3 article-title: Space-efficient and exact de Bruijn graph representation based on a bloom filter doi: 10.1007/978-3-642-33122-0_19 – volume: 29 start-page: 1072 year: 2013 ident: 2023020115461644300_btv033-B4 article-title: QUAST: quality assessment tool for genome assemblies publication-title: Bioinformatics doi: 10.1093/bioinformatics/btt086 – volume: 9 start-page: 357 year: 2012 ident: 2023020115461644300_btv033-B6 article-title: Fast gapped-read alignment with Bowtie 2 publication-title: Nat. Methods doi: 10.1038/nmeth.1923 – volume: 1 start-page: 18 year: 2012 ident: 2023020115461644300_btv033-B8 article-title: SOAPdenovo2: an empirically improved memory-efficient short-read de novo assembler publication-title: GigaScience doi: 10.1186/2047-217X-1-18 – year: 2014 ident: 2023020115461644300_btv033-B7 article-title: GPU-accelerated BWT construction for large collection of short reads publication-title: arXiv – volume: 19 start-page: 455 year: 2012 ident: 2023020115461644300_btv033-B1 article-title: SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing publication-title: J. Comput. Biol. doi: 10.1089/cmb.2012.0021 – volume: 111 start-page: 4904 year: 2014 ident: 2023020115461644300_btv033-B5 article-title: Tackling soil diversity with the assembly of large, complex metagenomes publication-title: Proc. Natl Acad. Sci. USA doi: 10.1073/pnas.1402564111 – volume: 28 start-page: 1420 year: 2012 ident: 2023020115461644300_btv033-B9 article-title: IDBA-UD: a de novo assembler for single-cell and meta-genomic sequencing data with highly uneven depth publication-title: Bioinformatics doi: 10.1093/bioinformatics/bts174 – volume: 464 start-page: 59 year: 2010 ident: 2023020115461644300_btv033-B10 article-title: A human gut microbial gene catalogue established by metagenomic sequencing publication-title: Nature doi: 10.1038/nature08821
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SubjectTerms	Algorithms Assembling Assembly Bioinformatics Graphics processing units Graphs High-Throughput Nucleotide Sequencing Mathematical models Metagenomics - methods Partitioning Software Soil Soil (material)
Title	MEGAHIT: an ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph
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