Minimap and miniasm: fast mapping and de novo assembly for noisy long sequences
Single Molecule Real-Time (SMRT) sequencing technology and Oxford Nanopore technologies (ONT) produce reads over 10 kb in length, which have enabled high-quality genome assembly at an affordable cost. However, at present, long reads have an error rate as high as 10-15%. Complex and computationally i...
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Veröffentlicht in: | Bioinformatics (Oxford, England) England), 2016-07, Vol.32 (14), p.2103-2110 |
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description | Single Molecule Real-Time (SMRT) sequencing technology and Oxford Nanopore technologies (ONT) produce reads over 10 kb in length, which have enabled high-quality genome assembly at an affordable cost. However, at present, long reads have an error rate as high as 10-15%. Complex and computationally intensive pipelines are required to assemble such reads.
We present a new mapper, minimap and a de novo assembler, miniasm, for efficiently mapping and assembling SMRT and ONT reads without an error correction stage. They can often assemble a sequencing run of bacterial data into a single contig in a few minutes, and assemble 45-fold Caenorhabditis elegans data in 9 min, orders of magnitude faster than the existing pipelines, though the consensus sequence error rate is as high as raw reads. We also introduce a pairwise read mapping format and a graphical fragment assembly format, and demonstrate the interoperability between ours and current tools.
https://github.com/lh3/minimap and https://github.com/lh3/miniasm
hengli@broadinstitute.org
Supplementary data are available at Bioinformatics online. |
doi_str_mv | 10.1093/bioinformatics/btw152 |
format | Article |
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We present a new mapper, minimap and a de novo assembler, miniasm, for efficiently mapping and assembling SMRT and ONT reads without an error correction stage. They can often assemble a sequencing run of bacterial data into a single contig in a few minutes, and assemble 45-fold Caenorhabditis elegans data in 9 min, orders of magnitude faster than the existing pipelines, though the consensus sequence error rate is as high as raw reads. We also introduce a pairwise read mapping format and a graphical fragment assembly format, and demonstrate the interoperability between ours and current tools.
https://github.com/lh3/minimap and https://github.com/lh3/miniasm
hengli@broadinstitute.org
Supplementary data are available at Bioinformatics online.</description><identifier>ISSN: 1367-4803</identifier><identifier>ISSN: 1460-2059</identifier><identifier>EISSN: 1367-4811</identifier><identifier>DOI: 10.1093/bioinformatics/btw152</identifier><identifier>PMID: 27153593</identifier><language>eng</language><publisher>England: Oxford University Press</publisher><subject>Animals ; Bacteria - genetics ; bioinformatics ; Caenorhabditis elegans ; Caenorhabditis elegans - genetics ; Chromosome Mapping - methods ; Computational Biology ; consensus sequence ; genome assembly ; High-Throughput Nucleotide Sequencing - methods ; Humans ; nanopores ; Original Papers ; Sequence Analysis, DNA ; Software</subject><ispartof>Bioinformatics (Oxford, England), 2016-07, Vol.32 (14), p.2103-2110</ispartof><rights>The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.</rights><rights>The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com 2016</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c510t-fb0b345db03ea2dd504623516957ed90d641e22ea3999cd77ed19dee2c6c76843</citedby><cites>FETCH-LOGICAL-c510t-fb0b345db03ea2dd504623516957ed90d641e22ea3999cd77ed19dee2c6c76843</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4937194/pdf/$$EPDF$$P50$$Gpubmedcentral$$H</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4937194/$$EHTML$$P50$$Gpubmedcentral$$H</linktohtml><link.rule.ids>230,314,723,776,780,881,27901,27902,53766,53768</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/27153593$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Li, Heng</creatorcontrib><title>Minimap and miniasm: fast mapping and de novo assembly for noisy long sequences</title><title>Bioinformatics (Oxford, England)</title><addtitle>Bioinformatics</addtitle><description>Single Molecule Real-Time (SMRT) sequencing technology and Oxford Nanopore technologies (ONT) produce reads over 10 kb in length, which have enabled high-quality genome assembly at an affordable cost. However, at present, long reads have an error rate as high as 10-15%. Complex and computationally intensive pipelines are required to assemble such reads.
We present a new mapper, minimap and a de novo assembler, miniasm, for efficiently mapping and assembling SMRT and ONT reads without an error correction stage. They can often assemble a sequencing run of bacterial data into a single contig in a few minutes, and assemble 45-fold Caenorhabditis elegans data in 9 min, orders of magnitude faster than the existing pipelines, though the consensus sequence error rate is as high as raw reads. We also introduce a pairwise read mapping format and a graphical fragment assembly format, and demonstrate the interoperability between ours and current tools.
https://github.com/lh3/minimap and https://github.com/lh3/miniasm
hengli@broadinstitute.org
Supplementary data are available at Bioinformatics online.</description><subject>Animals</subject><subject>Bacteria - genetics</subject><subject>bioinformatics</subject><subject>Caenorhabditis elegans</subject><subject>Caenorhabditis elegans - genetics</subject><subject>Chromosome Mapping - methods</subject><subject>Computational Biology</subject><subject>consensus sequence</subject><subject>genome assembly</subject><subject>High-Throughput Nucleotide Sequencing - methods</subject><subject>Humans</subject><subject>nanopores</subject><subject>Original Papers</subject><subject>Sequence Analysis, DNA</subject><subject>Software</subject><issn>1367-4803</issn><issn>1460-2059</issn><issn>1367-4811</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFUctOwzAQtBCIlsIngHLkEupHnMQckFDFSwL1AmfLsTfFKLFLnBb173FpqeiJ065mZ2cfg9A5wVcECzaurLeu9l2reqvDuOq_CKcHaEhYXqRZScjhLsdsgE5C-MAYc8zzYzSgBeGMCzZE0xfrbKvmiXImaWOuQnud1Cr0SUTn1s1-KgYS55c-USFAWzWrJE6OiA2rpPGRE-BzAU5DOEVHtWoCnG3jCL3d371OHtPn6cPT5PY51ZzgPq0rXLGMmwozUNQYjrOcMk5ywQswAps8I0ApKCaE0KaIIBEGgOpcF3mZsRG62ejOF1ULRoPrO9XIeReP6VbSKyv3K86-y5lfykywgoi1wOVWoPNx99DL1gYNTaMc-EWQlHJGeVlk5F8qiR8uREkojVS-oerOh9BBvduIYLn2Te77Jje-xb6Lv-fsun6NYt_8oZr1</recordid><startdate>20160715</startdate><enddate>20160715</enddate><creator>Li, Heng</creator><general>Oxford University Press</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>7S9</scope><scope>L.6</scope><scope>5PM</scope></search><sort><creationdate>20160715</creationdate><title>Minimap and miniasm: fast mapping and de novo assembly for noisy long sequences</title><author>Li, Heng</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c510t-fb0b345db03ea2dd504623516957ed90d641e22ea3999cd77ed19dee2c6c76843</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Animals</topic><topic>Bacteria - genetics</topic><topic>bioinformatics</topic><topic>Caenorhabditis elegans</topic><topic>Caenorhabditis elegans - genetics</topic><topic>Chromosome Mapping - methods</topic><topic>Computational Biology</topic><topic>consensus sequence</topic><topic>genome assembly</topic><topic>High-Throughput Nucleotide Sequencing - methods</topic><topic>Humans</topic><topic>nanopores</topic><topic>Original Papers</topic><topic>Sequence Analysis, DNA</topic><topic>Software</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Li, Heng</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>AGRICOLA</collection><collection>AGRICOLA - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Bioinformatics (Oxford, England)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Li, Heng</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Minimap and miniasm: fast mapping and de novo assembly for noisy long sequences</atitle><jtitle>Bioinformatics (Oxford, England)</jtitle><addtitle>Bioinformatics</addtitle><date>2016-07-15</date><risdate>2016</risdate><volume>32</volume><issue>14</issue><spage>2103</spage><epage>2110</epage><pages>2103-2110</pages><issn>1367-4803</issn><issn>1460-2059</issn><eissn>1367-4811</eissn><abstract>Single Molecule Real-Time (SMRT) sequencing technology and Oxford Nanopore technologies (ONT) produce reads over 10 kb in length, which have enabled high-quality genome assembly at an affordable cost. However, at present, long reads have an error rate as high as 10-15%. Complex and computationally intensive pipelines are required to assemble such reads.
We present a new mapper, minimap and a de novo assembler, miniasm, for efficiently mapping and assembling SMRT and ONT reads without an error correction stage. They can often assemble a sequencing run of bacterial data into a single contig in a few minutes, and assemble 45-fold Caenorhabditis elegans data in 9 min, orders of magnitude faster than the existing pipelines, though the consensus sequence error rate is as high as raw reads. We also introduce a pairwise read mapping format and a graphical fragment assembly format, and demonstrate the interoperability between ours and current tools.
https://github.com/lh3/minimap and https://github.com/lh3/miniasm
hengli@broadinstitute.org
Supplementary data are available at Bioinformatics online.</abstract><cop>England</cop><pub>Oxford University Press</pub><pmid>27153593</pmid><doi>10.1093/bioinformatics/btw152</doi><tpages>8</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Animals Bacteria - genetics bioinformatics Caenorhabditis elegans Caenorhabditis elegans - genetics Chromosome Mapping - methods Computational Biology consensus sequence genome assembly High-Throughput Nucleotide Sequencing - methods Humans nanopores Original Papers Sequence Analysis, DNA Software |
title | Minimap and miniasm: fast mapping and de novo assembly for noisy long sequences |
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