Mining statistically-solid k-mers for accurate NGS error correction.
Identifieur interne : 000832 ( PubMed/Checkpoint ); précédent : 000831; suivant : 000833Mining statistically-solid k-mers for accurate NGS error correction.
Auteurs : Liang Zhao [République populaire de Chine] ; Jin Xie [République populaire de Chine] ; Lin Bai [République populaire de Chine] ; Wen Chen [République populaire de Chine] ; Mingju Wang [République populaire de Chine] ; Zhonglei Zhang [République populaire de Chine] ; Yiqi Wang [République populaire de Chine] ; Zhe Zhao [République populaire de Chine] ; Jinyan Li [Australie]Source :
- BMC genomics [ 1471-2164 ] ; 2018.
Descripteurs français
- KwdFr :
- MESH :
English descriptors
- KwdEn :
- MESH :
Abstract
NGS data contains many machine-induced errors. The most advanced methods for the error correction heavily depend on the selection of solid k-mers. A solid k-mer is a k-mer frequently occurring in NGS reads. The other k-mers are called weak k-mers. A solid k-mer does not likely contain errors, while a weak k-mer most likely contains errors. An intensively investigated problem is to find a good frequency cutoff f0 to balance the numbers of solid and weak k-mers. Once the cutoff is determined, a more challenging but less-studied problem is to: (i) remove a small subset of solid k-mers that are likely to contain errors, and (ii) add a small subset of weak k-mers, that are likely to contain no errors, into the remaining set of solid k-mers. Identification of these two subsets of k-mers can improve the correction performance.
DOI: 10.1186/s12864-018-5272-y
PubMed: 30598110
Affiliations:
Links toward previous steps (curation, corpus...)
Links to Exploration step
pubmed:30598110Le document en format XML
<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Mining statistically-solid k-mers for accurate NGS error correction.</title><author><name sortKey="Zhao, Liang" sort="Zhao, Liang" uniqKey="Zhao L" first="Liang" last="Zhao">Liang Zhao</name><affiliation wicri:level="1"><nlm:affiliation>Precision Medicine Research Center, Taihe Hospital, Hubei University of Medicine, Shiyan, China. s080011@e.ntu.edu.sg.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Precision Medicine Research Center, Taihe Hospital, Hubei University of Medicine, Shiyan</wicri:regionArea><wicri:noRegion>Shiyan</wicri:noRegion></affiliation></author><author><name sortKey="Xie, Jin" sort="Xie, Jin" uniqKey="Xie J" first="Jin" last="Xie">Jin Xie</name><affiliation wicri:level="1"><nlm:affiliation>Precision Medicine Research Center, Taihe Hospital, Hubei University of Medicine, Shiyan, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Precision Medicine Research Center, Taihe Hospital, Hubei University of Medicine, Shiyan</wicri:regionArea><wicri:noRegion>Shiyan</wicri:noRegion></affiliation></author><author><name sortKey="Bai, Lin" sort="Bai, Lin" uniqKey="Bai L" first="Lin" last="Bai">Lin Bai</name><affiliation wicri:level="1"><nlm:affiliation>School of Computing and Electronic Information, Guangxi University, Nanning, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>School of Computing and Electronic Information, Guangxi University, Nanning</wicri:regionArea><wicri:noRegion>Nanning</wicri:noRegion></affiliation></author><author><name sortKey="Chen, Wen" sort="Chen, Wen" uniqKey="Chen W" first="Wen" last="Chen">Wen Chen</name><affiliation wicri:level="1"><nlm:affiliation>Precision Medicine Research Center, Taihe Hospital, Hubei University of Medicine, Shiyan, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Precision Medicine Research Center, Taihe Hospital, Hubei University of Medicine, Shiyan</wicri:regionArea><wicri:noRegion>Shiyan</wicri:noRegion></affiliation></author><author><name sortKey="Wang, Mingju" sort="Wang, Mingju" uniqKey="Wang M" first="Mingju" last="Wang">Mingju Wang</name><affiliation wicri:level="1"><nlm:affiliation>Precision Medicine Research Center, Taihe Hospital, Hubei University of Medicine, Shiyan, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Precision Medicine Research Center, Taihe Hospital, Hubei University of Medicine, Shiyan</wicri:regionArea><wicri:noRegion>Shiyan</wicri:noRegion></affiliation></author><author><name sortKey="Zhang, Zhonglei" sort="Zhang, Zhonglei" uniqKey="Zhang Z" first="Zhonglei" last="Zhang">Zhonglei Zhang</name><affiliation wicri:level="1"><nlm:affiliation>Precision Medicine Research Center, Taihe Hospital, Hubei University of Medicine, Shiyan, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Precision Medicine Research Center, Taihe Hospital, Hubei University of Medicine, Shiyan</wicri:regionArea><wicri:noRegion>Shiyan</wicri:noRegion></affiliation></author><author><name sortKey="Wang, Yiqi" sort="Wang, Yiqi" uniqKey="Wang Y" first="Yiqi" last="Wang">Yiqi Wang</name><affiliation wicri:level="1"><nlm:affiliation>Precision Medicine Research Center, Taihe Hospital, Hubei University of Medicine, Shiyan, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Precision Medicine Research Center, Taihe Hospital, Hubei University of Medicine, Shiyan</wicri:regionArea><wicri:noRegion>Shiyan</wicri:noRegion></affiliation></author><author><name sortKey="Zhao, Zhe" sort="Zhao, Zhe" uniqKey="Zhao Z" first="Zhe" last="Zhao">Zhe Zhao</name><affiliation wicri:level="1"><nlm:affiliation>School of Computing and Electronic Information, Guangxi University, Nanning, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>School of Computing and Electronic Information, Guangxi University, Nanning</wicri:regionArea><wicri:noRegion>Nanning</wicri:noRegion></affiliation></author><author><name sortKey="Li, Jinyan" sort="Li, Jinyan" uniqKey="Li J" first="Jinyan" last="Li">Jinyan Li</name><affiliation wicri:level="1"><nlm:affiliation>Advanced Analytics Institute, Faculty of Engineering & IT, University of Technology Sydney, NSW 2007, Australia. jinyan.li@uts.edu.au.</nlm:affiliation><country xml:lang="fr">Australie</country><wicri:regionArea>Advanced Analytics Institute, Faculty of Engineering & IT, University of Technology Sydney, NSW 2007</wicri:regionArea><wicri:noRegion>NSW 2007</wicri:noRegion></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2018">2018</date><idno type="RBID">pubmed:30598110</idno><idno type="pmid">30598110</idno><idno type="doi">10.1186/s12864-018-5272-y</idno><idno type="wicri:Area/PubMed/Corpus">000689</idno><idno type="wicri:explorRef" wicri:stream="PubMed" wicri:step="Corpus" wicri:corpus="PubMed">000689</idno><idno type="wicri:Area/PubMed/Curation">000689</idno><idno type="wicri:explorRef" wicri:stream="PubMed" wicri:step="Curation">000689</idno><idno type="wicri:Area/PubMed/Checkpoint">000832</idno><idno type="wicri:explorRef" wicri:stream="Checkpoint" wicri:step="PubMed">000832</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">Mining statistically-solid k-mers for accurate NGS error correction.</title><author><name sortKey="Zhao, Liang" sort="Zhao, Liang" uniqKey="Zhao L" first="Liang" last="Zhao">Liang Zhao</name><affiliation wicri:level="1"><nlm:affiliation>Precision Medicine Research Center, Taihe Hospital, Hubei University of Medicine, Shiyan, China. s080011@e.ntu.edu.sg.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Precision Medicine Research Center, Taihe Hospital, Hubei University of Medicine, Shiyan</wicri:regionArea><wicri:noRegion>Shiyan</wicri:noRegion></affiliation></author><author><name sortKey="Xie, Jin" sort="Xie, Jin" uniqKey="Xie J" first="Jin" last="Xie">Jin Xie</name><affiliation wicri:level="1"><nlm:affiliation>Precision Medicine Research Center, Taihe Hospital, Hubei University of Medicine, Shiyan, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Precision Medicine Research Center, Taihe Hospital, Hubei University of Medicine, Shiyan</wicri:regionArea><wicri:noRegion>Shiyan</wicri:noRegion></affiliation></author><author><name sortKey="Bai, Lin" sort="Bai, Lin" uniqKey="Bai L" first="Lin" last="Bai">Lin Bai</name><affiliation wicri:level="1"><nlm:affiliation>School of Computing and Electronic Information, Guangxi University, Nanning, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>School of Computing and Electronic Information, Guangxi University, Nanning</wicri:regionArea><wicri:noRegion>Nanning</wicri:noRegion></affiliation></author><author><name sortKey="Chen, Wen" sort="Chen, Wen" uniqKey="Chen W" first="Wen" last="Chen">Wen Chen</name><affiliation wicri:level="1"><nlm:affiliation>Precision Medicine Research Center, Taihe Hospital, Hubei University of Medicine, Shiyan, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Precision Medicine Research Center, Taihe Hospital, Hubei University of Medicine, Shiyan</wicri:regionArea><wicri:noRegion>Shiyan</wicri:noRegion></affiliation></author><author><name sortKey="Wang, Mingju" sort="Wang, Mingju" uniqKey="Wang M" first="Mingju" last="Wang">Mingju Wang</name><affiliation wicri:level="1"><nlm:affiliation>Precision Medicine Research Center, Taihe Hospital, Hubei University of Medicine, Shiyan, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Precision Medicine Research Center, Taihe Hospital, Hubei University of Medicine, Shiyan</wicri:regionArea><wicri:noRegion>Shiyan</wicri:noRegion></affiliation></author><author><name sortKey="Zhang, Zhonglei" sort="Zhang, Zhonglei" uniqKey="Zhang Z" first="Zhonglei" last="Zhang">Zhonglei Zhang</name><affiliation wicri:level="1"><nlm:affiliation>Precision Medicine Research Center, Taihe Hospital, Hubei University of Medicine, Shiyan, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Precision Medicine Research Center, Taihe Hospital, Hubei University of Medicine, Shiyan</wicri:regionArea><wicri:noRegion>Shiyan</wicri:noRegion></affiliation></author><author><name sortKey="Wang, Yiqi" sort="Wang, Yiqi" uniqKey="Wang Y" first="Yiqi" last="Wang">Yiqi Wang</name><affiliation wicri:level="1"><nlm:affiliation>Precision Medicine Research Center, Taihe Hospital, Hubei University of Medicine, Shiyan, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Precision Medicine Research Center, Taihe Hospital, Hubei University of Medicine, Shiyan</wicri:regionArea><wicri:noRegion>Shiyan</wicri:noRegion></affiliation></author><author><name sortKey="Zhao, Zhe" sort="Zhao, Zhe" uniqKey="Zhao Z" first="Zhe" last="Zhao">Zhe Zhao</name><affiliation wicri:level="1"><nlm:affiliation>School of Computing and Electronic Information, Guangxi University, Nanning, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>School of Computing and Electronic Information, Guangxi University, Nanning</wicri:regionArea><wicri:noRegion>Nanning</wicri:noRegion></affiliation></author><author><name sortKey="Li, Jinyan" sort="Li, Jinyan" uniqKey="Li J" first="Jinyan" last="Li">Jinyan Li</name><affiliation wicri:level="1"><nlm:affiliation>Advanced Analytics Institute, Faculty of Engineering & IT, University of Technology Sydney, NSW 2007, Australia. jinyan.li@uts.edu.au.</nlm:affiliation><country xml:lang="fr">Australie</country><wicri:regionArea>Advanced Analytics Institute, Faculty of Engineering & IT, University of Technology Sydney, NSW 2007</wicri:regionArea><wicri:noRegion>NSW 2007</wicri:noRegion></affiliation></author></analytic><series><title level="j">BMC genomics</title><idno type="eISSN">1471-2164</idno><imprint><date when="2018" type="published">2018</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Algorithms</term><term>Data Mining</term><term>High-Throughput Nucleotide Sequencing</term><term>Research Design</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Algorithmes</term><term>Fouille de données</term><term>Plan de recherche</term><term>Séquençage nucléotidique à haut débit</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Algorithms</term><term>Data Mining</term><term>High-Throughput Nucleotide Sequencing</term><term>Research Design</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Algorithmes</term><term>Fouille de données</term><term>Plan de recherche</term><term>Séquençage nucléotidique à haut débit</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">NGS data contains many machine-induced errors. The most advanced methods for the error correction heavily depend on the selection of solid k-mers. A solid k-mer is a k-mer frequently occurring in NGS reads. The other k-mers are called weak k-mers. A solid k-mer does not likely contain errors, while a weak k-mer most likely contains errors. An intensively investigated problem is to find a good frequency cutoff f<sub>0</sub> to balance the numbers of solid and weak k-mers. Once the cutoff is determined, a more challenging but less-studied problem is to: (i) remove a small subset of solid k-mers that are likely to contain errors, and (ii) add a small subset of weak k-mers, that are likely to contain no errors, into the remaining set of solid k-mers. Identification of these two subsets of k-mers can improve the correction performance.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">30598110</PMID><DateCompleted><Year>2019</Year><Month>04</Month><Day>08</Day></DateCompleted><DateRevised><Year>2020</Year><Month>02</Month><Day>25</Day></DateRevised><Article PubModel="Electronic"><Journal><ISSN IssnType="Electronic">1471-2164</ISSN><JournalIssue CitedMedium="Internet"><Volume>19</Volume><Issue>Suppl 10</Issue><PubDate><Year>2018</Year><Month>Dec</Month><Day>31</Day></PubDate></JournalIssue><Title>BMC genomics</Title><ISOAbbreviation>BMC Genomics</ISOAbbreviation></Journal><ArticleTitle>Mining statistically-solid k-mers for accurate NGS error correction.</ArticleTitle><Pagination><MedlinePgn>912</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1186/s12864-018-5272-y</ELocationID><Abstract><AbstractText Label="BACKGROUND" NlmCategory="BACKGROUND">NGS data contains many machine-induced errors. The most advanced methods for the error correction heavily depend on the selection of solid k-mers. A solid k-mer is a k-mer frequently occurring in NGS reads. The other k-mers are called weak k-mers. A solid k-mer does not likely contain errors, while a weak k-mer most likely contains errors. An intensively investigated problem is to find a good frequency cutoff f<sub>0</sub> to balance the numbers of solid and weak k-mers. Once the cutoff is determined, a more challenging but less-studied problem is to: (i) remove a small subset of solid k-mers that are likely to contain errors, and (ii) add a small subset of weak k-mers, that are likely to contain no errors, into the remaining set of solid k-mers. Identification of these two subsets of k-mers can improve the correction performance.</AbstractText><AbstractText Label="RESULTS" NlmCategory="RESULTS">We propose to use a Gamma distribution to model the frequencies of erroneous k-mers and a mixture of Gaussian distributions to model correct k-mers, and combine them to determine f<sub>0</sub>. To identify the two special subsets of k-mers, we use the z-score of k-mers which measures the number of standard deviations a k-mer's frequency is from the mean. Then these statistically-solid k-mers are used to construct a Bloom filter for error correction. Our method is markedly superior to the state-of-art methods, tested on both real and synthetic NGS data sets.</AbstractText><AbstractText Label="CONCLUSION" NlmCategory="CONCLUSIONS">The z-score is adequate to distinguish solid k-mers from weak k-mers, particularly useful for pinpointing out solid k-mers having very low frequency. Applying z-score on k-mer can markedly improve the error correction accuracy.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Zhao</LastName><ForeName>Liang</ForeName><Initials>L</Initials><AffiliationInfo><Affiliation>Precision Medicine Research Center, Taihe Hospital, Hubei University of Medicine, Shiyan, China. s080011@e.ntu.edu.sg.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>School of Computing and Electronic Information, Guangxi University, Nanning, China. s080011@e.ntu.edu.sg.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Xie</LastName><ForeName>Jin</ForeName><Initials>J</Initials><AffiliationInfo><Affiliation>Precision Medicine Research Center, Taihe Hospital, Hubei University of Medicine, Shiyan, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Bai</LastName><ForeName>Lin</ForeName><Initials>L</Initials><AffiliationInfo><Affiliation>School of Computing and Electronic Information, Guangxi University, Nanning, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Chen</LastName><ForeName>Wen</ForeName><Initials>W</Initials><AffiliationInfo><Affiliation>Precision Medicine Research Center, Taihe Hospital, Hubei University of Medicine, Shiyan, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Wang</LastName><ForeName>Mingju</ForeName><Initials>M</Initials><AffiliationInfo><Affiliation>Precision Medicine Research Center, Taihe Hospital, Hubei University of Medicine, Shiyan, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Zhang</LastName><ForeName>Zhonglei</ForeName><Initials>Z</Initials><AffiliationInfo><Affiliation>Precision Medicine Research Center, Taihe Hospital, Hubei University of Medicine, Shiyan, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Wang</LastName><ForeName>Yiqi</ForeName><Initials>Y</Initials><AffiliationInfo><Affiliation>Precision Medicine Research Center, Taihe Hospital, Hubei University of Medicine, Shiyan, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Zhao</LastName><ForeName>Zhe</ForeName><Initials>Z</Initials><AffiliationInfo><Affiliation>School of Computing and Electronic Information, Guangxi University, Nanning, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Li</LastName><ForeName>Jinyan</ForeName><Initials>J</Initials><AffiliationInfo><Affiliation>Advanced Analytics Institute, Faculty of Engineering & IT, University of Technology Sydney, NSW 2007, Australia. jinyan.li@uts.edu.au.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2018</Year><Month>12</Month><Day>31</Day></ArticleDate></Article><MedlineJournalInfo><Country>England</Country><MedlineTA>BMC Genomics</MedlineTA><NlmUniqueID>100965258</NlmUniqueID><ISSNLinking>1471-2164</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName UI="D000465" MajorTopicYN="N">Algorithms</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D057225" MajorTopicYN="Y">Data Mining</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D059014" MajorTopicYN="Y">High-Throughput Nucleotide Sequencing</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D012107" MajorTopicYN="Y">Research Design</DescriptorName></MeshHeading></MeshHeadingList><KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">Error correction</Keyword><Keyword MajorTopicYN="N">Next-generation sequencing</Keyword><Keyword MajorTopicYN="N">z-score</Keyword></KeywordList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="entrez"><Year>2019</Year><Month>1</Month><Day>2</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2019</Year><Month>1</Month><Day>2</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2019</Year><Month>4</Month><Day>9</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>epublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">30598110</ArticleId><ArticleId IdType="doi">10.1186/s12864-018-5272-y</ArticleId><ArticleId IdType="pii">10.1186/s12864-018-5272-y</ArticleId><ArticleId IdType="pmc">PMC6311904</ArticleId></ArticleIdList><ReferenceList><Reference><Citation>Bioinformatics. 2009 Sep 1;25(17):2157-63</Citation><ArticleIdList><ArticleId IdType="pubmed">19542152</ArticleId></ArticleIdList></Reference><Reference><Citation>Bioinformatics. 2010 May 15;26(10):1284-90</Citation><ArticleIdList><ArticleId IdType="pubmed">20378555</ArticleId></ArticleIdList></Reference><Reference><Citation>Bioinformatics. 2010 Oct 15;26(20):2526-33</Citation><ArticleIdList><ArticleId IdType="pubmed">20834037</ArticleId></ArticleIdList></Reference><Reference><Citation>Nature. 2010 Oct 28;467(7319):1061-73</Citation><ArticleIdList><ArticleId IdType="pubmed">20981092</ArticleId></ArticleIdList></Reference><Reference><Citation>Genome Biol. 2010;11(11):R116</Citation><ArticleIdList><ArticleId IdType="pubmed">21114842</ArticleId></ArticleIdList></Reference><Reference><Citation>Bioinformatics. 2011 Feb 1;27(3):295-302</Citation><ArticleIdList><ArticleId IdType="pubmed">21115437</ArticleId></ArticleIdList></Reference><Reference><Citation>BMC Bioinformatics. 2011 Mar 29;12:85</Citation><ArticleIdList><ArticleId IdType="pubmed">21447171</ArticleId></ArticleIdList></Reference><Reference><Citation>Bioinformatics. 2011 Jun 1;27(11):1455-61</Citation><ArticleIdList><ArticleId IdType="pubmed">21471014</ArticleId></ArticleIdList></Reference><Reference><Citation>Genome Res. 2011 Jul;21(7):1181-92</Citation><ArticleIdList><ArticleId IdType="pubmed">21482625</ArticleId></ArticleIdList></Reference><Reference><Citation>Genome Res. 2012 Mar;22(3):557-67</Citation><ArticleIdList><ArticleId IdType="pubmed">22147368</ArticleId></ArticleIdList></Reference><Reference><Citation>Genome Res. 2012 Mar;22(3):549-56</Citation><ArticleIdList><ArticleId IdType="pubmed">22156294</ArticleId></ArticleIdList></Reference><Reference><Citation>Bioinformatics. 2012 Feb 15;28(4):593-4</Citation><ArticleIdList><ArticleId IdType="pubmed">22199392</ArticleId></ArticleIdList></Reference><Reference><Citation>Bioinformatics. 2013 Feb 1;29(3):308-15</Citation><ArticleIdList><ArticleId IdType="pubmed">23202746</ArticleId></ArticleIdList></Reference><Reference><Citation>Genome Biol. 2013 May 29;14(5):R51</Citation><ArticleIdList><ArticleId IdType="pubmed">23718773</ArticleId></ArticleIdList></Reference><Reference><Citation>Bioinformatics. 2013 Oct 1;29(19):2490-3</Citation><ArticleIdList><ArticleId IdType="pubmed">23853064</ArticleId></ArticleIdList></Reference><Reference><Citation>Bioinformatics. 2014 Oct;30(19):2723-32</Citation><ArticleIdList><ArticleId IdType="pubmed">24919879</ArticleId></ArticleIdList></Reference><Reference><Citation>Bioinformatics. 2014 Nov 1;30(21):3004-11</Citation><ArticleIdList><ArticleId IdType="pubmed">25015988</ArticleId></ArticleIdList></Reference><Reference><Citation>Bioinformatics. 2014 Sep 1;30(17):i356-63</Citation><ArticleIdList><ArticleId IdType="pubmed">25161220</ArticleId></ArticleIdList></Reference><Reference><Citation>Genome Biol. 2014;15(11):509</Citation><ArticleIdList><ArticleId IdType="pubmed">25398208</ArticleId></ArticleIdList></Reference><Reference><Citation>Bioinformatics. 2015 May 15;31(10):1569-76</Citation><ArticleIdList><ArticleId IdType="pubmed">25609798</ArticleId></ArticleIdList></Reference><Reference><Citation>Genome Res. 2015 Nov;25(11):1750-6</Citation><ArticleIdList><ArticleId IdType="pubmed">26447147</ArticleId></ArticleIdList></Reference><Reference><Citation>Bioinformatics. 2016 Aug 1;32(15):2369-71</Citation><ArticleIdList><ArticleId IdType="pubmed">27153708</ArticleId></ArticleIdList></Reference><Reference><Citation>Bioinformatics. 2017 Dec 1;33(23):3844-3851</Citation><ArticleIdList><ArticleId IdType="pubmed">28205674</ArticleId></ArticleIdList></Reference><Reference><Citation>Nat Methods. 2017 Nov;14(11):1072-1074</Citation><ArticleIdList><ArticleId IdType="pubmed">28945707</ArticleId></ArticleIdList></Reference></ReferenceList></PubmedData></pubmed><affiliations><list><country><li>Australie</li><li>République populaire de Chine</li></country></list><tree><country name="République populaire de Chine"><noRegion><name sortKey="Zhao, Liang" sort="Zhao, Liang" uniqKey="Zhao L" first="Liang" last="Zhao">Liang Zhao</name></noRegion><name sortKey="Bai, Lin" sort="Bai, Lin" uniqKey="Bai L" first="Lin" last="Bai">Lin Bai</name><name sortKey="Chen, Wen" sort="Chen, Wen" uniqKey="Chen W" first="Wen" last="Chen">Wen Chen</name><name sortKey="Wang, Mingju" sort="Wang, Mingju" uniqKey="Wang M" first="Mingju" last="Wang">Mingju Wang</name><name sortKey="Wang, Yiqi" sort="Wang, Yiqi" uniqKey="Wang Y" first="Yiqi" last="Wang">Yiqi Wang</name><name sortKey="Xie, Jin" sort="Xie, Jin" uniqKey="Xie J" first="Jin" last="Xie">Jin Xie</name><name sortKey="Zhang, Zhonglei" sort="Zhang, Zhonglei" uniqKey="Zhang Z" first="Zhonglei" last="Zhang">Zhonglei Zhang</name><name sortKey="Zhao, Zhe" sort="Zhao, Zhe" uniqKey="Zhao Z" first="Zhe" last="Zhao">Zhe Zhao</name></country><country name="Australie"><noRegion><name sortKey="Li, Jinyan" sort="Li, Jinyan" uniqKey="Li J" first="Jinyan" last="Li">Jinyan Li</name></noRegion></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
EXPLOR_STEP=$WICRI_ROOT/Sante/explor/MersV1/Data/PubMed/Checkpoint
HfdSelect -h $EXPLOR_STEP/biblio.hfd -nk 000832 | SxmlIndent | more
Ou
HfdSelect -h $EXPLOR_AREA/Data/PubMed/Checkpoint/biblio.hfd -nk 000832 | SxmlIndent | more
Pour mettre un lien sur cette page dans le réseau Wicri
{{Explor lien
|wiki= Sante
|area= MersV1
|flux= PubMed
|étape= Checkpoint
|type= RBID
|clé= pubmed:30598110
|texte= Mining statistically-solid k-mers for accurate NGS error correction.
}}
Pour générer des pages wiki
HfdIndexSelect -h $EXPLOR_AREA/Data/PubMed/Checkpoint/RBID.i -Sk "pubmed:30598110" \
| HfdSelect -Kh $EXPLOR_AREA/Data/PubMed/Checkpoint/biblio.hfd \
| NlmPubMed2Wicri -a MersV1
| This area was generated with Dilib version V0.6.33. |  |