Estimating the total genome length of a metagenomic sample using k-mers.
Identifieur interne : 000577 ( PubMed/Corpus ); précédent : 000576; suivant : 000578Estimating the total genome length of a metagenomic sample using k-mers.
Auteurs : Kui Hua ; Xuegong ZhangSource :
- BMC genomics [ 1471-2164 ] ; 2019.
English descriptors
- KwdEn :
- MESH :
- genetics : Microbiota.
- methods : Metagenomics.
- Algorithms, Datasets as Topic, High-Throughput Nucleotide Sequencing, Humans, Metagenome, Sequence Analysis, DNA, Software.
Abstract
Metagenomic sequencing is a powerful technology for studying the mixture of microbes or the microbiomes on human and in the environment. One basic task of analyzing metagenomic data is to identify the component genomes in the community. This task is challenging due to the complexity of microbiome composition, limited availability of known reference genomes, and usually insufficient sequencing coverage.
DOI: 10.1186/s12864-019-5467-x
PubMed: 30967110
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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Estimating the total genome length of a metagenomic sample using k-mers.</title><author><name sortKey="Hua, Kui" sort="Hua, Kui" uniqKey="Hua K" first="Kui" last="Hua">Kui Hua</name><affiliation><nlm:affiliation>MOE Key Laboratory of Bioinformatics Division and Center for Synthetic & System Biology, BNRIST, Beijing, 100084, China.</nlm:affiliation></affiliation></author><author><name sortKey="Zhang, Xuegong" sort="Zhang, Xuegong" uniqKey="Zhang X" first="Xuegong" last="Zhang">Xuegong Zhang</name><affiliation><nlm:affiliation>MOE Key Laboratory of Bioinformatics Division and Center for Synthetic & System Biology, BNRIST, Beijing, 100084, China. zhangxg@tsinghua.edu.cn.</nlm:affiliation></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2019">2019</date><idno type="RBID">pubmed:30967110</idno><idno type="pmid">30967110</idno><idno type="doi">10.1186/s12864-019-5467-x</idno><idno type="wicri:Area/PubMed/Corpus">000577</idno><idno type="wicri:explorRef" wicri:stream="PubMed" wicri:step="Corpus" wicri:corpus="PubMed">000577</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">Estimating the total genome length of a metagenomic sample using k-mers.</title><author><name sortKey="Hua, Kui" sort="Hua, Kui" uniqKey="Hua K" first="Kui" last="Hua">Kui Hua</name><affiliation><nlm:affiliation>MOE Key Laboratory of Bioinformatics Division and Center for Synthetic & System Biology, BNRIST, Beijing, 100084, China.</nlm:affiliation></affiliation></author><author><name sortKey="Zhang, Xuegong" sort="Zhang, Xuegong" uniqKey="Zhang X" first="Xuegong" last="Zhang">Xuegong Zhang</name><affiliation><nlm:affiliation>MOE Key Laboratory of Bioinformatics Division and Center for Synthetic & System Biology, BNRIST, Beijing, 100084, China. zhangxg@tsinghua.edu.cn.</nlm:affiliation></affiliation></author></analytic><series><title level="j">BMC genomics</title><idno type="eISSN">1471-2164</idno><imprint><date when="2019" type="published">2019</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Algorithms</term><term>Datasets as Topic</term><term>High-Throughput Nucleotide Sequencing</term><term>Humans</term><term>Metagenome</term><term>Metagenomics (methods)</term><term>Microbiota (genetics)</term><term>Sequence Analysis, DNA</term><term>Software</term></keywords><keywords scheme="MESH" qualifier="genetics" xml:lang="en"><term>Microbiota</term></keywords><keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Metagenomics</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Algorithms</term><term>Datasets as Topic</term><term>High-Throughput Nucleotide Sequencing</term><term>Humans</term><term>Metagenome</term><term>Sequence Analysis, DNA</term><term>Software</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Metagenomic sequencing is a powerful technology for studying the mixture of microbes or the microbiomes on human and in the environment. One basic task of analyzing metagenomic data is to identify the component genomes in the community. This task is challenging due to the complexity of microbiome composition, limited availability of known reference genomes, and usually insufficient sequencing coverage.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">30967110</PMID><DateCompleted><Year>2019</Year><Month>08</Month><Day>28</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>20</Volume><Issue>Suppl 2</Issue><PubDate><Year>2019</Year><Month>Apr</Month><Day>04</Day></PubDate></JournalIssue><Title>BMC genomics</Title><ISOAbbreviation>BMC Genomics</ISOAbbreviation></Journal><ArticleTitle>Estimating the total genome length of a metagenomic sample using k-mers.</ArticleTitle><Pagination><MedlinePgn>183</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1186/s12864-019-5467-x</ELocationID><Abstract><AbstractText Label="BACKGROUND" NlmCategory="BACKGROUND">Metagenomic sequencing is a powerful technology for studying the mixture of microbes or the microbiomes on human and in the environment. One basic task of analyzing metagenomic data is to identify the component genomes in the community. This task is challenging due to the complexity of microbiome composition, limited availability of known reference genomes, and usually insufficient sequencing coverage.</AbstractText><AbstractText Label="RESULTS" NlmCategory="RESULTS">As an initial step toward understanding the complete composition of a metagenomic sample, we studied the problem of estimating the total length of all distinct component genomes in a metagenomic sample. We showed that this problem can be solved by estimating the total number of distinct k-mers in all the metagenomic sequencing data. We proposed a method for this estimation based on the sequencing coverage distribution of observed k-mers, and introduced a k-mer redundancy index (KRI) to fill in the gap between the count of distinct k-mers and the total genome length. We showed the effectiveness of the proposed method on a set of carefully designed simulation data corresponding to multiple situations of true metagenomic data. Results on real data indicate that the uncaptured genomic information can vary dramatically across metagenomic samples, with the potential to mislead downstream analyses.</AbstractText><AbstractText Label="CONCLUSIONS" NlmCategory="CONCLUSIONS">We proposed the question of how long the total genome length of all different species in a microbial community is and introduced a method to answer it.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Hua</LastName><ForeName>Kui</ForeName><Initials>K</Initials><AffiliationInfo><Affiliation>MOE Key Laboratory of Bioinformatics Division and Center for Synthetic & System Biology, BNRIST, Beijing, 100084, China.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Department of Automation, Tsinghua University, Beijing, 100084, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Zhang</LastName><ForeName>Xuegong</ForeName><Initials>X</Initials><AffiliationInfo><Affiliation>MOE Key Laboratory of Bioinformatics Division and Center for Synthetic & System Biology, BNRIST, Beijing, 100084, China. zhangxg@tsinghua.edu.cn.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Department of Automation, Tsinghua University, Beijing, 100084, China. zhangxg@tsinghua.edu.cn.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>School of Life Sciences, Tsinghua University, Beijing, 100084, China. zhangxg@tsinghua.edu.cn.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2019</Year><Month>04</Month><Day>04</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="D066264" MajorTopicYN="N">Datasets as Topic</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D059014" MajorTopicYN="N">High-Throughput Nucleotide Sequencing</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D006801" MajorTopicYN="N">Humans</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D054892" MajorTopicYN="Y">Metagenome</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D056186" MajorTopicYN="N">Metagenomics</DescriptorName><QualifierName UI="Q000379" MajorTopicYN="Y">methods</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D064307" MajorTopicYN="N">Microbiota</DescriptorName><QualifierName UI="Q000235" MajorTopicYN="Y">genetics</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D017422" MajorTopicYN="N">Sequence Analysis, DNA</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D012984" MajorTopicYN="Y">Software</DescriptorName></MeshHeading></MeshHeadingList><KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">Distinct k-mers</Keyword><Keyword MajorTopicYN="N">Genome length</Keyword><Keyword MajorTopicYN="N">Metagenomics</Keyword><Keyword MajorTopicYN="N">Sequencing coverage</Keyword></KeywordList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="entrez"><Year>2019</Year><Month>4</Month><Day>11</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2019</Year><Month>4</Month><Day>11</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2019</Year><Month>8</Month><Day>29</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>epublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">30967110</ArticleId><ArticleId IdType="doi">10.1186/s12864-019-5467-x</ArticleId><ArticleId IdType="pii">10.1186/s12864-019-5467-x</ArticleId><ArticleId 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